An article published in Crit_Care analyzes the performance of post-arrest and pre-arrest prediction models for neurological outcome after cardiac arrest. The prognostic accuracy of these models may support decisions on care and therapeutic efforts.
Sensitivity analyses with exclusion of studies with a high risk of bias were not conducted since only two studies were judged to have low risk of bias overall. Instead, a subgroup analysis was conducted, assessing the score performance in studies at high risk of bias due to the inclusion of an inappropriately small number of patients and in studies with an adequately large sample. The OHCA and CAHP scores performed similarly in both subgroups .
A random-effects meta-regression analysis showed no significant correlation between either mean/median patient age or percentage of a good outcome and C-statistic in the validation studies for the OHCA and CAHP score . For the GO-FAR score, the number of studies was too small to perform subgroup and meta-regression analyses.
The pre-arrest GO-FAR score showed acceptable discriminatory performance with the analysis of overall calibration showing substantial underestimation of good outcome. Results were similar across all subgroup analyses, indicating that the results presented in this meta-analysis are robust and the OHCA and CAHP scores perform well in predicting mortality or neurological outcome as measured by CPC, with predictions being accurate for outcomes assessed at hospital discharge as well as up to 6 months after cardiac arrest.
An important finding of this systematic review is the observed poor reporting across validation studies, a problem that has previously been highlighted [
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