Archives of Academic Emergency Medicine

Introduction: Traumatic injuries can affect respiration both directly and indirectly. This study aimed to evaluate the predictive factors of need for mechanical ventilation (MV) following traumatic injuries.

Methods: This Retrospective registry-based cross-sectional study comprised trauma patients admitted to a major referral trauma center in Iran, from March 28, 2019, to January 31, 2023, identified within the National Trauma Registry of Iran (NTRI). Logistic regression analysis was used to assess the association between demographic and clinical variables with the need for MV.

Results: A total of 2708 trauma patients with a mean age of 41.79 ± 21.84 (range:1-98) years were included (73.4% male). A total of 251 (9.3%) patients were admitted to the Intensive Care Unit (ICU); 113 (4.2%) experienced MV. The significant associated factors of need for MV based on the univariable analysis were age ≥ 65 years (p <0.001); penetrating trauma (p < 0.001) and falling (p = 0.01); private mode of transportation to ED (p < 0.001); site of injury (p < 0.001); heart rate ≥ 100/ minutes (p = 0.04); O2 saturation < 90 % on room air (p < 0.01); Glasgow Coma Scale (GCS) < 13 (p< 0.001); and injury Severity Score (ISS) ≥ 9 (p< 0.001). Based on the multivariate logistic regression analysis, the independent predictors of the need for MV in trauma patients were the site of injury (p < 0.001), GCS < 13 (p < 0.001), and ISS ≥ 9 (p < 0.001).

Conclusion: Based on the findings, ISS ≥ 9, GCS < 13, and site of injury were among the independent predictors of the need for MV following trauma.

Introduction: Determining the trauma patients’ prognosis is crucial for patients’ safety, triage, and appropriate management. This study aimed to evaluate the screening performance of Traumatic Emergency Room Major Injury Death At Least 24 hours (TERMINAL-24) score in predicting the mortality of trauma patients.

Methods: This cross-sectional study was conducted in the emergency department (ED) of a referral trauma center, between October 2023 and September 2024. The main goals of the project were determining the value of TERMINAL-24 score in predicting early (within 8 hours of admission to ED) and in-hospital mortality of multi-trauma patients as well as comparing the accuracy of TERMINAL-24 with other trauma severity scores (GAP, RGAP, NTS) in this regard.

Results: 963 multi-trauma patients were included in this study. The mean age of the patients was 37.75±17.10 years (73.2% male). 55 patients died in the emergency department and 46 patients died during hospitalization in other departments. Male gender (p = 0.009), older age (p =0.011), traffic accidents (p = 0.005), more critical vital signs (p = <0.001), admitting in neurosurgery ward (p < 0.001), and higher trauma severity (P < 0.001) were significantly associated with higher mortality rate. The area under the curve (AUC) of TERMINAL-24 score in predicting early and in-hospital mortality of trauma patients were 0.964 (95%CI: 0.937-0.991) and 0.954 (95%CI: 0.925-0.983), respectively. The specificity and sensitivity of TERMINAL-24 score for predicting early mortality at its best cut-off point (cut-off = 2.5) were 95.04% (95%CI: 93.43-96.28) and 96.36% (95%CI: 87.63-99.35), respectively. For predicting in-hospital mortality, these measures were 98.84% (95%CI: 97.88–99.37) and 87.13% (95%CI: 79.22-92.32), respectively (best cut-off = 2.5).

Conclusions: It seems that, TERMINAL-24 score has the same accuracy in predicting both early and in-hospital outcomes of trauma patients. Considering the calculation formula of this score and its simplicity, it can be used in pre-hospital and in-hospital settings to predict the outcome of trauma patients.

Introduction: The stroke scale for the mid-level personnel (SML) was designed for emergency medical services personnel to predict acute ischemic stroke due to large vessel occlusion (LVO) in both prehospital and in-hospital settings. This study aimed to validate and determine the appropriate cut point of the SML score in this regard.

Methods: This single-centered, prospective validation study to assess a novel LVO triage tool was performed in a tertiary care hospital in Bangkok. Patients presenting within 24 hours of onset of acute stroke were included in the study. The scale is designed for mid-level providers and emergency medical services (EMS) personnel including paramedics, emergency medical technicians (EMTs) and emergency department (ED) nurses. LVO was confirmed by brain and neck computed tomography angiography (CTA). Area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), likelihood ratios (LRs), and correctly classified instances (CCI) were calculated. Youden’s index was used to determine an appropriate cut point of the SML score for LVO prediction.

Results:  200 cases with the median age of 64.0 (56.5-73.0) years were included (53.5% female). 83 (41.5%) cases were affiliated to the LVO and 117 (58.5%) to the non-LVO group.

The median SML scores for non-LVO and LVO stroke patients were 3 (2 - 3) and 6 (5 - 7), respectively (p < 0.001). The most common presentations in both groups were facial palsy, arm weakness and speech impairment or dysarthria. There was significantly higher prevalence of neglect (8 (6.8%) vs. 5 (4.3%); p < 0.001) and eye deviation (39 (47%) vs. 29 (35%); p < 0.001) in the LVO stroke group than in the non-LVO group. LVO patients scored higher in all categories when compared to non-LVO cases. SML scores of 4 and 5 had the highest Youden's index of 0.82 and 0.67, respectively. SML score of 4 yielded the highest correctly classified instances (CCI) of 90% with sensitivity and specificity of 96.4% (95% confidence interval (CI): 89.9-99.3%) and 85.3% (95% CI: 77.6-91.2), respectively. SML score of 4 also achieved the lowest negative LR of 0.04 and an odds ratio of 157 (95% CI: 46.7-521).  The AUC of SML in cutoff point of 4 was 0.901 (95%CI: 0.853 - 0.949).

Conclusions: SML score may be helpful for mid-level medical providers and also EMS personnel in detecting LVOs since prehospital phase. According to the results, we recommend a cut point SML score ≥ 4 for enhanced sensitivity and NPV.

Introduction: Although several clinical prediction models (CPMs) have been developed for identifying acute dizziness with central causes, their application in clinical practice remains unclear. This study aimed to evaluate the accuracy and clinical utility of four CPMs in identifying dizziness with central lesions.

Methods: This single-center, retrospective, diagnostic accuracy study was conducted at the ED of Aomori Hospital, Japan, from April to March 2023. The area under the receiver operating characteristic curve (AUROC) of four risk stratification models (ABCD2, TriAGe+, PCI, and Sudbury) in predicting dizziness with central causes were evaluated considering the brain imaging (computed tomography (CT) scan and magnetic resonance imaging (MRI)) findings, interpreted by a neurologist or neurosurgeon, as the gold standard. Calibration was evaluated visually using calibration plots. Additionally, analyses of efficacy, safety, and clinical utility using a decision curve were conducted.

Results: Of the 3,606 patients identified, 2,958 with the mean age of 65.3 ± 16.4 (range: 15-97.) years were included in the final analysis (64.7% female). 155 (5.2 %) were diagnosed with central lesions. The AUROCs were 0.67 (95% confidence interval (CI): 0.62–0.71) for ABCD2, 0.80 (95% CI: 0.76–0.84) for TriAGe+, 0.82 (0.78-0.86) for PCI, and 0.85 (95% CI: 0.82–0.88) for Sudbury. TriAGe+, PCI, and Sudbury demonstrated good calibration. Among these, the Sudbury model demonstrated the highest diagnostic efficiency, was the only model to meet safety criteria, and provided the highest net benefit in decision curve analysis, particularly at lower predicted prevalence thresholds.

Conclusion: The TriAGe+, PCI, and Sudbury models demonstrated strong discriminatory performance and reliable calibration when applied during ED admission at a community hospital. Particularly, the Sudbury model may reduce false-negative outcomes for central lesions, thereby potentially minimizing the need for unnecessary neuroimaging in patients identified as low-risk.

Introduction: Trauma is a significant global public health concern and the leading cause of morbidity and mortality in children. This study aimed to assess the independent predictors of trauma severity as well as mortality in pediatric patients admitted to the intensive care unit (ICU).

Methods: In this cross-sectional study, following the STROBE checklist, we retrospectively analyzed the clinical and baseline characteristics of pediatric patients with trauma injuries admitted to the ICU of Children’s Hospital of Zhejiang University School of Medicine, China, over a decade.

Results: 951 pediatric patients with a mean age of 4.79 ± 3.24 years (60.78% Boys) were studied (mortality rate 8.41%). Significant associations were observed between ISS and place of residence (p = 0.021), location of the injury (p = 0.010), year of injury (p <0.001), and injury mechanism (p <0.001). The two independent factors of trauma severity were the year of injury (β  = 0.47; 95%CI: 0.28 – 0.65) and injury mechanism (β = -0.60; 95%CI: -0.88 - -0.31).

Significant differences were observed between survived and non-survived regarding age (p <0.001), ISS score (p <0.001), time elapsed from injury to ICU (p <0.001), duration of mechanical ventilation (p <0.001), GCS score (p <0.001), and the proportion of patients requiring mechanical ventilation (p <0.001 ). The results of multivariate analysis indicated that age (OR = 0.805; 95%CI: 0.70 - 0.914; p = 0.001) and GCS score at ICU admission (OR = 0.629; 95%CI: 0.53 - 0.735; p < 0.001) acted as protective factors, whereas mechanical ventilation in the ICU (OR = 7.834; 95%CI: 1.766 - 34.757; p = 0.007)  and ISS score at ICU admission (OR = 1.088; 95%CI: 1.047 - 1.130; p < 0.001) served as risk factors for mortality.

Conclusion: Automobile-related injuries represent the leading cause of trauma in children, with escalating severity scores year over year among pediatric patients admitted to the ICU with trauma injuries. Based on the findings the independent predictors of mortality of pediatric trauma patients admitted to the ICU were age, GCS score at ICU admission; mechanical ventilation in the ICU, and ISS score at ICU admission. Also, the year of injury and injury mechanism were independent predictors of trauma severity.

Introduction: One of the main contributing factors of emergency department (ED) crowding is ED patient boarding. This study aimed to assess the factors influencing length of stay (LOS) in intensive care unit (ICU) and in-hospital mortality (IHM) among ICU-admitted ED boarded cases.

Methods: A retrospective cohort study was conducted on adult patients at a tertiary care hospital in Lebanon who required ICU admission and stayed for 6+ hours in the ED during one year. The independent predictive factors of LOS in ICU and IHM were studied using multivariable logistic regression analysis.

Results: Out of 583 patients (mean age 69.5 years; 61.6% male), 12.8% died in hospital. 25.5% had a prolonged ICU stay (≥7 days) with a median LOS of 3 days. Prolonged ICU LOS was associated with previous cancer diagnosis (adjusted odds ratio (aOR)=1.66), prehospital bedridden status (>5 days, aOR=4.41), ED vasopressor use (aOR=1.86), extended ED boarding (aOR=1.03), IHM (aOR=3.37), and not being married (aOR=2.0). IHM was associated with abnormal Modified Shock Index at ED triage (aOR=7.35), ED mechanical ventilation use (aOR=6.07), ED triage Shock Index ≥1.3 (aOR=18.25), and long ICU stay (aOR=7.48). ED-triage Saturation of Peripheral Oxygen (SPO₂) level was negatively associated with IHM (aOR=0.89).

Conclusion: It seems that, ED boarding of ICU patients is associated with an increase in ICU LOS, which is associated with an increase in IHM. Hospitals should allocate resources to reduce ED boarding and improve outcomes for critically ill patients.

Introduction: Understanding the epidemiological patterns of poisoning cases in specific regions is essential for health authorities to implement preventive measures and strategic planning. This study aimed to describe the epidemiologic characteristics of acute poisoning cases registered in Tehran province’s emergency medical services (EMS).

Methods: This retrospective cross-sectional study was conducted on all registered acute poisoning cases from 2022 to 2024 in the Asayar database of Tehran Province’s EMS. The cases were included through census sampling and descriptive analysis was used for evaluating the epidemiologic characteristics of registered cases.

Results: 76,113 acute poisoning cases were registered by Tehran Province EMS during the study period. The mean age of cases was 34.3 ± 15.0 years (59.1% male). The most frequent method of poisoning was oral, with 71,521 (94.0%) cases, and inhalational, with 3,236 (4.2%) cases. The highest number of cases was reported in the eastern region of Tehran with 15,058 cases. Seasonal distribution of poisonings was as follows: 20,201 (26.6%) cases in summer, 21,322(28.0%) cases in winter, 21,105 (27.7%) cases in autumn, and 13,485 (17.7%) cases in spring. Most poisonings occurred in residential settings, accounting for 72,194 (94.9%) cases. The most frequent used antidote was naloxone, in 12,662 (16.6%) cases, and atropine, in 961 (1.3%) cases.

Conclusion: Based on the findings of this study, the most vulnerable population groups to the poisoning were young individuals, males, and those with a history of psychiatric illness and substance abuse, predominantly affected by oral route. The geographical and temporal distribution of poisonings highlights the need for targeted preventive interventions, public education, and enhancement of prehospital emergency service infrastructure in high-risk areas.

Introduction: Predicting the number of emergency medical team (EMT) consultations that are needed following a natural or man-made disaster can help improve decisions regarding the dispatch and withdrawal of these teams. This study aimed to predict the number of consultations by EMTs using the K value and constant attenuation model.

Methods: Data were collected using the Japan-Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) and Minimum Data Set (MDS) for five disasters in Japan and one disaster in Mozambique. We compared the number of consultations, which was predicted based on K value and constant attenuation model with actual data collected with J-SPEED/Minimum Data Set (MDS) tools.

Results: The total number of EMT consultations per disaster ranged from 684 to 18,468. The predicted curve and actual K data were similar for each of the disasters (R² from 0.953 to 0.997), but offset adjustments were needed for the Kumamoto earthquake and the Mozambique cyclone because their R² values were below 0.985. For the six disasters, the difference between the number of consultations predicted based on K values and the measured cumulative number of consultations ranged from ±1.0% to ± 4.1%.

Conclusions: The K value and constant attenuation model, although originally developed to predict the number of patients with COVID-19, provided reliable predictions of the number of EMT consultations required during six different disasters. This simple model may be useful for the coordination of future responses of EMTs during disasters.

Introduction: Code stroke is a framework to reduce time and improve the quality of care in the prehospital setting. However, increased scene time, delays, and other barriers in the prehospital setting necessitate updating the current protocol. This study aimed to update the Iranian national code stroke protocol for the prehospital setting.

Methods: This study represents the results of the second phase of the Iranian Comprehensive Stroke Code Management Program, a mixed methods study. We used the Caspian scientific 10-step method to update this protocol, which included a literature review, critical appraisal, extraction of recommendations, face-content validity, the Delphi method, RAND method, expert panel, stakeholders, and publishing and printing. We divided the updated protocol into three stages (on scene, ambulance care, and on admission).

Results: Twenty experts (55% nurses; mean age 40.7±9.1 years, experience 15.9±7.9 years) were enrolled. On-Scene focuses on rapid ABC (airway, breathing, circulation) assessment, BEFAST (balance, eyes, face, arm, speech, and time) criteria, blood glucose check, and on-scene time under 5 minutes. Ambulance Care Involving SAMPLER (Symptoms, Allergies, Medications, Past medical history, Last time the patient was seen normally, Events leading up to the emergency medical service call, and Risk factor) history-taking, maintaining oxygen saturation ≥94%, symptom/witness documentation, electrocardiography (ECG) for cardiac-stroke cases, master's degree (MSN)-led transport coordination, and neurology team alerts and in-hospital admission ensuring precise handover, 724 pager alerts, stroke code clocks, computed tomography (CT)-ready team, and protocol updates via joint committees.

Conclusion: The main points were the stroke clock, pager 724, direct delivery to computed tomography scan, administering BEFAST, and reducing scene time. We recommend that each center to enhance the infrastructure and resources for implementation of these updates. In the next phase, we will implement and evaluate this protocol.

Introduction: Calcium gluconate (CG) administration during cardiopulmonary resuscitation (CPR) has not been recommended in routine clinical practice. This study examined the impact of prehospital CG administration on outcomes of out-of-hospital cardiac arrest (OHCA) cases.

Methods: This retrospective cohort study collected data on adult patients aged >18 years who experienced non-traumatic OHCA and were transported by the emergency medical service (EMS) to the emergency department. Data on return of spontaneous circulation (ROSC) at the scene, survival to hospital admission, and survival to hospital discharge were obtained from EMS reports and electronic medical records and compared between OHCA cases who received or didn’t receive CG.

Results: In total, 215 adult patients with non-traumatic OHCA were enrolled in this study. Among them, 107 received CG and 108 didn’t receive. In particular, CG administration was associated with a lower rate of ROSC at the scene compared with cases without its administration (8.6% lower). The likelihood of ROSC at the scene was 0.75 times that of those who did not receive CG. CG administration was associated with a lower survival to hospital admission (16.48% lower). The likelihood of survival to hospital admission was 0.42 times that of patients who did not receive CG. In addition, survival to hospital discharge was 7.37% lower in patients who received CG, and the likelihood of survival to hospital discharge was 0.21 times that of those who did not receive CG.

Conclusions: Prehospital CG administration by the EMS team did not improve ROSC in the scene, survival to hospital admission, or survival to hospital discharge. The findings highlight the need for selective use of calcium based on guideline-recommended indications rather than empirical administration.

Introduction: Angiogenesis through restoration of blood supply to the ischemic myocardium is a pivotal process that contributes to cardiac repair and leads to improvement of myocardial function. This study was conducted to evaluate cardioprotective effects of Diosgenin against myocardial infarction (MI) with focus on angiogenesis, myocardial fibrosis, and oxidative stress.

Methods: 4 groups of male Wistar rats were considered for this study: (1) sham, (2) MI, (3) MI+Vehicle and (4) MI+Diosgenin. MI model was created by occluding left anterior descending (LAD) artery for 30 minutes and reperfusion was established for 14 days by opening this artery. Diosgenin (50 mg/kg) was given orally to the rats for 21 days (from 7 days before MI induction until the end of the 14-day reperfusion period). Cardiac injury markers including troponin I, creatine kinase-MB (CK-MB), and lactate dehydrogenase (LDH) were measured using enzyme-linked immunosorbent assay (ELISA), same as cardiac stress oxidative markers (superoxide dismutase (SOD), Malondialdehyde (MDA), reduced glutathione (GSH)). Echocardiography was used to measure heart function parameters and myocardial fibrosis was assessed via a specific tissue staining named Masson׳s trichrome. Blood vessel staining kit was used to assess left ventricular angiogenesis.

Results: Ischemia-reperfusion injury increased serum levels of troponin I, CK-MB and LDH, as well as cardiac malondialdehyde (MDA) and myocardial fibrosis. MI also decreased myocardial function (Ejection fraction (EF)% and Fractional shortening (FS)%) and Diosgenin treatment reversed these parameters. Capillary density as marker of angiogenesis significantly increased in all of MI groups. However, development of angiogenesis was significantly higher in Diosgenin group compared with MI group.

Conclusion: Diosgenin exerts cardioprotective effects against ischemia-reperfusion injury by strengthening cardiac antioxidant defense and reducing deposition of collagen fibers. It seems that the strengthening of angiogenesis in heart tissue is one of the main mechanisms of Diosgenin to increase the heart's resistance against ischemia.

Introduction: A growing area is the use of ChatGPT in simulation-based learning, a widely recognized methodology in medical education. This study aimed to evaluate ChatGPT’s ability to generate realistic simulation scenarios to assist faculty as a significant challenge in medical education.

Method: This study employs a qualitative research design and thematic analysis to interpret expert opinions. The study was conducted in two phases. Scenario generation via ChatGPT and expert review for validation. We used ChatGPT (GPT-4) to create clinical scenarios on cardiovascular topics, including cardiogenic shock, postoperative cardiac tamponade after heart surgery, and heart failure. A panel of five experts, four nurses with expertise in emergency medicine and critical care and an anesthesia specialist, evaluated the scenarios. The experts' feedback, strengths and weaknesses, and proposed revisions from the expert discussions were analyzed via thematic analysis. Key themes and proposed revisions were identified, recorded, and compiled by the research team.

Results: The clinical scenarios were produced by ChatGPT in less than 5 seconds per case. The thematic analysis identified six recurring themes in the experts' discussions: clinical accuracy, the clarity of learning objectives, the logical flow of patient cases, realism and feasibility, alignment with nursing competencies, and level of difficulty. All the experts agreed that the scenarios were realistic and followed clinical guidelines. However, they also identified several errors and areas that needed improvement. The experts identified and documented specific errors, incorrect recommendations, missing information, and inconsistencies with standard nursing practices.

Conclusion: It seems that, ChatGPT can be a valuable tool for developing clinical scenarios, but expert review and refinement are necessary to ensure the accuracy and alignment of the generated scenarios with clinical and educational standards.

Introduction: Emergency department discharge destination is an important topic in both clinical practice and management. This study aimed to analyze the association of Care Complexity Individual Factors (CCIFs) with discharge destinations in patients who visit the emergency department (ED).

Methods: This is a retrospective cohort study with consecutive sampling, including all patients who visited the ED of a tertiary hospital during 2021-2022. Data were collected from electronic health records. The main study outcomes were discharge destinations (mortality, intensive care unit admission, hospitalization, left without being seen/discharge against medical advice, and home discharge) and 26 CCIFs. Independent multinomial logistic regression was used for assessing the association of each factor and the discharge destinations, adjusted for age, sex, and triage level. All analyses were performed with R, version 4.3.2.

Results: A total of 35,383 patients were included. Of these, 60.8% were home discharged, 34.1% were hospitalized, 2.6% were transferred to the intensive care unit, 2.1% were left without being seen, and 0.4% died. The presence of CCIFs was a risk factor of ED mortality (odds ratio (OR): 13.49 [95% confidence interval (CI): 4.99;36.46]), intensive care unit admission (OR:1.26 [95%CI:1.08;1.47]), and hospitalization (OR: 1.62 [95%CI:1.53;1.71]), whilst the presence of care complexity factors was a protective factor of discharge against medical advice (OR:0.64 [95%CI:0.55;0.74]).

Conclusion: The discharge destinations from the ED showed strong associations with the patient’s complexity factors. Health professionals should consider these relationships for the design of early detection strategies and as an aid in decision-making, to ensure equity and quality of care.

Introduction: High stress hyperglycemia ratio (SHR) and low hemoglobin-to-red blood cell distribution width ratio (HB/RDW) are each known predictors of mortality in acute ischemic stroke (AIS). This study aimed to assess the predictive performance of high SHR (≥1.18) and low HB/RDW (≤0.76) together in stroke patients treated with thrombolysis.

Methods: We retrospectively collected data from 345 AIS patients treated with thrombolysis. HB/RDW values were obtained from pre-recombinant tissue plasminogen activator complete blood counts; while fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels were measured in the morning after an 8–14-hour overnight fast. Patients were categorized into four groups based on SHR and HB/RDW levels. We used multivariable Poisson regression with robust variance to estimate risk ratios (RRs) and 95% confidence intervals (CIs). Models assessed associations with in-hospital mortality (IHM), early neurological deterioration (END), and functional outcomes at discharge and 3 months, adjusting for age, sex, prior stroke, pre-existing disability, myocardial infarction, atrial fibrillation, heart failure, chronic kidney disease, and malignancy. Propensity score weighting analysis was further conducted as a sensitivity analysis.

Results: Among 345 patients, only 37 were in the high SHR (SHR+) and low HB/RDW (HB/RDW+) group. A total of 65 patients (18.8%) died during hospitalization. The SHR+ HB/RDW+ group had significantly higher risks of IHM (adjusted RR: 9.97, 95% CI: 4.95–20.08), END (adjusted RR: 2.95, 95% CI: 1.51–5.77), 3-month mortality (adjusted RR: 6.23, 95% CI: 3.49–11.12), and poor 3-month functional outcomes (adjusted RR: 2.86, 95% CI: 2.01–4.06) compared to the SHR- HB/RDW- group. These associations remained robust across sensitivity analyses. The combination of SHR ≥1.18 and HB/RDW ≤0.76 predicted IHM with an AuROC of 0.78 (95% CI: 0.73–0.83). Although the combined biomarker improved sensitivity and net benefit, its AUROC was not statistically superior to that of individual markers.

Conclusions: Combined high SHR and low HB/RDW levels at admission significantly predict poor outcomes in thrombolysis-treated AIS, performing better than either biomarker alone. Further validation in larger, diverse cohorts is warranted.

Introduction: Delays in accessing an appropriate level of care can lead to significant morbidity or even mortality of trauma patients. This study aimed to develop a simplified prehospital predictive model to determine the need for tertiary care trauma centers (TTC), enabling timely and appropriate transport decisions by emergency medical service (EMS) teams.

Methods: This is a retrospective cohort study conducted at the emergency department (ED) of Ramathibodi Hospital between January 2020 and April 2024. Prehospital trauma patients aged ≥15 years who were transported by EMS were included in the study. Patients were divided into two groups with and without the need for TTC, and the independent predictive factors of the need for TTC were explored using multivariable regression analysis.

Results: The study included 440 trauma patients, with 31.1% requiring TTC. The predictors of the need for TTC included age (coefficient (Coef.) -0.003; 95% confidence interval (CI): -0.018 to 0.012; P=0.693), traffic mechanism (Coef. 0.848; 95%CI: 0.150 to 1.546; P=0.017), respiratory rate (Coef. 0.044; 95%CI: -0.037 to 1.124; P=0.285), heart rate (Coef. -0.004; 95%CI: -0.020 to 0.012; P=0.610), and Glasgow Coma Scale (Coef. -0.312; 95%CI: -0.451 to -0.173; P<0.001). The predictive model categorized patients into low, moderate, and high-risk groups. Patients who were categorized in the high-risk group showed a positive likelihood ratio (LHR+) of 14.88 for requiring TTC. The model achieved an area under the receiver operating characteristic curve (AuROC) of 73%, indicating the good discriminative ability of this prediction model.

Conclusions: The predictive model classifies trauma patients into three risk groups based on five prognostic variables, which are able to predict the likelihood of requiring TTC. Internal validation has verified its high level of accuracy in trauma triage.

Introduction: Several studies suggest a causal link between psychoactive agents and motor vehicle accidents (MVA). This study aimed to evaluate the impact of substance abuse and alcohol intoxication on the prognosis of high-speed MVA victims.

Methods: This is a single-center retrospective cross-sectional study involving adult multiple trauma cases who were admitted to the emergency department for high-speed MVA and underwent toxicological screening. The cohort was conducted based on two main outcomes; the survival status and the neurological outcomes.

Results: 894 patients with the mean age of 27.8 ± 9.24 (range:18-37) years were studied (97.9% male). The most common indicators of severity were car rollover and ejection from the car. 296 of the patients had severe traumatic brain injury (TBI). 622 of the patients had a positive toxicological screening, with benzodiazepines (51.2%) and alcohol (26.6%) being the most commonly abused substances. The mortality rate was 5.8% and 12.1% of the patients had unfavorable neurological outcomes upon discharge. On multivariate logistic regression, predictors of mortality among high-speed MVA victims were report of a death at the scene (adjusted odds ratio (aOR): 2.529; 95% confidence interval (CI): 1.026-6.232; p = 0.044), severe TBI, the presence of dilated pupils (aOR: 11.074; 95% CI: 1.293-94.812; p = 0.028), hypotension (aOR: 0.456; 95% CI: 0.227-0.916; p = 0.027), and hypoxia (aOR: 2.95; 95% CI: 1.46-5.95; p = 0.003). Predictors of unfavorable neurological outcomes were report of a death at the scene (aOR: 3.133; 95% CI: 1.445-6.791; p = 0.004),  positive toxicology screening (aOR: 3.30; 95% CI:1.68-10.204; p = 0.038), severe TBI,  the presence of hypoxia (aOR: 2.96; 95% CI:1.645-5.319; p = 0.000), hypotension (aOR: 0.437; 95% CI: 0.252-0.758; p = 0.003), and bleeding (aOR: 0.287; 95% CI: 0.164-0.501; p < 0.001).

Conclusion: A concerning proportion of high-speed MVA victims had a positive toxicology screening. Although intoxication did not increase mortality of high-speed MVAs, it was a significant predictor of unfavorable neurological outcomes of survivors.

Introduction: An accurate emergency department (ED) diagnosis is critically important for providing proper treatment during the so-called “Golden Hour.” This study aimed to evaluate the agreement between admitting and discharge diagnoses in ED.

Method: This retrospective cross-sectional study was conducted over the course of 6 months in the emergency department (ED) of a tertiary care center. The main aim of the study was to evaluate the agreement between admission and hospital discharge diagnoses. The patients were categorized into two groups based on whether the admitting and discharge diagnoses were matched or mismatched. The reasons for diagnostic discrepancies, as well as their impact on patient outcomes, were assessed.

Results: A total of 6812 cases with mean age of 43.2 ± 17.9 (range: 1–95 years) years were included (59.30% male). The admitting and discharge diagnoses were matched in 5585 (81.99%) cases and mismatched in 1227 (18.01%) cases (7.2% were completely unmatched). The proportion of mismatched diagnoses did not differ significantly between males and females (p = 0.0977). Mismatched diagnoses were significantly more common in 0–15 years age group (37.86%), and the lowest proportion was seen in patients aged 15–65 years (9.65%) (p < 0.001). The most frequent reason for diagnostic discrepancy was “writing chronic disease as discharge diagnosis (relabeling),” (37.08%). Other contributing factors included radiological tests after hospital admission (20.37%), physical examination findings (18.1%), additional laboratory tests (15.81%), and other causes (8.57%). A change in diagnosis impacted the clinical outcomes of 103 (8.39%) patients.

Conclusion: Diagnostic agreement between ED and discharge diagnoses was observed in 81.99% of cases, with a 7.2% complete mismatch rate. The most frequent causes were discharge relabeling and delayed investigations. These discrepancies had measurable impacts on management, hospital stay, and mortality.

Introduction: Calcium channel blocker (CCB) poisoning is a critical toxicological emergency that can result in severe complications, particularly cardiovascular effects. This study aimed to evaluate the accuracy of Machine learning (ML) models in predicting the outcomes of CCB poisoning.

Methods: This retrospective cross-sectional study analyzed the medical records of patients diagnosed with CCB poisoning at Loghman Hakim Hospital between 2019 and 2024. The accuracy of machine learning (ML) models in predicting the outcomes of CCB poisoning and identifying its predictive factors was evaluated. Various ML models, including XGBoost, CatBoost, Random Forest, and AdaBoost, were trained on clinical and laboratory data. Then, feature selection was performed to identify the most relevant variables. The hold-out set was randomly selected to avoid selection bias. Model performance was assessed using accuracy, precision, recall, F1-score, and macro-averaged area under the receiver operating characteristic (ROC) curve (AUC).

Results: 274 CCB poisoning cases with the mean age of 31.99± 17.47 (range: 1.5 to 89) years were evaluated (70.4% female). Feature selection identified 18 key prognostic factors, including body temperature, whole bowel irrigation, need for cardiology consultation, arterial oxygen saturation, Glasgow coma scale (GCS)-eye response, electrocardiography (ECG) findings, serum level of alkaline phosphatase (ALP), pH-venous blood gas (VBG), HCO₃-VBG, serum level of lactate dehydrogenase (LDH), blood sugar, pulse rate, fraction of inspired oxygen (FiO2), time elapsed from ingestion to admission, troponin, serum level of alanine aminotransferase (ALT), serum level of creatinine, and serum level of potassium. Among the ML models, XGBoost and CatBoost demonstrated the highest predictive performance, with macro-averaged AUC values of 0.9899 (95%confidence interval (CI): 0.98-0.99) and 0.9983 (95%CI: 0.997-0.999), respectively. These models outperformed traditional statistical approaches, providing enhanced risk stratification for patients with CCB poisoning.

Conclusion: This study highlights the potential of ML-based models for predicting outcomes in CCB poisoning, offering a data-driven framework for early risk stratification. The superior performance of XGBoost and CatBoost suggests their clinical applicability. Future research should focus on external validation in multi-center settings and real-time integration into clinical decision-making systems.

Introduction: Many international search and rescue teams were deployed to the devastating earthquake of Southeastern Turkey and Northern Syria on February 6^th, 2023, including the Jordan International Search and Rescue Team (JSAR). This study aims to explore the challenges faced by the JSAR team members during their deployment.

Methods: We employed a qualitative face-to-face semi-structured interview approach. Eighteen respondents were interviewed using an interview guide. Interviews took between 25 and 60 minutes (mean 45 minutes). Data were transcribed verbatim and an inductive thematic approach was used to analyze data and develop codes, categories, and themes.

Results: The challenges were categorized into three main themes; logistical, coordination, and environmental. Logistical challenges included delays in deployment due to government and flight arrangements, difficulties in transporting excess equipment, and a lack of fuel upon arrival that led to delays in setting up camp and heating. Coordination challenges involved disruption in operation schedule and difficulties working with local volunteer responders. Environmental challenges encompassed extreme cold temperatures, which affected personnel comfort and performance, and recurrent aftershocks, which complicated rescue operations and posed safety risks. 

Conclusion: The JSAR experience highlights that technical readiness alone is insufficient for effective disaster response. Findings from this study underscore significant gaps in logistics, coordination, and environmental adaptation. These gaps can be addressed through improved pre-deployment coordination, context-specific resource planning, and better collaboration mechanisms between host countries and international teams, which would be crucial for enhancing the effectiveness of international search and rescue operations. Host governments, International Search and Rescue Advisory Group (INSARAG) stakeholders, and emergency management bodies can build on these lessons to better integrate specialized teams, reduce procedural delays, and enhance global disaster response systems.

Introduction: Drug therapy-related problems (DTRP) can lead to avoidable negative health consequences, particularly during hospital admissions. This study aimed to assess the frequency, causes, and associated factors of DTRPs, which are detected by clinical pharmacists’ interventions.

Methods: This is a prospective cross-sectional study of patients admitted to the medical wards of Fakeeh University Hospital, UAE, over a three-month period from September 2022 to December 2022. The data of patients who were assessed by clinical pharmacists regarding the pretense and causes of DTRPs were collected and analyzed using SPSS version 27.0.

Results: 310 patients with the mean age of 33.43 ± 19.98 years were studied (53.9% male). The highest percentage of patients were Asian (31.0%) and Arabs (30.6%). 79 (25.4%) cases had no DTRPs, while 231 (74.6) had DTRPs. The surgical ward had the highest frequency of DTRPs (41.0%). Improper drug selection with 79 cases, drug use without indication with 73 cases, and sub-therapeutic dosage with 26 cases were among the most common causes of DTRPs. Alcohol intake (p= 0.03), food allergy (p = 0.02), age group 31-40 years (p = 0.04), presence of co-morbidities (p = 0.01), family history of diseases (p = 0.02), and admission to the intensive care unit (ICU) (p = 0.01) were amongst the significantly associated factors of DTRPs. The acceptance status for clinical pharmacists’ interventions were complete in 90.0% of cases, partial in 4.1 %, and rejection in 5.9%.

Conclusion: The study findings show a high prevalence of DTRPs due to drug/dose selection and drug use without indication. It seems that the participation of clinical pharmacists in multidisciplinary teams together with the presence of closed loop medication management facilitates the detection and correction of DTRPs.

Introduction: Smart glasses with an augmented reality workflow have emerged as a new tool for triage in mass casualty incidents (MCIs). This study aimed to investigate the accuracy and time efficiency of smart glasses in MCIs triage.

Methods: A retrospective field exercise study was conducted in November 2024 at EMS Srinagarind Hospital, Thailand. All participants performed self-assessments and used smart glasses for triage sieve. Data were recorded in terms of accuracy and time required for triage.

Results: A total of 108 participants were enrolled, with a mean age of 33.4 years, of whom 57.4% were female. The smart glasses group achieved the highest accuracy in triage level 1, with 98.3% compared to 79.3% in the self-assessment group (P < 0.001). The smart glasses group also completed triage significantly faster than the self-assessment group, with a time of 23.5 versus 72.4 seconds for triage level 1 and 31.3 versus 89.1 seconds for level 2.

Conclusion: The use of smart glasses with an augmented reality workflow for triage sieve in MCIs is beneficial, improving both accuracy and evaluation time for patients in triage levels 1 and 2.

Introduction: Various tools have been developed to determine the priority of radiography in trauma patients. This study aimed to investigate the role of machine learning models in predicting chest injuries following multiple trauma.

Methods: We used the database of a comprehensive cross-sectional survey conducted in 2015. Eight machine learning models were developed using demographic characteristics, physical exam findings, and radiologic results of 2860 patients.

Results: Area under the receiver operating characteristic curve (AUC) was greater than 0.96 in Random Forest, Gradient Boosting, XGBoost, Decision Tree, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbors (KNN), and Neural Network models. The random forest model, XGBoost and Gradient Boosting had the highest accuracy (0.99). Sensitivity was also highest in the Gradient Boosting, XGBoost and KNN models (0.99). The specificity of all of the models in predicting chest radiography outcomes of multiple trauma patients was higher than 0.97, except for logistic regression and SVM (0.912 and 0.885 respectively).

Conclusions: Our study highlights the strong potential of machine learning models, especially Random Forest and Gradient Boosting, in predicting chest trauma outcomes with high accuracy and sensitivity.

Introduction: Traumatic Brain Injury (TBI) is one of the leading causes of mortality and severe disability worldwide. This study aimed to develop and optimize machine learning (ML) algorithms to predict abnormal brain computed tomography (CT) scans in patients with mild TBI.

Methods: In this retrospective analyses, the outcome was dichotomized into normal or abnormal CT scans, and univariate analyses were employed for feature selection. Then SMOTE was applied to address class imbalance. The dataset was split 80:20 for training/testing, and multiple ML algorithms were evaluated using accuracy, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). SHAP analysis was used to interpret feature contributions.

Results: The data included 424 patients with an average age of 40.3 ± 19.1 years (76.65% male). Abnormal brain CT scan findings were more common in older males, patients with lower Glasgow Coma Scale (GCS) scores, suspected fractures, hematomas, and visible injuries above the clavicle. Among the ML models, XGBoost performed best (AUC 0.9611, accuracy 0.8937), followed by Random Forest, while Naive Bayes showed high recall but poor specificity. SHAP analysis highlighted that lower GCS scores, decreased SpO2 levels, and tachypnea were strong predictors of abnormal brain CT findings.

Conclusion: XGBoost and Random Forest achieved high predictive accuracy, sensitivity, and specificity. GCS, SpO2, and respiratory rate were key predictors. These models may reduce unnecessary CT scans and optimize resource use. Further multicenter validation is needed to confirm their clinical utility.

Introduction: Lead poisoning can present with a spectrum of symptoms, from fatigue to severe multiorgan complication; and Zeolite is known for its ability to remove heavy metals. This study aimed to assess the impact of zeolite on serum lead levels and blood parameters of patients with mild to moderate lead poisoning.

Methods: This double-blind randomized clinical trial evaluated the effects of zeolite on serum lead levels of patients with mild to moderate lead poisoning, conducted between August 2022 and December 2022. The intervention group received oral zeolite tablets in addition to standard treatment, while the control group received only standard treatment. The impact of zeolite administration on serum lead levels and blood parameters was investigated using an appropriate statistical test.

Results: 80 patients with a mean age of 39.84 ± 11.94 (range: 23-75) years were randomized (78.75% male). The two groups were similar regarding age (p = 0.329), sex (p = 0.785), baseline serum lead levels (p = 0.596), and liver enzymes (p = 0.648).The Zeolit group had lower serum lead levels (25.22 ± 13.26 vs. 37.68 ± 15.34; p < 0.001, ES: 0.869) and hematocrit (36.21 ± 7.83 vs. 39.53 ± 5.60; ES: 0.488; p = 0.032) after 2 weeks of treatment.

Conclusion: Zeolite tablets show considerable promise as an adjunct therapy for mild to moderate lead poisoning. They effectively lower serum lead levels without adverse effects. This intervention could reduce the metal burden in the bloodstream and mitigate lead-induced multiorgan damage, offering a more effective and less invasive treatment option.

Introduction: Intoxication-related unconsciousness is a frequent and challenging condition in emergency medicine, where rapid interventions are critical to improve patient outcomes. This study aimed to evaluate the efficacy of methylphenidate in improving consciousness levels of intoxicated patients.

Methods: In this double-blind clinical trial, intoxicated patients over 18 years of age with the Glasgow Coma Score (GCS) 13 and below were studied. 51 people were included in the intervention group and received methylphenidate, while 50 were in the control group and received placebo. Consciousness levels were measured using the Reed score before and at 12, 24, 36, and 48 hours post-intervention and compared between groups using SPSS software version 21.

Results: 101 patients with the mean age of 34± 14.26 (range: 17-81) years were studied (55.4% male). 74.5% of the people in the intervention group achieved the most alert state (a REED score of zero) after 48 hours, compared to only 32% in the control group. The intervention group had significantly lower average Reed scale (0.33) compared to the control group (0.76) 48 hours after the treatment (p = 0.001). Using Methylphenidate in treatment of intoxicated patients showed effect size of 0.703 (95% confidence interval (CI): 0.299-1.104), number needed to treat of 2.17 (95%CI: 1.48 - 3.34), absolute risk reduction of 46% (95%CI: 0.29 -0.67), and relative risk reduction of 57% (95%CI: 0.37 - 0.72).

Conclusion: It seems that, the use of methylphenidate in patients with intoxication can reduce the time it takes for their consciousness to return to a normal level. Since benzodiazepines are the leading cause of poisoning, this study suggests that methylphenidate could be beneficial in cases of benzodiazepine poisoning to aid in cognitive recovery.

Introduction: The National Early Warning Score (NEWS) is commonly used to identify patients at high mortality risk. However, it has notable limitations. In this study, to enhance the accuracy, we revised it and evaluated the performance of modified NEWS (MNEWS) in predicting the outcomes of suspected sepsis patients.

Methods: This single-center, prospective cohort study was conducted on patients with suspected sepsis to evaluate the accuracy of MNEWS in predicting mortality, survival to discharge, vasopressor requirements, and the need for mechanical ventilation. The MNEWS comprises the NEWS variables plus age, chronic major organ dysfunction, malignancy, functional status, and specific infected organ involvement. Sensitivity, specificity, likelihood ratio (LR), and area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the MNEWS in predicting the studied outcomes.

Results: Of the 1,393 patients included in this study, 209 died. Mean MNEWS was significantly higher in non-survivors than survivors (19.8 vs. 14.9, p<0.001). The AUROC of MNEWS in predicting 30-day mortality was 0.82 (95% CI: 0.79–0.85). MNEWS ≥ 18 had the highest accuracy for 30-day mortality prediction with 76.1% sensitivity, 75% specificity, positive LR of 3.13, and AUROC of 0.76 (95% CI: 0.73–0.79). The AUROC of MNEWS ≥18 for predicting survival until discharge, need for vasopressors, and need for mechanical ventilation were 0.75 (95% CI: 0.72–0.78), 0.72 (95% CI: 0.69–0.75), and 0.76 (95% CI: 0.73–0.79), respectively. Additionally, MNEWS ≥18 demonstrated superior predictive performance, compared with NEWS ≥7 and qSOFA ≥2 for various clinical outcomes.

Conclusions: The MNEWS was similar to the NEWS in overall predictive accuracy for 30-day mortality but exhibited a higher predictive accuracy than did the qSOFA score. Notably, MNEWS ≥18 was a significant indicator of 30-day mortality risk, as well as the likelihood of requiring vasopressors, survival to discharge, and 7-day mortality.

Introduction: Coronary artery bypass grafting (CABG) surgery requires an extended length of stay (LOS) in the intensive care unit (ICU). This study aimed to predict the factors affecting LOS in the ICU after CABG surgery using machine learning methods.

Methods: In this study, after extracting factors affecting the LOS of patients in the ICU after CABG surgery from the literature and confirming these factors by experts, the medical records of 605 patients at Farshchian Specialized Heart Hospital were reviewed between April 20 and August 9, 2024. Four machine learning models were trained and tested to predict the most desired factors, and finally, the performance of the models was evaluated based on the relevant criteria.

Results: The most important predictors of the LOS of CABG patients in the ICU were the length of intubation, body mass index (BMI), age, duration of surgery, and the number of postoperative transfusions of packed cells. The Random Forest model also performed best in predicting the effective factors (Mean square Error = 1.64, Mean absolute error = 0.93, and R² = 0.28)

Conclusion: The insights gained from the mashine learning model highlight the significance of demographic and clinical variables in predicting LOS in ICU. By understanding these predictors, healthcare professionals can better identify patients at higher risk for prolonged ICU stays.

Introduction: Emergence agitation (EA) occurs shortly after emergence from anesthesia in pediatric patients causing disorientation, restlessness, and non-purposeful movement. This study aimed to compare intranasal dexmedetomidine (DEX) and oral midazolam in managing EA in pediatric patients scheduled for neurosurgical procedures.

Methods: This double-blinded randomized clinical trial was conducted on 50 pediatric patients who underwent neurosurgical procedure in an educational hospital between March and June 2024. One group received intranasal DEX (2 mcg/kg) and other group received oral midazolam (1 mg/kg of midazolam) before induction of anesthesia. The rate of EA as well as vital signs changes were compared between the two groups using statistical analysis.

Results: 50 participants were enrolled in the study and randomly divided to DEX and midazolam groups (25 participants in each group). The two groups were similar regarding age (p = 0.538); sex (p = 0.417); pre-operation heart rate (p = 0.675); systolic (p = 0.226) and diastolic (p = 0.753) blood pressure; and pre-operative mean arterial blood pressure (p = 0.634). Among all participants, 13 (26.00%) patients showed signs of EA after extubation (2 patients (8.00%) in DEX group and 11 (44.00%) patients in midazolam group; p = 0.004). Regrading vital signs, only the decrease in heart rate after extubation in the DEX group was significantly greater than that observed in the midazolam group (-9.28±12.88 vs. -2.48±8.23, respectively; p = 0.0310). The number needed to treat (NNT), relative risk reduction (RRR), and absolute risk reduction (ARR) of using intranasal DEX in management of EA were 2.77 (95%confidence interval (CI): 1.72-7.19), 81.8% (95%CI: 26.0%-95.5%), and 36.0% (95%CI: 13.9%-58.1%) respectively.

Conclusion: Intranasal DEX compare to oral midazolam demonstrated superior efficacy in managing postoperative EA in pediatric patients.

Introduction: Although emergency medicine is crucial globally, it remains underdeveloped in Iran, facing low recruitment rates. This study aimed to explore barriers deterring Iranian general practitioners (GPs) from pursuing emergency medicine as a specialty.

Methods: A cross-sectional survey was conducted in Kerman, Iran, in 2023. Data were collected from GPs using a structured questionnaire assessing demographic characteristics and barriers to choosing emergency medicine. Statistical analyses, including chi-square and Mann-Whitney U-tests, were performed.

Results: 198 GPs were involved in this study. 95.5% of the participants cited a mismatch between income and workload as the primary deterrent, while high psychological stress (87.4%) and limited private sector opportunities (86.9%) were also significant barriers. Additionally, 82.8% reported high burnout levels, with frequent night shifts (81.8%) and long working hours (75.3%) as contributing factors. Demographic analysis showed younger GPs and those with fewer years since graduation perceived financial and emotional strains more strongly, indicating that early-career physicians may feel more vulnerable to these challenges. Further, GPs lacking emergency department experience rated career uncertainties higher, suggesting unfamiliarity with the field might amplify negative perceptions. Rural GPs emphasized high patient loads and exposure risks, while urban GPs noted stress from crowded settings.

Conclusion: Findings highlight financial and workload issues as major deterrents to choosing emergency medicine as a specialty. Addressing these concerns through better compensation, work-life balance improvements, and enhanced career prospects could attract more GPs to this specialty.

Introduction: Effective information transfer between healthcare providers is essential for patient safety. This study aimed to evaluate the impact of ISBAR (Identify, Situation, Background, Assessment, Recommendation) framework on the quality of clinical handovers in emergency department (ED).

Methods: This prospective, pre- and post-intervention study was conducted at Hazrat Ali Asghar Pediatric Hospital in Tehran, Iran, from May to September 2023. A total of 428 clinical handovers were recorded (214 pre-intervention and 214 post-intervention) following a 90-minute training session and the introduction of a standardized ISBAR checklist. Handover quality was measured using the completeness of a 16-item ISBAR checklist. Data analysis employed descriptive statistics, the Mann–Whitney U test, and Chi-square tests.

Results: Implementation of the ISBAR protocol significantly improved the overall quality of information conveyed during handovers. Total handover scores increased from a mean rank of 127.55 pre-intervention to 301.45 post-intervention (P < 0.001). All five ISBAR domains showed significant enhancements; Identify (from 145.41 to 283.59, P=0.001), Situation (from 129.64 to 299.36, P=0.001), Background (from 136.40 to 292.60, P=0.001), Assessment (from 156.00 to 273.00, P< 0.001), and Recommendations (from 198.14 to 230.86, P=0.03). In addition, the completeness of individual items such as patient diagnosis, admission date, and vital signs improved markedly.

Conclusions: Adopting a standardized ISBAR handover protocol in a high-stakes pediatric environment ED significantly enhances the accuracy and completeness of patient handovers, thereby reducing the potential for errors and strengthening patient safety.

Introduction: Traumatic out-of-hospital cardiac arrest (TOHCA) presents significant public health challenges. The high accident rates and variability in prehospital management in Thailand further complicate TOHCA treatment. This study aimed to analyze prehospital prognostic factors of survival in TOHCA cases.

Methods: This study is a retrospective cohort study utilizing data from the Information Technology of Emergency Medicine System (ITEMS) from January 2012 to December 2022. It included TOHCA patients who received prehospital care and were transported to the emergency department (ED). We used an exploratory approach, incorporating all prognostic variables into a multivariable logistic regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CIs) and p-values.

Results: Over an 11-year period, 35,724 patients with the mean age of 39.69±20.53 (range: 1-99) years were included in the final analysis (78.69% male). Of these, 6,590 (18.45%) survived to hospital admission, while 29,134 (81.55%) died in the ED. Prehospital management factors significantly increasing the likelihood of survival to hospital admission included stopping bleeding (OR=1.38, 95% CI=1.24-1.54, P<0.001), endotracheal intubation (ETT) (OR=2.09, 95% CI=1.74-2.50, P<0.001), intravenous fluid administration (OR=1.66, 95% CI=1.35-2.05, P<0.001), defibrillation (OR = 2.35, 95% CI=1.96-2.81, P<0.001), age (aOR = 0.99, 95% CI = 0.98-0.99, P < 0.001), closed fracture (aOR = 0.59, 95% CI = 0.53-0.66, P < 0.001), open fracture (aOR = 0.54, 95% CI = 0.48-0.61, P < 0.001), dislocation (aOR = 0.60, 95% CI = 0.45-0.81, P = 0.001), and on scene time <10 min (aOR = 0.63, 95% CI = 0.54-0.75, P < 0.001).

Conclusions: To improve survival to hospital admission in TOHCA, several factors should be prioritized. These include administering intravenous fluid boluses, controlling external bleeding, delivering defibrillation when indicated, and performing ETT.

Introduction: Ventilation and oxygen delivery during cardiopulmonary resuscitation (CPR) is of paramount importance. This study aimed to compare the effects of manual and mechanical ventilation on respiratory parameters of intubated patients during CPR. Methods: This randomized controlled clinical trial was conducted in 2024 on 61 intubated patients with neurological disorders admitted to the ICU of educational hospitals. Participants were allocated to either the intervention or the control group using block randomization with a block size of six. The intervention group received mechanical ventilation, while the control group received manual ventilation using bag valve mask (BVM). The effects of manual versus mechanical ventilation during CPR on key physiological and respiratory parameters, including venous blood gases (VBG), end tidal Co2 (ETCO₂), and peripheral oxygen saturation (SpO₂) were compared between groups. Statistical analyses were performed using SPSS version 21.

Results: The study findings indicated no statistically significant differences between the manual and mechanical ventilation groups in terms of venous blood pH levels (P = 0.38), PCO₂ (P = 0.65), and HCO₃ levels (P = 0.47) changes. However, PO₂ (P < 0.001), ETCO₂ (P < 0.05). and SpO₂ (P < 0.001) were more stable and consistently higher in patients receiving mechanical ventilation.

Conclusion: These findings suggest that while pH, PCO₂, and HCO₃ levels did not significantly differ between the two ventilation methods, mechanical ventilation demonstrated superior efficacy in optimizing oxygenation (PO₂ and SpO₂) and regulating ETCO₂ levels.

Introduction: By enabling direct consultation with neurologists, Real-Time Telemedical Oversight (ReTMO) can facilitate rapid stroke assessment and decision-making. This study aimed to assess the efficacy of prehospital stroke management before and after ReTMO implementation.

Methods: A single-center retrospective before-and-after study was conducted at Ramathibodi Hospital, Bangkok, Thailand, from January 2020 to December 2024. In March 2022, a structured prehospital stroke protocol was integrated with the ReTMO system in this hospital. We evaluated its impact by comparing stroke patients transported by emergency medical services (EMS) before and after protocol implementation. Neurological outcomes at hospital discharge were analyzed using multivariable ordinal logistic regression. In contrast, door-to-treatment times in the emergency department (ED) and hospital length of stay were assessed using multivariable Gaussian regression.

Results: The study included 91 prehospital stroke patients, with 36 in the pre-protocol group and 55 in the post-protocol group. Implementation of the structured prehospital stroke protocol was associated with a significant reduction in door-to-computed tomography (CT) scan time by 10.47 (95% confidence interval (CI): -17.62 to -3.3) minutes and door-to-laboratory result time by 15.90 (95% CI: -30.48 to -1.33) minutes. Additionally, adjusted ordinal logistic regression analysis demonstrated a significant improvement in neurological outcomes at hospital discharge (odds ratio (OR) = 0.14, 95% CI: 0.02–0.99, P = 0.049). However, reductions in ED stroke treatment time and hospital length of stay were not statistically significant.

Conclusions: Implementing ReTMO alongside a structured prehospital stroke protocol significantly reduced in-hospital delays in door-to-CT and door-to-laboratory result times while also improving neurological outcomes at hospital discharge.

Introduction: Acute kidney injury (AKI) is one of the most frequent complications in septic shock cases, and has a high mortality rate. The aim of this study was to determine the value of urinary liver-type fatty acid binding protein (L-FABP) in early detection and outcome prediction of AKI in patients with sepsis and septic shock.

Methods: This prospective cohort study was conducted on patients who presented to the emergency department (ED) with sepsis or septic shock. Urinary L-FABP levels were measured at the time of admission and patients were classified into AKI and non-AKI groups within 7 days according to the KIDGO Criteria. The screening performance characteristics of urinary L-FABP in early detection of AKI within seven days of admission and need for renal replacement therapy (RRT) were calculated and reported.

Results: 212 patients with the mean age of 66.5 ± 16.2 (range 18-99) years were included (60.4% male). 54 (25.5%) patients had sepsis, and septic shock was developed in 158 (74.53%) cases. 143 (67.5%) patients were complicated with AKI. The area under the receiver operating characteristic (ROC) curve (AUC) of urinary L-FABP in early detection of sepsis-associated AKI was 0.94 (95% confidence interval (CI): 0.90 - 0.97), compared to the AUC of 0.64 (95% CI: 0.54-0.74) for serum creatinine. The sensitivity and specificity of urinary L_FABP at its best cutoff point (13.90 μg L-FABP/g Cr) were 89.9% and 86.3%, respectively. The area under the ROC curve of urinary L-FABP in predicting the need for RRT in sepsis-associated AKI patients was 0.74 (95% CI: 0.64-0.85), compared to the AUC of 0.53 (95% CI: 0.41-0.64) for serum creatinine. The sensitivity and specificity of urinary L-FABP at its best cutoff point (22.05 μg L-FABP/g Cr) were 63.6% and 71.4%, respectively.

­Conclusions:  It seems that, L-FABP could be considered as a valuable biomarker for early detection and predicting the severity of AKI in septic patients.

Introduction: In 2017, WHO endorsed the Emergency Medical Team (EMT) Minimum Data Set (MDS) for real-time data collection during health emergencies. It was first activated during Cyclone Idai in Mozambique in 2019. The objective of the study is to evaluate the completeness of data collected by EMTs during the Cyclone Idai response in Mozambique.

Methods: This study evaluated data completeness from Cyclone Idai, analyzing 277 daily reports with 18,468 patient consultations from 13 international teams between 27 March and 12 July, 2019. Completeness of team information, demographics, health events, disaster relation, and outcomes were compared across EMT types and classifications using box plots, Kruskal-Wallis, t-tests, and multivariable logistic regression.

Results: During the 110-day response, 13 EMTs submitted 277 daily reports on patient information. Findings showed that, out of the 277 daily reports, demographic information was complete in 92.8% of reports, health event information in 62.1%, information on the relation of health events to disaster in 57.4%, and outcome data in 50.2%. Type 2 EMTs exhibited higher data completeness, likely due to greater resources and personnel, compared to Type 1 Mobile and Type 1 Fixed EMTs. Type 1 Fixed EMTs demonstrated lower completeness for outcomes, health events, and disaster relation, potentially due to heavier workloads. Type 1 Mobile EMTs likely benefited from enhanced training and frequent interactions with data managers, which may have contributed to their higher data completeness compared to Type 1 Fixed EMTs. Classified EMTs performed better overall.

Conclusion: This study underscores the need for standardized training, and the data collection applications that enable the automatic inclusion of information such as geotags.

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble machine learning model designed to predict the onset of AKI in this patient population.

Methods: Leveraging data from 314 ICU patients, the model incorporates SHapley Additive exPlanations (SHAP) for enhanced interpretability, identifying key predictors such as serum creatinine levels, glucose variability, and patient age. The model achieved an Area Under the Curve (AUC) of 0.94, outperforming existing predictive approaches. By utilizing readily available clinical data and determining an optimal temporal prediction window, this model facilitates proactive clinical decision-making, aiming to reduce the risk of AKI and improve patient outcomes.

Results: The stacking ensemble model achieved 92\% accuracy, 93\% precision, 92\% sensitivity, and 0.94 AUC in 314 ICU patients, pinpointing creatinine, glucose variability, and age as critical AKI predictors.

Conclusion: The findings suggest that integrating advanced machine learning techniques with interpretable artificial intelligence (AI) can provide a scalable and cost-effective solution for early AKI detection in diverse healthcare settings.

Introduction: In patients with out-of-hospital cardiac arrest (OHCA) who receive advanced cardiac life support (ACLS) for 20 minutes, the decision of whether to continue or terminate resuscitation at the scene is difficult and complicated. This study aimed to develop and validate a simple and reliable clinical scoring system for identifying cardiopulmonary resuscitation (CPR) failure at the scene after 20 minutes of ACLS.

Methods: In this cross-sectional study we evaluated the adults with nontraumatic OHCA who received ACLS for 20 minutes. The independent predictors of CPR failure were identified using multivariate regression analysis and trying to develop a clinical decision rule. Receiver operating characteristic (ROC) curve was used for evaluating the performance of the developed model.

Results: 455 patients with the mean age of 63.85 ± 19.21 years were included (65.1% male). In most cases of OHCA, the cause of cardiac arrest was respiratory (54.9%). The first cardiac rhythm recorded in 68.1% was asystole. 313 (68.79%) cases were affiliated to the failed CPR group. The independent predictive factors of CPR failure based on multivariate analysis were the first cardiac rhythm recorded (p < 0.001), unwitnessed cardiac arrest (p < 0.001), lack of pupillary response (p < 0.001), advanced airway management at the scene (p < 0.001), and administration of drugs at the scene during CPR, including amiodarone (p = 0.020) and atropine (p = 0.002). The area under the ROC curve of the model was 0.832 (95% confidence interval (CI): 0.793–0.870) with 70.0% sensitivity, 82.4% specificity, 89.8% positive predictive value, 55.5% negative predictive value, 3.97 positive likelihood ratio, and 0.36 negative likelihood ratio.

Conclusion: Using data from routine care practices by EMS personnel, we devised a simple clinical scoring system for predicting CPR failure at the scene of OHCA after 20 minutes of complete ACLS.

Introduction: Head injuries (HI) pose a significant public health concern globally, impacting morbidity, mortality, and economic burden. This study aimed to evaluate the epidemiology and trends associated with head injuries in Iran from 1990 to 2019.

Methods: Our study, based on data from the Global Burden of Diseases (GBD) Study 2019, undertook a comprehensive comparison of the burden of HI in Iran with the Middle East and North Africa (MENA) and global benchmarks. We assessed the incidence, prevalence, and years lived with disability (YLD) through various metrics, including absolute numbers, age-standardized rates (ASR), percentage changes, and estimated annual percentage changes (EAPC) from 1990 to 2019.

Results: The incidence of HI in Iran decreased significantly from 1990 to 2019, with a notable reduction compared to MENA and global trends (EAPC: -1.44, 0.71, and -0.11, respectively). Prevalence showed a declining trend (EAPC: -1.00), with a slight increase in YLDs (EAPC: 0.12). Notable peaks in HI incidence coincided with natural disasters, notably the 1990 Manjil-Rudbar earthquake and the 2003 Bam earthquake.

Conclusion: Our study reveals a decline in the overall burden of HI in Iran over the study period. To sustain this positive trend and minimize the impact of HI on public health and socioeconomic well-being, policy efforts should be directed toward ongoing prevention, early detection, and preparedness for natural disasters.

Introduction: Hypokalemia, hyperkalemia, and acidosis are among the reversible causes of out-of-hospital cardiac arrest (OHCA) that can be promptly identified using point-of-care testing (POCT) for blood gas and electrolyte analysis. This study aimed to evaluate the efficacy of POCT in the prehospital setting for OHCA management.

Methods: In this cross-sectional study the management and outcomes of OHCA patients were compared before and after implementing the POCT for blood gas and electrolyte analysis by EMS in the prehospital setting of Ramathibodi Hospital, Thailand.

Results: 217 OHCA patients with a mean age of 61 ± 17.07 (range: 58.72-63.28) years were studied (64.06 % male). 148 (68.2%) patients received POCT in the prehospital setting. Patients in the POCT group received higher administration of sodium bicarbonate (p < 0.001) and calcium gluconate (p < 0.001) compared to those without POCT. Sustained ROSC was achieved in 25% of the POCT group, compared to 11.59% in the no POCT group (p = 0.030). POCT blood gas analysis was identified as an independent predictor of sustained ROSC based on multivariable analysis (adjusted Odds: 4.60, 95% CI: 1.35-15.69; p = 0.015).

Conclusions: It seems that POCT for blood gas and electrolyte analysis in the prehospital setting could improve sustained ROSC in OHCA patients by enabling rapid and targeted management of cardiac arrest’s reversible causes.

Introduction: Amiodarone has been reported to be associated with QTc interval prolongation and Torsades de pointes (TdP). This study aimed to assess the incidence and identify the risk factors of QTc prolongation and TdP associated with intravenous amiodarone therapy in patients diagnosed with atrial fibrillation (AF).

Methods: A retrospective cohort study was conducted using electronic health records of Buddhachinaraj Hospital, a tertiary care center in Thailand, between January 2016 and September 2019. The study population comprised patients with AF who received intravenous amiodarone therapy. Incidence and associated risk factors for QTc interval prolongation and TdP were assessed using multivariable logistic regression analysis.

Results: A total of 2,944 patients were included in the analysis. Among these, 49 cases of intravenous amiodarone-associated QTc interval prolongation or TdP were identified (33 (1.12%) and 16 (0.54%) cases, respectively), corresponding to an overall incidence of 1.66% (95% confidence interval (CI): 1.23 - 2.19). Multivariable analysis revealed that diabetes mellitus (adjusted odds ratio (aOR): 1.85; 95% CI: 1.02 - 3.38; p-value = 0.045), history of stroke (aOR: 3.09; 95% CI: 1.26 - 7.57; p-value = 0.014), use of antipsychotic medications (aOR: 3.07; 95% CI: 1.64 - 5.74; p-value < 0.001), and use of anticholinergic medications (aOR: 3.89; 95% CI: 1.54 - 9.85; p-value = 0.004) were significantly associated with an increased risk of QTc interval prolongation and TdP following amiodarone therapy for AF patients.

Conclusion: Although the incidence of QTc interval prolongation and TdP related to intravenous amiodarone therapy in patients with AF was relatively low, the risk was significantly elevated in individuals with diabetes mellitus, a history of stroke, or concurrent use of antipsychotic or anticholinergic agents. These findings underscore the importance of vigilant risk assessment and monitoring in clinical practice to mitigate the potential for intravenous amiodarone-induced arrhythmic complications.

Introduction: Opioid-induced respiratory depression is a life-threatening complication of opioid overdose. This study aimed to develop a model for predicting the risk of respiratory depression following opioid overdose using ChatGPT-4o.

Methods: A retrospective cross-sectional study was conducted on 2,005 patients admitted following opioid overdose at Loghman Hakim Hospital, Tehran, Iran, from February 2021 to February 2024. Demographic data, clinical presentations, interventions, and outcomes of patients were extracted from electronic medical records and a predictive model was developed using a no-code methodology with the assistance of ChatGPT-4o.

Results: 2,005 patients with the mean age of 32.97 ± 14.86 (Range: 1-100) years were studied (74.5% male). Respiratory depression was observed in 18% of patients upon admission. Naloxone was administered to 37.6% of patients, with higher usage in those requiring intubation. Key predictors included low oxygen saturation (SpO₂), low respiratory rate (RR), and increased heart rate (HR). The predictive model achieved an accuracy of 94.4% (95% confidence interval (CI): 87.0-96.3), a recall of 81.0% (95% CI: 78.0-84.0) for respiratory depression, and an area under the curve (AUC) of 0.98 (95% CI: 0.95-0.99).

Conclusion: The study highlights critical clinical predictors of respiratory depression risk in opioid overdose patients and demonstrates the potential of machine learning models in enhancing early detection and intervention.

Introduction: Ischemic stroke (IS) is one of the three main fatal disorders and is a major health challenge. 4-methylumbelliferone (4-MU) is one of the coumarin derivatives (7–hydroxy‐4–methylcoumarin) with antioxidant and anti-inflammatory impact. This study was conducted to elucidate the neuroprotective effects and anti-inflammatory impact of 4-MU in a rodent model of IS.

Methods: The IS model was induced by middle cerebral artery occlusion (MCAO) for 1 hour and reperfusion was established for 24 hours. 44 Male Wistar rats were assigned into four groups: (1) Sham, (2) MCAO (3) MCAO + Vehicle, and (4) MCAO + 4-MU (25 mg/kg). Evaluation of neurological deficit was performed using Garcia's score. 2,3,5-triphenoyl-2H-tetrazolium chloride (TTC) staining was employed to measure infarct size.  Nissl staining was applied to determine neuronal loss. Moreover, western blotting was utilized to detect the expression of the proteins relevant to the TLR4/NF-κB/NLRP3 axis (p–NF–κB p65, TLR4, NLRP3, IL-1β, IL-10, IL-18, ASC, and Caspase-1).

Results: It was observed that MCAO caused neurological deficit (P<0.0001), infarct (P<0.0001), and neuronal loss (P<0.002); up-regulated NLRP3 (P<0.0001), TLR4 (P<0.0001), p–NF–κB p65 (P<0.0005), IL-1β (P<0.0014), IL-18 (P<0.0001), ASC (P<0.0027), and Caspase-1 (P<0.0052); and reduced IL-10 concentrations (P<0.0024). Administration of 4-MU (25 mg/kg) quickly after reperfusion reduced neurological deficit (P<0.0001), infarct size (P<0.0001), neuronal loss (P<0.0058), and down-regulated NLRP3 (P<0.0257), TLR4 (P<0.0001), p–NF–κB p65 (P<0.0075), IL-1β (P<0.0106), IL-18 (P<0.0005), ASC (P<0.0072), and Caspase-1 (P<0.0315), and increased IL-10 concentrations (P<0.0215).

Conclusion: These results indicate that 4-MU can attenuate injury after MCAO by suppressing the TLR4/NF-κB/NLRP3 axis. Our findings show that 4-MU can be considered a novel therapeutic compound to cure IS.

Introduction: Prehospital Return of Spontaneous Circulation (P-ROSC), Utstein-Based Return of Spontaneous Circulation (UB-ROSC), and Return of Spontaneous Circulation After Cardiac Arrest (RACA) scores have been developed to estimate the likelihood of Return of Spontaneous Circulation (ROSC) in Out-of-hospital cardiac arrest (OHCA). This study aimed to validate and compare these three scoring systems.

Methods: A retrospective cohort study was conducted using electronic medical records of OHCA patients transported by Ramathibodi Emergency Medical Service (EMS) from January 2021 to October 2024. We included all OHCA patients aged >18 years who transported by Ramathibodi EMS. RACA, UB-ROSC, and P-ROSC scores were calculated, and ROSC was recorded. The area under the ROC curve (AUC) of each score were calculated to assess predictive accuracy.

Results: Among 336 OHCA cases, 94 (27.97%) patients achieved ROSC. The RACA score demonstrated the highest predictive accuracy, with an AUC of 0.77 (95% CI: 0.71–0.82). The UB-ROSC score followed with an AUC of 0.72 (95% CI: 0.66–0.78), while the P-ROSC score had the lowest predictive value with an AUC of 0.64 (95% CI: 0.58–0.70). Calibration analysis indicated that the RACA score aligned most closely with observed outcomes compared to the UB-ROSC and P-ROSC scores. The RACA score exhibited the best overall performance in terms of both discrimination and calibration.

Conclusions: Among the three predictive models assessed, the RACA and UB-ROSC scores demonstrated fair predictive accuracy for ROSC in OHCA patients, while the P-ROSC score had poor predictive value.

Introduction: Identifying the people who try to hide illegal substances in the body for smuggling is of considerable importance in forensic medicine and poisoning. This study aimed to develop a new diagnostic method using artificial intelligence to detect body packs in real-time Abdominal computed tomography (CT) scans.

Methods: In this cross-sectional study, abdominal CT scan images were employed to create a machine learning-based model for detecting body packs. A single-step object detection called RetinaNet using a modified neck (Proposed Model) was performed to achieve the best results. Also, an angled Bbox (oriented bounding box) in the training dataset played an important role in improving the results.

Results: A total of 888 abdominal CT scan images were studied. Our proposed Body Packs Detection (BPD) model achieved a mean average precision (mAP) value of 86.6% when the intersection over union (IoU) was 0.5, and a mAP value of 45.6% at different IoU thresholds (from 0.5 to 0.95 in steps of 0.05). It also obtained a Recall value of 58.5%, which was the best result among the standard object detection methods such as the standard RetinaNet.

Conclusion: This study employed a deep learning network to identify body packs in abdominal CT scans, highlighting the importance of incorporating object shape and variability when leveraging artificial intelligence in healthcare to aid medical practitioners. Nonetheless, the development of a tailored dataset for object detection, like body packs, requires careful curation by subject matter specialists to ensure successful training.

Introduction: Automatic systems based on Artificial intelligence (AI) algorithms have made significant advancements across various domains, most notably in the field of medicine. This study introduces a novel approach for identifying COVID-19-infected regions in lung computed tomography (CT) scan through the development of two innovative models.

Methods: In this study we used the Squeeze and Excitation based UNet TRansformers (SE-UNETR) and the Squeeze and Excitation based High-Quality Resolution Swin Transformer Network (SE-HQRSTNet), to develop two three-dimensional segmentation networks for identifying COVID-19-infected regions in lung CT scan. The SE-UNETR model is structured as a 3D UNet architecture with an encoder component built on Vision Transformers (ViTs). This model processes 3D patches directly as input and learns sequential representations of the volumetric data. The encoder connects to the decoder using skip connections, ultimately producing the final semantic segmentation output. Conversely, the SE-HQRSTNet model incorporates High-Resolution Networks (HRNet), Swin Transformer modules, and Squeeze and Excitation (SE) blocks. This architecture is designed to generate features at multiple resolutions, utilizing Multi-Resolution Feature Fusion (MRFF) blocks to effectively integrate semantic features across various scales. The proposed networks were evaluated using a 5-fold cross-validation methodology, along with data augmentation techniques, applied to the COVID-19-CT-Seg and MosMed datasets.

Results: Our experimental results demonstrate that the Dice value for the infection masks within the COVID-19-CT-Seg dataset improved by 3.81% and 4.84% with the SE-UNETR and SE-HQRSTNet models, respectively, compared to previously reported work. Furthermore, the Dice value for the MosMed dataset increased from 66.8% to 69.35% and 70.89% for the SE-UNETR and SE-HQRSTNet models, respectively.

Conclusion: These improvements indicate that the proposed models exhibit superior efficiency and performance relative to existing methodologies.

Introduction: Acute respiratory failure (ARF) is a critical complication of heat-related illness (HRI). This study aimed to identify predictors of HRI-induced ARF in patients presenting to the emergency department (ED).

Methods: Patients aged 20 years and above diagnosed with HRI (ICD-9-CM code 992 or ICD-10 code T67) who visited the EDs of the three hospitals in Tainan, Taiwan between January 2010 and October 2021, were included. Demographic characteristics, comorbidities, and laboratory data were collected. Logistic regression models using the backward elimination method were constructed to identify the independent predictors of HRI-induced ARF.

Results: 820 patients with the mean age of 50.0 ± 18.4 years were studied (80.0% male). 29 (3.5%) cases experienced ARF. Patients with ARF were less likely to walk on arrival compared to those without it (27.6% vs. 61.8%, p < 0.001). Additionally, they had higher prevalence of Glasgow Coma Scale (GCS) scores ≤ 8 (p = 0.003), respiratory rate > 20 breaths/min (p < 0.001), body temperature ≥ 40°C (p < 0.001), hypertension (p = 0.001), cerebrovascular disease (p = 0.001), and chronic obstructive pulmonary disease (p = 0.042). The multivariable logistic regression revealed that body temperature ≥ 40 °C on arrival (odds ratio (OR): 7.76; 95% confidence interval (CI): 3.14–19.15), an initial respiratory rate > 20 breaths/min (OR: 8.19; 95% CI: 3.48–19.24), and history of hypertension (OR: 3.38; 95% CI: 1.52–7.52) were predictors of HRI-induced ARF.

Conclusions: Elevated body temperature, respiratory rate, and a history of hypertension were key predictors of ARF in HRI patients, aiding in patient stratification for emergency care.

Introduction: Sepsis-associated acute kidney injury (SA-AKI) is a frequent complication in critically ill patients and is associated with increased mortality. This study aimed to evaluate the prognostic value of the lactate/albumin ratio (LAR) and other albumin-based biomarkers in predicting SA-AKI.

Methods: A retrospective observational study was conducted on 564 patients with sepsis, divided into two groups based on the presence (n = 298) or absence (n = 266) of AKI. Clinical characteristics, laboratory parameters, and disease severity scores (SOFA, APACHE II, NEWS, NEWS-Lactate) were compared between groups. The predictive performance of each marker in detecting SA-AKI was assessed using receiver operating characteristic (ROC) curve analysis.

Results: Patients with SA-AKI had significantly higher levels of lactate (p = 0.001), procalcitonin (PCT) (p = 0.001), urea (p = 0.019), creatinine (p = 0.004), and lower albumin (p = 0.001) concentrations upon admission. The LAR demonstrated the highest discriminative performance among all tested markers, with an area under the curve (AUC) of 0.800 (95% confidence interval (CI): 0.765–0.835), sensitivity of 70.5% (95% CI: 64.9 – 75.6), and specificity of 70.3% (95% CI: 64.4 – 75.7) at a cut-off value of 0.101. NEWS-Lactate also showed good prognostic ability (AUC = 0.772, 95% CI: 0.734–0.809), sensitivity of 71.1% (95% CI: 65.6 – 76.2), and specificity of 63.2% (95% CI: 57.1 – 69.0) at a cut-off value of 7.11. Other indices, including serum creatinine/albumin ratio (sCAR), blood urea nitrogen/albumin ratio (BAR), and procalcitonin/albumin ratio (PAR), and procalcitonin (PCT) × lactate, yielded moderate AUCs. While NEWS alone showed limited predictive value (AUC = 0.508), both SOFA and APACHE II scores were significantly higher in the SA-AKI group.

Conclusion: It seems that, the LAR and NEWS-Lactate are promising biomarkers for early detection of SA-AKI and may outperform conventional severity scores and standalone laboratory parameters.

Introduction: Torsade de pointes (TdP) is a deadly complication from drug-induced QT prolongation. Each of the 12 lead of an electrocardiogram (ECG) has a different length of QT interval, and thus might have a different performance in TdP prediction. This study aimed to determine the best ECG lead or set of leads in this regard.  

Methods: This is a comparative prognostic accuracy study using a two-gate data gathering design. The population in this study was from two sources, a case group (Patients who had drug-induced TdP, which were identified through a systematic Medline search) and a control group (those who overdosed on QT-prolonging drugs, which included patients who were under the consultation of Medical Toxicology Services). The areas under the receiver operating characteristic curve (AUROC) of heart rate-corrected QT (QTc) in each single ECG lead and of a mean/median QTc from a set of ECG leads (17 index test) in predicting the risk of TdP were calculated and compared with each other, trying to find the best lead for this propose. QTc Interval measurements were done by four investigators (Interrater reliabilities 0.95).

Results: Finally, we included 136 and 148 ECGs from TdP cases and controls, respectively. V3 lead had the highest frequency of longest QTc interval, among the leads. The lead having the longest QTc yielded the greatest AUROC in predicting TdP regardless of QT correction formulas (QTcFRA=0.9915, QTcRTH=0.9893, QTcBZT=0.9904). The mean QTc of 3 leads (lead II, plus any two of leads V2-V4), and a median QTc of 6 leads (I, II, aVF, V2, V4, V6) provided  similar overall performance for TdP prediction (regardless of the type of QTc formula).

Conclusion: The longest QTc provided the greatest AUROC in predicting drug-induced TdP, however, the longest QTc is not located in a fixed individual lead in any patient. A less time-consuming method with comparable performance to that of the longest QTc was to use a mean QTc from 3 leads (lead II, plus any two of leads V2-V4). The potential clinical impact of this finding needs to be verified in a prospective cohort study.

Introduction: ChatGPT, a general-purpose language model, is not specifically optimized for medical applications. This study aimed to assess the performance of ChatGPT-4 and o1-preview in generating differential diagnoses for common cases of ankle pain in emergency settings.

Methods: Common presentations of ankle pain were identified through consultations with an experienced orthopedic surgeon and a review of relevant hospital and social media sources. To replicate typical patient inquiries, questions were crafted in simple, non-technical language, requesting three possible differential diagnoses for each scenario. The second phase involved designing case vignettes reflecting scenarios typical for triage nurses or physicians. Responses from ChatGPT were evaluated against a benchmark established by two experienced orthopedic surgeons, with a scoring system assessing the accuracy, clarity, and relevance of the differential diagnoses based on their order.

Results: In 21 ankle pain presentations, ChatGPT-o1 preview outperformed ChatGPT-4 in both accuracy and clarity, with only the clarity score reaching statistical significance (p < 0.001). ChatGPT-o1 preview also had a significantly higher total score (p = 0.004). In 15 case vignettes, ChatGPT-o1 preview scored better on diagnostic and management clarity, though differences in diagnostic accuracy were not statistically significant. Among 51 questions, ChatGPT-4 and ChatGPT-o1 preview produced incorrect responses for 5 (9.8%) and 4 (7.8%) questions, respectively. Inter-rater reliability analysis demonstrated excellent reliability of the scoring system with interclass coefficients of 0.99 (95% CI, 0.998–0.999) for accuracy scores and 0.99 (95% CI, 0.990–0.995) for clarity scores.

Conclusion: Our findings demonstrated that both ChatGPT-4 and ChatGPT-o1 preview provide acceptable performance in the triage of ankle pain cases in emergency settings. ChatGPT-o1 preview outperformed ChatGPT-4, offering clearer and more precise responses. While both models show potential as supportive tools, their role should remain supervised and strictly supplementary to clinical expertise.

Introduction: Dizziness is a frequent emergency department (ED) complaint, often benign but sometimes due to serious underlying etiologies, including cerebrovascular diseases. This study aimed to estimate stroke prevalence among ED dizzy patients and determine its predictors.

Methods: This retrospective cohort study was performed at King Fahad Hospital of the University, reviewing all adult ED visits with documented dizziness from January–December 2023. Patients with incomplete records were excluded. Demographics, comorbidities, vital signs, and clinical features were studied and independent predictors of stroke among dizzy patients were identified using Logistic regression analysis.

Results: A total of 1,660 records were reviewed and 950 adult patients with the mean age of 42.0 ± 16.2 (range 18-93) years were included. The prevalence of stroke was 0.74% (95% confidence interval (CI): 0.35 to 1.54). The prevalence was higher among males (1.60%) and patients aged 50-60 years (2.09%). Male sex (odds ratio (OR): 9.33, 95% CI: 1.12 to 77.8; p = 0.039), older age (OR: 1.05, 95% CI: 1.01 to 1.10; p = 0.017), smoking (OR: 21.8, 95% CI: 3.95 to 120; p < 0.001), diabetes (OR: 24.6, 95% CI: 2.94 to 205; p = 0.003), hypertension (OR: 5.25, 95% CI:  1.17 to 23.7; p = 0.031), hyperlipidaemia (OR:19.9, 95% CI:  4.37 to 91.3; p < 0.0001), tinnitus (OR:10.3, 95% CI: 1.17 to 90.9; p = 0.036), antiplatelet medications (OR: 8.80, 95% CI: 1.66 to 46.7; p = 0.011), and higher systolic blood pressure (OR: 1.04, 95% CI: 1.02 to 1.08; 0.001) were associated with an increased risk of stroke. In addition, presence of any focal neurologic deficit was significantly associated with the higher probability of stroke in dizzy patients. In the final logistic regression model, smoking (adjusted OR (aOR): 22.7, 95% CI: 2.96 to 174; p = 0.003), hyperlipidemia (aOR: 20.2, 95% CI: 3.45 to 117; p = 0.001), and systolic blood pressure (aOR: 1.06, 95% CI: 1.02 to 1.10; p = 0.001) remained significant independent predictors of stroke risk in dizzy patients who referred to the ED.

Conclusion: Based on the finding of this series, the prevalence of stroke among dizzy patients was 0.74%. Older age, male sex, smoking, diabetes mellitus, hyperlipidaemia, tinnitus, antiplatelet medications, presence of focal neurologic deficit, and higher systolic blood pressure were among the associated factors of stroke in dizzy patients based on univariate analysis. Based on the final models, smoking, hyperlipidemia and increase systolic blood pressure were among the independent predictors of stroke in dizzy cases.

Introduction: Fournier’s gangrene (FG) is a type of necrotizing fasciitis affecting the external genitalia or perineum. The Geriatric Nutritional Risk Index (GNRI) has been reported as a prognostic factor to evaluate the outcomes of various diseases. This study aimed to investigate the utility of GNRI in predicting the mortality of FG patients.

Methods: This retrospective cross-sectional study evaluated the patients admitted to a referral hospital, during 14 years, with diagnosis of FG. The role of GNRI in predicting the mortality of these patients was studied. To further investigate the relationship of the GNRI score with patients’ prognosis, we controlled for the scores of Fournier's Gangrene Severity Index (FGSI) and Charlson Comorbidity Index (CCI).

Result: 78 patients with the mean age of 60.79 ± 13.76 (range: 24 -85) years were included in the study (89.74% male). The mortality rate in this series was 23 (29.5%) cases. The survived cases had significantly higher GNRI score (p < 0.001), higher Albumin level (p < 0.001), higher weight (p = 0.04), and lower mortality risk based on FGSI score (p < 0.001). In patients with low mortality risk according to FGSI score (p = 0.036) and mild comorbidities based on CCI score (p = 0.030), the association between GNRI and final prognosis was significant. In contrast, in patients with high mortality risk according to FGSI score (p =0.074) and moderate (p = 0.118) and severe (p = 0.215) comorbidities by CCI score this association was not significant.

The independent predictors of mortality in FG patients were GNRI score (OR: 1.242, 95%CI: 1.08, 1.41; p =0.001) and FGSI score (OR: 54.614, 95%CI: 6.89, 432.31; p < 0.001). The area under the receiver operating characteristic (ROC) curve of GNRI score in predicting the mortality of FG patients was 0.84 (95%CI: 0.75 - 0.93). The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of GNRI score at the optimal cut-off point (78.5) were, 80%, 77.9%, 60.6%, 90.4%, 3.69, and 0.255 respectively.

Conclusions: Our findings indicate that among patients with mild FG, as assessed by FGSI score, and those with low comorbidities based on CCI score, the GNRI score in survivors was significantly higher than that in non-survived. Additionally, multivariate regression analysis demonstrated that the GNRI score serves as an independent predictor of patient outcomes.

Introduction: Emergency medical service (EMS) response time is a critical factor in managements of out-of-hospital cardiac arrest (OHCA) cases. This study aimed to investigate the effects of EMS response time on survival of OHCA patients.

Methods: This study employed a retrospective cohort design focused on prognosis research. Data was collected from the Erawan EMS Dispatch Center of the Bangkok Metropolitan Administration from January 2019 to December 2023. All OHCA cases visited by dispatched prehospital teams in Bangkok were included. Multivariable logistic regression was used to analyze the effect of response time on survival at scene, survival to emergency department (ED), and survival to hospital discharge of OHCA cases.

Results: Among the 5,433 OHCA patients included in the study, 29.17% achieved return of spontaneous circulation at the scene, 6.9% survived to ED, and 1% survived to hospital discharge. Each 1-minute increase in response time decreased the likelihood of survival at the scene by 6% (OR: 0.94, p < 0.001), survival to ED admission by 4% (OR: 0.96, p < 0.001), and survival to hospital discharge by 6% (OR: 0.94, p = 0.006). Response times under 8 minutes significantly improved outcomes, with survival at the scene increasing by 2.31 times (p < 0.001), survival to ED by 1.76 times (p < 0.001), and survival to hospital discharge by 2.09 times (p = 0.048).

Conclusions: A maximum response time of 8 minutes significantly enhances survival outcomes, including survival at the scene, survival to ED, and survival to hospital discharge. Furthermore, each 1-minute increase in response time is associated with a 6% reduction in the likelihood of survival to hospital discharge.

Introduction: Intubating patients undergoing manual in-line stabilization (MILS) can make airway management more challenging. This study aimed to compare the outcomes of intubation with video-laryngoscope (VL) and Intubating Laryngeal Mask Airway (I-LMA) in manikin with restricted neck motion using MILS.

Methods: In this comparative study, emergency medicine residents and paramedics were randomly allocated to two crossover sets. Then the intubation outcomes (success rate, time to successful intubation, and cervical spine movement) were compared between intubation with VL and I-LMA in a manikin model with restricted cervical spine mobility, achieved through MILS.

Results: 64 participants with a mean age of 28.86 ± 4.03 (range: 24-47) years and a mean duration of intubation experience of 3.63 ± 1.35 years were studied (43.75% male, 81.3% emergency medicine resident). The intubation success rate was 62 out of 64 (96.88%) in the VL method and 52 out of 64 (81.25%) in the I-LMA method (p = 0.008). The mean time to successful intubation was 33.03±16.94 seconds in the VL method and 55.03±17.34 seconds in the I-LMA method (p < 0.001). The mean cervical range of motion (CROM) in flexion-extension was 4.38±1.82 degrees in the VL method and 4.13±3.20 degrees in the I-LMA method (p = 0.158). The mean CROM in rotation was 4.27±2.62 degrees in the VL method and 4.65±2.47 degrees in the I-LMA method (p= 0.258) and the mean CROM in lateral bending was 5.35±4.45 degrees in the VL method and 7.71±6.14 degrees in the I-LMA method (p = 0.010).

Conclusion: In a manikin model with restricted cervical spine mobility, the utilization of VL significantly improved intubation success rates, reduced time to successful intubation, and limited CROM.

Introduction: The awareness of the Emergency Department (ED) workforce about the department's operational guidelines and metrics is essential to optimize the workflow and reduce workload and patient revisits to the ED. Therefore, this study aimed to evaluate the knowledge of the ED workforce regarding operational metrics.

Methods: We conducted a national cross-sectional study using an online survey in the Kingdom of Saudi Arabia between September and December 2020. ED personnel were studied regarding the ED operational metrics like laboratory/imaging turnaround times, ED length of stay, and patient revisits, linking them to quality care. Data was summarized and analyzed using the Jamovi statistical package.

Results: One hundred sixty-six participants responded to our online survey. Ministry of Health hospitals represented the largest section (n=90, 54.2%), followed by academic hospitals (n=40, 24.1%). The frequencies of an exit block in the ED were reported as 2-3 days per week (29.5%), most days (24.7%), or daily (18.1%). 41% of the respondents did not know the metrics of lab and imaging turnaround time, while 21.7% did not know about the length of stay. Most respondents agreed that the principles of ED operation should be implemented in the training programs (88.6%) and reported their satisfaction with the productivity of their department in practicing effective operations (70.9%).

Conclusion: About one-third of the ED workers were unaware of the key operational metrics of the ED. However, the respondents believe that implementing operational metrics for ED increases the quality of medical care and should be part of the training programs.

Introduction: While urine culture is the gold standard for the urinary tract infection (UTI) diagnosis, delays in results highlight the need for rapid tests. This study aimed to evaluate the accuracy of urine Gram staining, leukocyte esterase, and nitrite in predicting the presence of UTI.

Methods: A cross-sectional diagnostic accuracy study was conducted on adult patients undergoing urine culture at a high-complexity hospital in northeastern Colombia. The results of Gram staining and urinalysis (nitrite and leukocyte esterase) were compared to urine culture as the gold standard test, and screening performance characteristics were calculated and reported for individual and combined tests.

Results: A total of 2,123 urine cultures were analyzed, with 49.8% testing positive. Escherichia coli was the most common pathogen (24.7%), and 76.17% of patients received antibiotics, primarily ceftriaxone (38.7%). Gram staining showed 56.9% (95% confidence interval (CI)=54.4 to 59.4) sensitivity and 76.8% (95% CI=72.6 to 80.5) specificity, leukocyte esterase had 67.9% (95% CI= 65.3 to 70.4) sensitivity and 84.5% (95% CI=81.4 to 87.2) specificity, and nitrite demonstrated the highest sensitivity (85.3%, 95% CI=82.0 to 88.2). The combination of Gram staining (+), leukocyte esterase (+), and nitrite (+) achieved 87.6% (95% CI=84.2 to 90.5) sensitivity and 94.6% (95% CI=93.1 to 95.9) negative predictive value (NPV), with the decision tree identifying this combination as having the highest diagnostic utility (positive likelihood ratio (PLR) = 23.77, 95% CI=18.34 to 30.80).

Conclusions: It seems that, integrating urine Gram staining with leucocyte esterase and nitrite improves UTI diagnosis in high-complexity emergency settings, reducing unnecessary urine cultures and antibiotic use while enhancing resource utilization and mitigating bacterial resistance.

Introduction: Quantitative and qualitative evaluations of the publication trends and architecture can be useful for guiding future research agendas of both researchers and journals.  This study aimed to investigate the bibliometric characteristics of emergency medicine (EM) researches across different journal quartiles.

Methods: A systematic search was conducted in the Scopus database to retrieve published documents from journals in Q1 to Q4 categories (based on Scimago Journal Ranking) from inception to April 2024. The bibliometric analyses were carried out using the Visualization of Similarities viewer (VOSviewer) software.

Results: Based on author keywords analysis, we identified 7 (96 nodes), 7 (110 nodes), 6 (89 nodes), and 7 (110 nodes) clusters for Q1 to Q4 categories, respectively. The most frequent author keywords in Q1 to Q4 categories were resuscitation, trauma, COVID-19, and pediatric, respectively. Among the top 10 author keywords in Q1 to Q4 categories, cardiac arrest, disaster, burn, and trauma with average of 19.58, 9.56, 4.92, and 1.61 citations were the most cited topics.

Conclusion: This bibliometric analysis highlights that main focus of research in EM researches varies across different journal quartiles. The most commonly studied topics in EM journal categories are resuscitation, trauma, COVID-19, and pediatric.

Introduction: Termination of resuscitation (TOR) rules in out of hospital cardiac arrest (OHCA) varies across different healthcare settings and populations. This study aimed to externally validate ten TOR rules for predicting death before hospital admission among OHCA patients.

Methods: A retrospective prognostic accuracy study analyzed 379 non-trauma OHCA patients (≥18 years) in Bangkok who were either treated by the emergency medical services (EMS) of Ramathibodi Hospital or transported to Ramathibodi's emergency department by another EMS provider (January 2010 - March 2023).  The predictive performance of ten TOR rules (AHA-BLS, AHA-ALS, Korean Cardiac Arrest Research Consortium (KoCARC) rules I, II, and III, Goto's rule, Shihabashi's rule, the New Model I, Helsinki’s, and Petrie’s rule) in predicting death before hospital admission as well as false positive rates (FPRs) of rules at various resuscitation times were calculated and reported with 95% confidence interval (CI).

Results: Among 379 OHCA patients, 308 (81.27%) died before hospital admission and 71 (18.73%) survived to discharge. The New model I demonstrated the most conservative predictive performance with sensitivity of 96.7% (95% CI: 93.0-98.8), NPV of 91.5% (95% CI: 82.5-96.8), and area under the curve (AUC) of 0.74 (95% CI: 0.70-0.79). The KoCARC III showed FPR of 2.8%. Based on the initial presenting criteria, the FPR varied at different resuscitation time points, with increasing FPR over 30 minutes. Among all rules, Helsinki's and AHA-BLS showed the highest FPRs (1.14 – 21.13 and 1.14 – 23.94, respectively) while the KoCARC TOR rules III demonstrated the most conservative consistency in maintaining a low FPR (0-2.82%) throughout time.

Conclusion: The KoCARC III demonstrated relatively high safety for TOR decisions in Bangkok's OHCA population, with the lowest FPR, and high sensitivity and NPV. TOR rules showed higher FPRs compared to previous studies. These findings should be interpreted with caution due to the retrospective design, potential selection bias, and EMS protocol changes over the 10-year study period.

Introduction: Hepatic ischemia results in the dysrhythmia of the intrahepatic hemodynamics. This study aimed to evaluate the changes occurring in the protein metabolism and serum lactate dehydrogenase (LDH) level after hepatic ischemia and assess the effects of antioxidant therapy in this regard.

Methods: In this experimental study (with manipulation of ischemia time and antioxidant therapy) 120 male rats were divided into groups of acute hepatic ischemia; acute hepatic ischemia +antioxidant; chronic ischemia using tetra chloromethane; and sham or intact control to evaluate the changes occurring in the protein metabolism (total protein, albumin, and globulin fractions) and LDH level 3, 7, 15, and 30 days after 10- or 30-minute hepatic ischemia induction and effects of antioxidant therapy in this regard.

Results: In the 10-minute ischemia group, total protein decreased to 34.69 ± 2.49 g/L at 3 days, while albumin fell to 12.36 ± 0.85 g/L. The inflammatory response was evident through elevated α1-globulin (9.02 ± 1.50 g/L) and LDH (3476.37 ± 324.89 U/L) at day 3, which gradually normalized by day 30. In the 30-minute ischemia group, the effects were more pronounced, with total protein reaching 54.57 ± 1.93 g/L and albumin 34.33 ± 2.20 g/L at day 3, alongside marked increases in α1-globulin (10.35 ± 1.30 g/L), α2-globulin (3.19 ± 0.43 g/L), β-globulin (8.09 ± 2.27 g/L), γ-globulin (5.64 ± 1.08 g/L), and LDH (2301.44 ± 80.07 U/L).  After 10- and 30-minute ischemia, α1, α2, β, and γ globulins as well as LDH level were significantly increased at the post-ischemic recovery. The group that received antioxidant showed significantly lower increases in the globulin fractions and LDH level at 3, 7, 15, and 30 days after the procedure.

Conclusion: Based on the findings, 10- and 30-minute acute hepatic ischemia had a profound negative effect on protein metabolism, which was reflected in decreased total protein and albumin, and increased globulin fractions and LDH, indicating the presence of continuous hepatocellular injury and a significant inflammatory reaction. Riditox antioxidant therapy had a consistent, albeit incomplete, hepatoprotective effect, which attenuated these biochemical imbalances.

Introduction: Reducing the compression rotation interval from 2 to 1 minute is expected to improve cardiopulmonary resuscitation (CPR) quality. This meta-analysis aimed to assess the effect of altering the compression rotation interval on key CPR quality parameters, including compression depth, rate, and rescuer fatigue.

Methods: We systematically searched MEDLINE, EMBASE, Scopus, Google Scholar, Web of Science, and the Cochrane Controlled Register of Trials from their inception to May 15, 2025. We searched for randomized controlled trials, simulation studies, and crossover studies that compared 1-min and 2-min compression rotation times. The assessed outcomes included compression depth, rate, correctness, and rescuer fatigue, which were reported as the standard mean difference (SMD) with a 95% confidence interval (95% CI).

Results: One randomized controlled trial and seven randomized crossover studies, involving 668 rescuers in total, using manikins, were included. The 1-min rotation group exhibited significantly greater compression depth, with an increase of 2.06 mm (SMD = 2.06, 95% CI: 0.44–3.68, p < 0.001). This group demonstrated lower levels of fatigue, as indicated by a significant reduction on the visual analog scale for fatigue (SMD = −1.27, 95% CI: −2.24 to −0.30, p < 0.001). However, there were no significant differences in the compression rate or percentage of compressions that achieved adequate depth.

Conclusion: It seems that altering the chest compression rotation interval from 2 min to 1 min improves the compression depth and reduces rescuer fatigue. However, parameters, such as the compression rate and compression adequacy, remained unchanged. Notably, all the studies were conducted on manikins, thus necessitating further research to assess the applicability of these changes in real-world clinical settings.

Introduction: Missed or delayed diagnosis of pulmonary embolism (PE) is associated with increased morbidity, mortality, and longer hospitalizations. This study aimed to evaluate the diagnostic accuracy of Artificial Intelligence (AI) models in detecting PE across imaging.

Methods: We systematically searched PubMed/MEDLINE, Scopus, Embase and Web of Science from inception to 1 January 2025 without language or regional limits. After removing duplicate results, the remaining records were screened through titles/abstracts, and two reviewers independently assessed full texts. Risk of bias was evaluated in duplicate with the QUADAS-2 tool. Pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio and area under the ROC curve were calculated with random-effects models in STATA 17. Heterogeneity was quantified with Cochran’s Q and I², while we explored its sources using subgroup analyses (for categorical moderators) and meta-regression (for continuous moderators). Publication bias was assessed with Deeks’ funnel plot and trim-and-fill, and we examined robustness through leave-one-out sensitivity analyses.

Results: A total of 1,432 records were identified through database searches, with 654 duplicates removed. After screening titles and abstracts of 787 articles, 256 full-text articles were assessed for eligibility, and 28 studies met the inclusion criteria. Internal validation phases included 43,330 participants (4,866 PE-positive, 38,463 PE-negative), while external validation phases comprised 3,588 participants (1,699 PE-positive, 1,889 PE-negative). In the internal validation phase, the pooled sensitivity and specificity of AI in PE diagnosis across imaging were 0.91 (95% confidence interval (CI): 0.88–0.95; I²=9%) and 0.94 (95% CI: 0.86–0.98; I²=99.78%), respectively. The positive likelihood ratio (PLR) was 16.08, and the negative likelihood ratio (NLR) was 0.09, both statistically significant (P < 0.001). The pooled diagnostic odds ratio (DOR) was 163.55 (95% CI: 71.30-375.14, I²: 96.1), and the area under the curve (AUC) was 0.95 (95% CI: 0.93 to 0.97), indicating excellent accuracy. In external validation, the pooled sensitivity and specificity were slightly lower at 0.89 (95% CI: 0.79–0.95; I²=95.60%) and 0.88 (95% CI: 0.80–0.93; I²=91.48%), respectively. The DOR was 59.65 (95% CI: 23.53 to 151.17, I²: 89.6) and AUC was 0.94 (95% CI: 0.92 to 0.96, I²: 89.6). There was no significant publication bias detected.

Conclusion: AI models achieved high diagnostic accuracy in detecting PE through imaging. However, this performance tends to decrease from internal to external validation, highlighting limitations in generalizability. Additionally, substantial heterogeneity was observed across studies, as indicated by high I² values, which should be considered when interpreting the pooled estimates.

Decisions on life-sustaining treatment depend on evaluating fundamental ethical principles regarding taking human life. This study aimed to compare the Islamic standpoint with secular views on ethical decision-making in end-of-life care. We conducted a scoping review to analyze and compare articles published in 2000-2022, regarding ethical criteria for withdrawing life-prolonging treatments in dying patients, and the final decision-maker in such cases. The main difference between the two viewpoints, however, lies in the perspective that in Islam to save human life is of utmost importance, and therefore the criteria for treatment benefits, indications, and goals should all be evaluated in the light of this profound Islamic concept. The most significant similarity discovered between the two standpoints was that a terminal patient’s wish not to prolong the process of dying should be respected, and the physician’s opinion in determining the benefit or futility of treatment is of utmost importance. Comparison of Islamic and Secular perspectives about ethical decision-making in end-of-life care regarding life sustaining treatment indicates that benefits of treatments for patients, and healthcare goals are among the major factors in decision-making according to both viewpoints, and patients, their families, physicians, and the medical team are all involved in making the final decision.

Introduction: Traumatic dental injuries (TDI) are a global public health concern, impacting individuals of various age groups. This systematic review aimed to consolidate current evidence on TDI prevalence, providing insights for improved management and prevention strategies.

Methods: A comprehensive search was conducted across PubMed/MEDLINE, Embase, and Scopus databases for studies published between January 1, 2000, and July 1, 2024. Studies reporting on the prevalence of TDI in various populations were included. We followed PRISMA guidelines in the review process. Descriptive statistics were used to summarize study characteristics, and a random-effects model was applied in the meta-analysis using STATA version 14 to pool prevalence rates, while accounting for inter-study variability. Begg’s and Egger’s tests were conducted to assess publication bias.

Results: The review included data of 151,205 patients from 30 studies across diverse healthcare settings. The prevalence rates varied significantly across studies, ranging from as low as 1.88% to as high as 86.98%. The overall pooled prevalence of TDI, calculated using a random effects model, was 19.48% (95% CI: 11.21% to 27.74%), indicating substantial heterogeneity among the studies (I-squared = 100.0%, p < 0.001). The prevalence varied significantly across different healthcare settings and demographic groups. No evidence of publication bias was found (p > 0.05).

Conclusions: This systematic review underscores the high prevalence of TDI and highlights the need for targeted preventive strategies and evidence-based interventions in dental trauma care.

Artificial intelligence (AI) systems have witnessed notable advancements, revolutionizing various fields of research and medicine. Specifically, advancements of AI and the rapid growth of machine learning hold immense potential to significantly impact emergency medicine. This narrative review aimed to summarize AI applications in prehospital emergency care, emergency radiology, triage and patient classification, emergency diagnosis and interventions, pediatric emergency care, trauma care, outcome prediction, as well as the legal and ethical challenges and limitations of AI use in emergency medicine.

A comprehensive literature search was conducted in Web of Science, Scopus, and Medline using a wide range of artificial intelligence and machine learning-related keywords combined with terms related to emergency medicine to identify relevant published studies. The findings show that AI-powered tools can assist clinicians in emergency departments in improving the management of prehospital emergency care, emergency radiology, triage, emergency department workflow, complex diagnoses, treatment, clinical decision-making, pediatric emergency care, trauma care, and the prediction of admissions, discharges, complications, and outcomes. However, the majority of these applications have been reported in retrospective studies, whereas randomized controlled trials (RCTs) are essential to determine the true value of AI in emergency settings. These applications can serve as effective tools in emergency departments when they are continuously supplied with high-quality real-time data and are adopted through collaboration between skilled data scientists and clinicians. Implementing these AI-assisted tools in emergency departments requires adequate infrastructure and machine learning operation systems.

Since emergency medicine involves various clinical decision-making scenarios based on classifications, flowcharts, and well-structured approaches, future well-designed prospective studies are necessary to achieve the goal of replacing conventional methods with new AI and machine learning techniques.

Introduction: Despite the evident impact of ultrasonography on diagnosis in acute care settings, there is still a great deal of uncertainty regarding its accuracy. This study aimed to assess the diagnostic performance of lung ultrasonography (LUS) for the identification of acute heart failure in patients with suggestive manifestations.

Methods: Medline, Scopus, and Web of Science were comprehensively searched from their inception to November 2024 to identify original studies investigating accuracy of LUS for diagnosis of heart failure. Data extraction and quality assessment were performed by two independent reviewers. The statistical analysis for pooling the results of diagnostic performance parameters was conducted using Stata and Meta-DiSc softwares.

Results: Thirty-eight included studies in this meta-analysis were published between 2006 and 2024, encompassing a total of 6,783 patients. There was significant heterogeneity between included studies with respect to sensitivity (I²=92.51 and P<0.01) and specificity (I²=93.79 and P<0.01). The pooled sensitivity, specificity, and accuracy of LUS for detection of heart failure were 0.92 (95% CI, 0.87-0.95), 0.90 (95% CI, 0.86-0.93), and 0.96 (95% CI, 0.94-0.98), respectively. In addition, pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 7.87 (95% CI, 5.60-11.07), 0.14 (95% CI, 0.10-0.19), and 70.74 (95% CI, 41.98-119.21), respectively.

Conclusion: Our meta-analysis demonstrates that LUS is a highly practical imaging for diagnosing acute heart failure, with excellent sensitivity, specificity, and accuracy. It is particularly valuable for excluding the heart failure when the result is negative. However, the influence of outlier and influential studies warrants caution, and future studies should aim to further validate these findings in diverse clinical contexts.

Introduction: In January 2020, WHO declared the 2019 Coronavirus Disease (COVID-19) a pandemic. Though COVID-19 vaccines are recommended, ongoing surveillance is crucial due to potential unforeseen events. Evaluation of long-term effectiveness and safety and addressing emerging variants are vital. This study integrates systematic reviews to assess COVID-19 vaccine efficacy, immunogenicity, and safety comprehensively.

Methods: This study was an umbrella review study on the feasibility and effectiveness of vaccines for COVID-19. We conducted a comprehensive search in PubMed, Web of Sciences, and Scopus, using MeSH terms and keywords related to COVID-19 vaccines. Inclusion criteria comprised peer-reviewed systematic reviews and meta-analyses in English, focusing on feasibility and effectiveness. Exclusion criteria targeted non-systematic reviews exclusively on vaccine safety and duplicates. Two independent reviewers screened and resolved discrepancies. Data extraction included key details.  Methodological quality was assessed using the ROBIS tool. Data synthesis involves narrative and, if applicable, quantitative synthesis (meta-analysis). Reporting followed PRISMA guidelines.

Results: A total of 32 systematic reviews were included in the study, of which 20 also conducted a meta-analysis. The studies investigated in the included reviews ranged from 7 to 74. The included articles were conducted in various countries around the globe. The findings indicated that COVID-19 vaccines are generally safe and effective for individuals with various medical conditions. The overall risk of bias for the included studies was assessed as low risk.

Conclusion: The study outcomes indicated that mRNA vaccines exhibit a higher incidence of adverse events but demonstrate greater efficacy.  Conversely, inactivated and protein subunit vaccines are safer but exhibit lower efficiency.  Moreover, the vaccine is considered safe for individuals with specific conditions such as inflammatory bowel disease, solid organ transplant recipients, children, pregnant individuals, and those with hematologic problems. Ultimately, the acceptance of the COVID-19 vaccine among individuals is influenced by various factors, including geographic, socioeconomic, and pandemic-related considerations.

Introduction: Chest Compression Synchronized Ventilation (CCSV) is a novel approach aimed at optimizing gas exchange and hemodynamics during cardiopulmonary resuscitation (CPR). However, its clinical value, safety profile and implementation barriers remain unclear. This study aimed to systematically synthesize existing evidence on the use of CCSV during cardiac arrest in animals and humans.

Methods: We conducted a scoping review and systematically searched five databases (Medline, Embase, CENTRAL, Scopus, Web of Science) up to May 2025. Studies investigating CCSV or mechanistically related ventilation strategies during cardiac arrest were included regardless of study design, language or publication date. Data were charted for study characteristics, outcomes and adverse events.

Results: Thirty-two studies published between 1980 and 2025 were included. Most were animal studies (n=19), primarily conducted in pigs, with limited human data (n=10). CCSV showed positive effects on arterial oxygenation, carbon dioxide clearance, and hemodynamic parameters as well as cerebral oxygenation compared to conventional ventilation modes. Adverse events such as pneumothorax and lung injury were inconsistently reported.

Conclusions: Available data on CCSV suggests potential physiological benefits during CPR, particularly in experimental settings. Human data remain scarce, and larger, prospective human trials are essential to evaluate clinical effectiveness, guide implementation, and assess risks compared to conventional ventilation strategies.

Introduction: Traumatic optic neuropathy (TON) is a serious condition resulting from optic nerve injury, often due to head trauma. This study systematically reviews the existing literature to evaluate the effectiveness of various treatments in improving visual outcomes in TON patients.

Methods: A comprehensive literature search was conducted across databases including Medline (via PubMed), Web of Science, Cochrane Library, and EMBASE from January 1992 to October 2024. Studies were selected based on inclusion criteria that focused on TON patients treated with corticosteroids, conservative therapy, erythropoietin therapy, or surgical interventions. Quality assessment of the included studies was performed using the Joanna Briggs Institute (JBI) Risk of Bias Tool for each design. Data extraction and quality assessment were performed by two independent reviewers, with a meta-analysis conducted to evaluate the pooled visual acuity (VA) improvement rates.

Results: A total of 23 studies were included, encompassing 1,851 patients with TON. The meta-analysis revealed a pooled VA improvement rate of 50.6% across all treatment modalities. Specifically, corticosteroid-only treatment resulted in a 56.2% improvement rate, while combined corticosteroid and surgical decompression showed a 42.9% improvement rate. Conservative therapy had a 47.8% improvement rate. The heterogeneity among studies was significant (I²= 89.9%), and no significant publication bias was detected. Subgroup analyses indicated varied outcomes, with some studies reporting better results with early intervention.

Conclusion: The treatment of TON remains challenging, with no single modality showing clear superiority. The corticosteroids and surgical interventions provide potential benefits; however, conservative therapy might be appropriate for certain cases. Future research should focus on optimizing treatment protocols and exploring new therapeutic options, such as erythropoietin to improve visual outcomes in TON patients.

Introduction: The diagnostic accuracies of different electrocardiography (ECG) interpretation methods remain unclear. Therefore, this study aimed to systematically evaluate and compare the diagnostic accuracy of prehospital 12-lead ECG interpretation methods for identifying ST-elevation myocardial infarction (STEMI) and activating cardiac catheterization laboratories (CCLs).

Methods: A comprehensive search was conducted in Medline, Scopus, and CINAHL databases up to August 2024. Two reviewers independently selected studies that assessed the diagnostic accuracy of prehospital 12-lead ECG in real-time STEMI identification and CCL activation. Pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated using bivariate generalized mixed-effects regression models or random-effects meta-analysis as appropriate. The quality of the included studies was assessed using the QUADAS-2 tool.

Results: Thirty-six studies involving 67,168 patients were included. Overall, for STEMI identification, the pooled AUC of ECG was 0.96 (95%CI:0.94–0.98), sensitivity was 80% (95% CI, 69–88%), specificity was 97% (95%CI: 94–98%), and DOR was 114 (95%CI: 59–222). Ambulance clinicians achieved the highest DOR (264; 95%CI: 33–2125), followed by transmission method (136; 95%CI, 59–312) and computer-assisted analysis (78; 95%CI: 33–186). Transmission method demonstrated superior specificity (‎0.98; 95%CI: 0.94-0.99‎) and the lowest rates of inappropriate (13.2%; 95% CI: ‎8.6%–19.2%), and false-positive (11.0%; 95%CI: 6.9%–15.0%) CCL activations.

Conclusion: All prehospital ECG interpretation methods yielded acceptable diagnostic accuracy for STEMI identification; however, transmission offered the greatest specificity and fewer unnecessary CCL activations. Adopting transmission-based strategies, where feasible, and enhancing training and decision support for ambulance clinicians may improve prehospital STEMI detection and resource utilization.

Introduction: Risk perception is a cognitive, multidimensional process through which individuals identify and assess potential threats. This study aimed to systematically review the recent research to identify the key factors influencing the risk perception within healthcare workers operating in critical and disaster scenarios.

Methods: This study was conducted as a systematic review in accordance with PRISMA guidelines. A search was performed for articles published between January 2014 and July 2025 in the PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases. Of the 2,154 initial articles, 10 eligible studies were included in the analysis following screening and quality assessment. Quantitative, qualitative, and mixed-methods studies addressing factors influencing healthcare workers' risk perception during disasters were selected, and the data were coded and categorized using thematic analysis.

Results: The analysis of the 10 selected studies identified a central theme titled "Factors Influencing Risk Perception," which was further divided into five key domains: 1) Demographic and individual factors, 2) Experience and exposure to risk, 3) Knowledge resources and information capital, 4) Cognitive–emotional attitudes and beliefs, and 5) Protective behaviors and measures.

Conclusion: This review demonstrates that healthcare workers' risk perception during disasters is a multifaceted phenomenon shaped by the interaction of individual, experiential, knowledge-based, emotional, and behavioral factors. Understanding these dimensions is crucial for explaining responses and designing interventions to enhance resilience and preparedness among healthcare workers. Based on the conceptual framework, it is recommended that educational programs and organizational policies consider demographic differences, experiences, and the psychosocial needs of staff.

Introduction: Exosomes function as cell signaling carriers and have drawn much attention to the cell-free treatments of regenerative medicine. This meta-analysis aimed to investigate the efficacy of mesenchymal stem cell-derived (MSC-derived) exosomes in animal models of spinal cord injuries (SCI).

Method: A comprehensive search was conducted in Medline, Embase, Scopus, and Web of Science to attain related articles published by January 31, 2023. The eligible keywords were correlated with the spinal cord injury and MSC-derived exosomes. The evaluated outcomes were locomotion, cavity size, cell apoptosis, inflammation, neuro-regeneration, and microglia activation. A standardized mean difference was calculated for each sample and a pooled effect size was reported.

Results: 65 papers fully met the inclusion criteria. Treatment with MSC-derived exosomes ultimately improved locomotion and shrunk cavity size (p<0.0001). The administration of MSC-derived exosomes enhanced the expression of beta-tubulin III, NF200, and GAP-43, and increased the number of NeuN-positive and Nissl-positive cells, while reducing the expression of glial fibrillary acidic protein (p<0.0001). The number of apoptotic cells in the treatment group decreased significantly (p<0.0001). Regarding the markers of microglia activation, MSC-derived exosomes increased the number of CD206- and CD68-positive cells (p=0.032 and p<0.0001, respectively). Additionally, MSC-derived exosome administration significantly increased the expression of the anti-inflammatory interleukin (IL)-10 and IL-4 (p<0.001 and p=0.001, respectively) and decreased the expression of the inflammatory IL-1b, IL-6, and TNF-a (p<0.0001).

Conclusion: MSC-derived exosome treatment resulted in a significantly improved locomotion of SCI animals through ameliorating neuroinflammation, reducing apoptosis, and inducing neuronal regrowth by facilitating a desirable microenvironment.

Cardiac arrest is a life-threatening condition with a high mortality rate, necessitating prompt recognition and treatment of reversible causes to enhance patient survival. Point-of-care ultrasound (POCUS) has emerged as a useful tool that contributes to optimizing resuscitative efforts. This imaging modality offers real-time visualization that assists in detecting reversible causes such as cardiac tamponade, pulmonary embolism, tension pneumothorax and hypovolemia. This review aims to explore the expanding role of ultrasound in the assessment and management of cardiac arrest, emphasizing its utility in identifying cardiac arrest, differentiating between true pulseless electrical activity (PEA) and pseudo-PEA, detecting the reversible causes, guiding clinical decision-making, and potentially predicting outcomes. A comprehensive literature search was performed using the PubMed database from inception to April 2025. Articles were selected based on their relevance to the role and applications of POCUS in cardiac arrest.

Introduction: Heart failure (HF) is a prevalent and advancing cardiovascular disorder that impacts 1-2% of the worldwide population, particularly the elderly. Studies indicate that the intravenous administration of apelin may yield advantageous effects in preventing heart failure subsequent to myocardial injury. This meta-analysis aimed to assess the effects of exogenous apelin administration on heart failure in animal models, in light of the lack of a definitive consensus on the matter.

Method: An extensive search was performed in the Medline (via PubMed), Web of Science, Embase, and Scopus databases till the end of January 2024. Two independent reviewers screened and summarized the relevant articles. Outcomes related to cardiac function, including ejection fraction (EF), maximum and minimum rate of left ventricle systolic pressure (+dp/dt and –dp/dt, respectively), heart rate, left ventricular end-diastolic pressure (LVEDP), and left ventricular systolic pressure (LVSP) were assessed. Findings were reported as a pooled standardized mean difference (SMD) with a 95% confidence interval (95% CI).

Results: 12 studies were included. Pooled analysis demonstrated that early treatment with apelin following myocardial injury significantly increases +dp/dt (SMD = 2.36; 95% CI: 1.58 to 3.15; p < 0.001) and decreases -dp/dt (SMD = -3.31; 95% CI: -4.46 to -2.17; p < 0.001). Furthermore, the administration of apelin resulted in a significant increase in EF (SMD = 0.79; 95% CI: 0.15 to 1.44; p = 0.02) and LVSP (SMD = 2.09; 95% CI: 0.82 to 3.36; p < 0.001), while it led to a decrease in LVEDP in the animals (SMD = -1.85; 95% CI: -2.81 to -0.88; p < 0.001). Noteworthy, apelin treatment was shown to have no significant influence on the heart rate of the animals (SMD = -0.12; 95% CI: -0.82 to -0.58; p = 0.73).

Conclusion: The current study demonstrated that the early administration of apelin has the potential to improve cardiac function and mitigate the onset of heart failure subsequent to myocardial injury. Further, in vivo research is essential to lay the groundwork for the integration of apelin into clinical practice.

Introduction: Previous studies have investigated different methods for estimating neurological outcomes after cardiac arrest. However, there is still much uncertainty about using optic nerve sheath diameter (ONSD) measurement as an indirect method for predicting neurological outcomes following cardiac arrest. In this meta-analysis, we aimed to investigate the value of ONSD for predicting the neurological outcomes of cardiac arrest survivors.

Methods: We comprehensively performed a systematic search in three main electronic databases, including Scopus, Medline, and Web of Science Cochrane, from inception to August 2024. Based on the heterogeneity evaluation results, fixed or random effects models were used to estimate the pooled diagnostic parameters. Meta-regressions were performed for subgroup analysis.

Results: The pooled sensitivity and specificity of ONSD for predicting the neurological outcomes were 0.56 (95% CI, 0.35–0.74) and 0.92 (95% CI, 0.85–0.96), respectively. Meta-regression revealed that as the cutoff level of ONSD increases, the sensitivity significantly decreases (P < 0.01), while the specificity significantly increases (P = 0.01). Furthermore, meta-regression analysis revealed that ONSD measurement using CT scans is significantly associated with lower sensitivity and higher specificity compared to ultrasound (P = 0.009 and P = 0.01).

Conclusion: Our meta-analysis showed that ONSD has low sensitivity and high specificity for predicting neurological outcomes in survivors of cardiac arrest. However, since the cut-off values and methods of ONSD measurement affect its predictive performance, further studies will be required to standardize these factors to achieve optimal predictive parameters.

Introduction: Evidence supports the clinical applicability of near-infrared spectroscopy (NIRS) in intracranial hematoma detection in prehospital settings. This systematic review and meta-analysis aimed to determine the diagnostic yield of NIRS for detecting intracranial hematoma in traumatic brain injury (TBI) patients.

Methods: A systematic search was performed in July 2024 in Medline, Embase, Scopus, and Web of Science databases. We included studies that evaluated the diagnostic performance of NIRS in detecting intracranial hematoma in both adult and pediatric patients suspected of TBI in prehospital or emergency settings, using brain computed tomography (CT) scan or magnetic resonance imaging as the gold standard.

Results: Eighteen studies enrolling 2979 patients were included. NIRS exhibited an Area Under the Curve (AUC) of 0.91 (95% confidence interval [CI]: 0.88, 0.93), with a sensitivity of 0.86 (95% CI: 0.78, 0.91), and specificity of 0.82 (95% CI: 0.72, 0.89) across all age groups. In children, the results demonstrated an AUC of 0.92 (95% CI: 0.89, 0.94), sensitivity of 0.95 (95% CI: 0.21, 1.00), and specificity of 0.81 (95% CI: 0.65, 0.91). Among adults, the AUC was 0.91 (95% CI: 0.88, 0.93), with sensitivity and specificity of 0.86 (95% CI: 0.78, 0.92) and 0.83 (95% CI: 0.70, 0.91), respectively. Performance improved when NIRS was operated by non-physicians (AUC = 0.94 [95% CI: 0.91, 0.96], sensitivity = 0.90 [95% CI: 0.79, 0.95], specificity = 0.85 [95% CI: 0.71, 0.93]) compared to physicians (AUC = 0.90 [95% CI: 0.87, 0.92], sensitivity = 0.88 [95% CI: 0.77, 0.94], specificity = 0.75 [95% CI: 0.59, 0.76]). Patients' age group and operator type were identified as potential sources of heterogeneity. Sensitivity analyses confirmed the robustness of the findings, particularly in mild TBI cases and studies implementing a ΔOD > 0.2 as the threshold for a positive NIRS result.

Conclusion: NIRS proves to be an effective diagnostic tool for detecting traumatic intracranial hematoma in both pediatric and adult groups, with high sensitivity and specificity. Its utility in prehospital triage, operated by physicians or paramedics, underscores its potential for broader clinical application.

Introduction: Foreign body aspiration (FBA) is a common, life-threatening pediatric emergency and was shown to be associated with high risk of morbidity and mortality. This systematic review and meta-analysis aimed to investigate the diagnostic value of chest computed tomography (CT) scan for identification of FBA in children.

Methods: From inception to May 2024, a systematic search was carried out across multiple databases including Medline, Scopus, and Web of Science, considering published papers in English language. Quality assessment of the included studies was performed using seven domains of Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2).

Results: The systematic literature search yielded 7203 articles. The pooled sensitivity and specificity of chest CT scan for identification of FBA were 0.99 (95% CI: 0.98-0.99) and 0.97 (95% CI: 0.96-0.98), respectively. The pooled positive likelihood ratio was 10.12 (95% CI: 4.59-22.20), and pooled negative likelihood ratio was 0.05 (95% CI: 0.02-0.1). Furthermore, the area under the summarized receiver operating characteristic (SROC) curve was 0.98.

Conclusion: Our meta-analysis revealed that despite high heterogeneity, in the diagnostic characteristics of chest CT scan among studies, it has high diagnostic value in identifying FBA in suspected pediatric cases.

Introduction: Combining multiple drugs for intubation raises concerns such as increased side effects, medication errors, nursing workload, and costs. Ketamine, with its anesthetic and analgesic properties, shows promise as a sedative agent for post-intubation care. This study aimed to evaluate the efficacy and safety of ketamine infusion as the sole sedative for critically ill intubated patients.

Methods: Following PRISMA 2020 guidelines, we conducted a systematic review by searching Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and Google Scholar up to May 10, 2024. We included studies assessing ketamine use for post-intubation sedation in critically ill adults or children. Study quality was assessed using the Newcastle–Ottawa scale, and meta-analysis was performed using a random-effects model.

Results: The systematic review included 7 studies, with 4 studies included in the meta-analysis. There was no significant difference in mortality (OR = 1.52; 95% CI: 0.49–4.70, p = 0.46; I2 = 83%) or length of hospital stay (MD = 6.42; 95% CI: -1.42-14.26, p = 0.11; I2 = 84%) between the ketamine only and other groups. The most common adverse events in the ketamine infusion group were atrial fibrillation and agitation.

Conclusion: Single-agent ketamine infusion is effective and safe for critically ill intubated patients. No significant differences were found in mortality or hospital stay between ketamine only and other groups. Atrial fibrillation and agitation were the most common adverse effects.

Introduction: Meta-analyses of diagnostic/prognostic studies for calculating the pooled sensitivity and specificity require true positive (TP), true negative (TN), false positive (FP), and false negative (FN) counts. However, few studies report these values directly. This study aimed to consolidate practical methods to reconstruct sensitivity and specificity from minimal data.

Methods: Our framework addresses three main situations: (1) algebraic rearrangements to compute specificity given partial metrics; (2) digitization of receiver operating characteristic (ROC) curves to obtain threshold-specific sensitivity and specificity; and (3) application of the binormal model when only AUC and prevalence are available. We tested these methods on a dataset related to mortality prediction in myocardial infarction (MI) using machine learning models, assessing how well they reconstructed sensitivity and specificity.

Results: Algebraic formulas and ROC digitization yielded reliable estimates when partial metrics or graphical curves were sufficiently detailed. However, the binormal model, which assumes equal variances, showed noticeable inaccuracies, especially for sensitivity. Linear regression analyses indicated that higher prevalence and higher AUC reduced estimation errors.

Conclusion: These methods offer practical alternatives for reconstructing diagnostic accuracy measures when data are incomplete. Relying solely on AUC-based estimations may introduce substantial bias, particularly in low-prevalence contexts. We recommend that primary studies report threshold-specific sensitivity and specificity to support more accurate meta-analytic estimations.

Introduction: Surgical site infection (SSI) constitutes a substantial complication after knee arthroplasty, contributing to notable morbidity. This study aimed to review the existing literature on the incidence and risk factors of SSI following knee arthroplasty.

Methods: A systematic search was undertaken across various international electronic databases, including Scopus, PubMed, Web of Science, and Persian electronic databases such as Iranmedex and the Scientific Information Database. The search strategy involved the use of keywords derived from Medical Subject Headings, such as “incidence”, “Surgical wound infection”, “Surgical site infection”, and “Arthroplasty”, covering records from the earliest available up to March 17, 2024.

Results: The study incorporated a collective participant group of 1,366,494 knee arthroplasty procedures from twenty-three chosen studies. The pooled incidence rate of SSI after knee arthroplasty was 1.7% (95% confidence interval (CI): 1.1% to 2.6%; I²=99.687%; P<0.001). The Odds Ratio (OR) for the incidence of SSI in males was observed to be significantly higher than that in females (OR: 1.617; 95% CI: 1.380 to 1.894; Z=5.951; P<0.001). The pooled incidence of SSI among diabetic patients was 1.3% (95% CI: 0.6% to 2.8%; I²=99.126%; P<0.001).

Conclusion: Based on the main findings, SSIs continue to be a significant complication of knee arthroplasty, with an incidence of 1.1% to 2.6%. Male gender and diabetes mellitus were associated with an augmented probability of SSIs following knee arthroplasty.

Introduction: Diabetic ketoacidosis (DKA) is one of the complications of diabetes mellitus that requires rapid and accurate diagnosis. End-tidal carbon dioxide (EtCO₂) has been used for diagnosing DKA, however, there is uncertainty about the predicting value of this tool. In the current systematic review and meta-analysis, we purposed to assess the predictive value of EtCO₂ in diagnosing DKA.

Methods: We conducted a comprehensive search in PubMed, Scopus, and Web of Science for relevant studies and after screening based on the inclusion criteria, we extracted data. DKA diagnosis in the included studies was based on a composite clinical reference standard, including arterial blood gas (ABG) analysis and ketone testing. We used the Joanna Briggs Institute (JBI) checklist for diagnostic test accuracy studies for quality appraisal. Meta-analysis was performed based on the methods of the Cochrane DTA Handbook using the MetaDTA: Diagnostic Test Accuracy Meta-Analysis v2.1.3.

Results: A total of 13 studies were included in the systematic review, eight of which were proceeding to meta-analysis. The pooled sensitivity and specificity of EtCO₂ for diagnosing DKA were 0.96 (95% confidence interval (CI): 0.85-0.93) and 0.88 (95% CI: 0.79-0.93), respectively. The pooled diagnostic odds ratio (DOR) was 211.07 (95% CI: 38.3- 1162.1). The positive and negative likelihood ratios were 8.27 (95% CI: 4.6-14.7) and 0.03 (95% CI: 0.009-0.18), respectively. The results of the quality appraisal of include studies indicated moderate to low risk of bias.

Conclusions: The findings of this systematic review and meta-analysis show the high sensitivity and specificity of EtCO₂ in diagnosing DKA, which indicates its potential as a reliable diagnostic tool in emergency settings. However, the overall quality of the included studies, which were assessed to have medium to high risk of bias, should be considered when using EtCO₂ in clinical practice. Further high-quality research is needed to confirm the diagnostic value of EtCO₂ in emergency settings.

Ozone therapy, often marketed as an immune-boosting alternative treatment, lacks robust evidence of efficacy and poses significant safety risks. Despite claims of therapeutic benefits, Regulatory agencies, such as the U.S. Food and Drug Administration (FDA), warn against its use due to its toxic properties and lack of proven benefits at tolerable exposure levels. This case report highlights severe neurological complications, including ischemic infarcts and persistent cognitive deficits, following intravenous ozone (O₃) therapy in a previously healthy patient. A 36-year-old woman presented to the emergency department with chest pain, syncope, and generalized seizure shortly after receiving intravenous ozone therapy. Diagnostic imaging revealed multiple ischemic infarcts in the thalamus and cerebellum, consistent with an embolic event. The patient required intensive care unit (ICU) admission, and despite improved neurological function experienced lasting cognitive impairments necessitating long-term rehabilitation.

Aortic dissection (AD), a life-threatening cardiovascular emergency, is characterized by the separation of the aorta’s inner and middle layers due to a tear in the intima. It is classified as Stanford type A or B based on the tear’s location and extent. Symptoms vary but commonly include severe pain in the chest, back, or abdomen, along with atypical presentations such as shock, heart failure, or syncope. End-organ ischemia, including stroke and limb necrosis, may occur. Timely diagnosis and intervention are crucial for survival. Here, we report a 31-year-old male patient who presented with acute neurological symptoms, initially suspected of having a stroke, but was ultimately diagnosed with Stanford type A AD upon computed tomography (CT) angiography. This case underscores the importance of considering AD in the differential diagnosis of patients with neurological symptoms for accurate and prompt management.

Cardiopulmonary resuscitation (CPR) remains controversial with dismal outcomes for cardiac arrest (CA) victims. Inadequate organ perfusion and frequent CPR-related trauma most likely occur due to inappropriate adaptation to hemostatic conditions, electrophysiology, cardiotorsal anatomy, and thoracic biomechanics. Alternatively, we propose a new technique compromising chest compressions through the 5^th intercostal space while placing the victim in the left lateral decubitus position with wrapped abdomen and raised legs, allowing to: bypass the sternal barrier, refill the heart, and then recoil-rebound the chest (3R /CPR), within the axis of the cylindrical ribcage. Our goal is to evaluate the technique following its necessary application on two drowning victims. It seems that, 3R/CPR adapts the pathophysiological conditions of CA victims promoting a less traumatic return of spontaneous circulation (ROSC), making it worthy of further investigation and study.

ST segment elevation patterns on Electrocardiogram (ECG) are a crucial finding in the diagnosis and treatment of acute coronary syndrome. An ST segment elevation pattern can be a sign of acute myocardial ischemia requiring immediate intervention. However, ST elevation patterns have been reported to occur due to obstructive intraabdominal pathology, a diagnosis often confirmed by cardiac catheterization. Here we report a 75-year-old female who presented to the emergency department with worsening chest and epigastric abdominal pain.  ECG demonstrated ST-segment elevations in inferior leads (II, III, and aVF) with reciprocal changes in the lateral leads (I and aVL).  Physical exam was suggestive of a bowel obstruction at the site of a large incarcerated ventral hernia, which was later confirmed by imaging. Due to the lack of typical chest pain symptoms and a strong suspicion of obstructive intraabdominal pathology, activation of the catheterization laboratory was deferred.  Decompression of the bowel obstruction was achieved with a nasogastric tube, which resulted in immediate resolution of ST-segment elevations. During her admission, her ventral hernia was repaired, and left heart catheterization was deferred per cardiology recommendations. While an ST-segment elevation due to occlusive myocardial infarction is a diagnosis that cannot be missed and requires an emergent workup, it is important to be aware that it is possible for a small bowel obstruction (SBO) to present with ECG changes consistent with an ST-segment elevation myocardial infarction (STEMI). We also found that ST-segment elevations due to obstructive intraabdominal pathology are more reportedly seen in the literature in the inferior leads than any other contiguous leads, which is a novel pattern not discussed in past literature.

There were 70 articles published in the 2024 volume of Archives of Academic Emergency Medicine. Around 350 authors contributed to the published works, who were affiliated to centers located in countries such as USA, Canada, Germany, Finland, China, Poland, Italy, Australia, UAE, Malaysia, India, Egypt, Bangladesh, Turkey, Thailand, Nigeria, Jordon, Yemen, Saudi Arabia, Azerbaijan, Vietnam, Pakistan. We would like to thank the authors for trusting us with their valuable works and publishing their articles with us.

After a burn injury, pre-hospital care, which includes first aid measures before transfer to a burns center, is considered to be a significantly important step in the process of burn treatment. Individuals who receive medical care at a hospital following initial first aid administered at home experience a better outcome. This letter aimed to discuss about the importance and obstacles of prehospital management of burn injuries.

A study by Le Xuan et al. suggested that the lactate/albumin ratio (LAR) may aid in predicting sepsis-associated acute kidney injury. However, overlapping receiver operating characteristic (ROC) curve confidence intervals, creatinine-only acute kidney injury (AKI) definitions, and single-point biomarker assessments limit interpretation. Given its single-centre retrospective design, broader validation with dynamic biomarkers and kidney-specific comparators is needed before the LAR can be integrated into sepsis risk stratification.

This letter suggests that relabelling often reflects documentation differences rather than diagnostic error. It highlights higher mismatch rates in paediatric and neurological patients and considers whether improved coding systems or earlier access to investigations could reduce these gaps. Future studies assessing diagnostic confidence at admission and stronger collaboration between emergency and inpatient teams may also help improve concordance.