Statistical analysis
Study features and patients’ characteristics were reported. Data are presented as number (percentage) or mean and 95% confidence interval (CI), as appropriate. The pooled estimated prevalence of each outcome was calculated utilizing a random-effect model, which is more generalized when potential heterogeneity among studies is present. All values were presented with 95% confidence intervals (CI), and the weighted prevalence of outcomes is depicted as a forest plot. We assessed the homogeneity of incidence of events across studies using Cochran Q for each of the outcomes. Also, to test for heterogeneity, Higgins I2 was calculated.I2 represents the percentage of total variation across studies that can be attributed to heterogeneity rather than chance. The I2 value 0% indicates no heterogeneity, 25% low heterogeneity, 50% moderate heterogeneity, and 75% high heterogeneity (9). Funnel plots were drawn for all extracted outcomes to assess publication bias. Visual inspection of asymmetry was assessed to check for publication bias, and Egger’s test was also conducted to evaluate small-study effects on the pooled estimated outcome (10). Moreover, Moment base univariate meta-regression was performed to assess the effects of hypothermic circulatory arrest (HCA) time on neurologic outcomes (stroke and SCI), depicted as bubble plot. All data were analyzed using STATA software (StataCorp, TX, USA).