Prediction of good functional outcome decreases diagnostic uncertainty in unconscious survivors after out-of-hospital cardiac arrest

Purpose: To explore modifications of the 2021 European Resuscitation Council/European Society of Intensive Care Medicine (ERC/ESICM) guideline algorithm for neuroprognostication after cardiac arrest to improve its prognostic accuracy. Methods: Post-hoc analysis of four prospective multicentre studies (TTM, TTM2, KORHN and ProNeCA). We raised the Glasgow Coma Scale motor (GCS-M) inclusion threshold at 72 h after cardiac arrest from the current GCS-M < 4 to GCS-M < 6 (all unconscious patients). Secondly, we included good outcome predictors (GCS-M 4-5, neuron-specific enolase < 17 <mu>g/L, benign electroencephalography patterns <= 72 h post-arrest and normal magnetic resonance imaging at 72-168 h post-arrest) in the algorithm. Functional outcome was assessed dichotomously at six months, including modified Rankin Scale 0-3, Cerebral Performance Category 1-2 or Glasgow Outcome Scale 4-5 (no symptoms to moderate disability) as good outcome. Results: We analysed 3,388 patients, of whom 2,079 had GCS-M < 4 at >= 72 h. Of the 874 patients identified by the 2021 ERC/ESICM poor outcome criteria, 870 had poor functional outcome (specificity: 99.6% [95%CI 99.0-99.9]). Using the GCS-M < 6 threshold, 366 more patients entered the algorithm (N = 2,445). Seven more patients with poor outcomes were identified, with close to identical specificity. Good outcome predictors thereafter identified 673 patients with potential recovery, of whom 411 (61%) had a good functional outcome at six months. With the updated algorithm, the number of prognosticated patients with an indeterminate prognosis decreased from 1,205/2,079 (58%) to 891/2,445 (36%). Conclusion: Raising the GCS-M inclusion threshold and adding favourable predictors to the 2021 ERC/ESICM prognostication algorithm reduced prognostic uncertainty without increasing falsely pessimistic predictions.