Optic Nerve Sheath Diameter in Predicting the Neurological Outcomes of Cardiac Arrest Survivors: A Systematic Review and Meta-analysis - Jafari Khouzani, Parisa; Rahmani, Erfan; Rezaei, Mehdi; Pohrbagher Benam, Sasan; Moghadam Fard, Atousa; Amani-Beni, Reza; Daneshvar, Maziar; Jalayer Sarnaghy, Faezeh; Masoomi Goodarzi, Naghme; Abedi Azar, Ramila; Mirbolook, Amirhossein; Bashghareh, Peyman; et al. (Archives of Academic Emergency Medicine, 2025)
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.