External validation of the 2020 ERC/ESICM prognostication strategy algorithm after cardiac arrest

Abstract

Purpose To assess the performance of the post-cardiac arrest (CA) prognostication strategy algorithm recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM) in 2020. Methods This was a retrospective analysis of the Korean Hypothermia Network Prospective Registry 1.0. Unconscious patients without confounders at day 4 (72–96 h) after return of spontaneous circulation (ROSC) were included. The association between the prognostic factors included in the prognostication strategy algorithm, except status myoclonus and the neurological outcome, was investigated, and finally, the prognostic performance of the prognostication strategy algorithm was evaluated. Poor outcome was defined as cerebral performance categories 3–5 at 6 months after ROSC. Results A total of 660 patients were included in the final analysis. Of those, 108 (16.4%) patients had a good neurological outcome at 6 months after CA. The 2020 ERC/ESICM prognostication strategy algorithm identified patients with poor neurological outcome with 60.2% sensitivity (95% CI 55.9–64.4) and 100% specificity (95% CI 93.9–100) among patients who were unconscious or had a GCS_M score ≤ 3 and with 58.2% sensitivity (95% CI 53.9–62.3) and 100% specificity (95% CI 96.6–100) among unconscious patients. When two prognostic factors were combined, any combination of prognostic factors had a false positive rate (FPR) of 0 (95% CI 0–5.6 for combination of no PR/CR and poor CT, 0–30.8 for combination of No SSEP N20 and NSE 60). Conclusion The 2020 ERC/ESICM prognostication strategy algorithm predicted poor outcome without an FPR and with sensitivities of 58.2–60.2%. Any combinations of two predictors recommended by ERC/ESICM showed 0% of FPR.

Prognostic accuracy of head computed tomography for prediction of functional outcome after out-of-hospital cardiac arrest: Rationale and design of the prospective TTM2-CT-substudy

“… 29 In a recent guideline validation study from South-Korea where therapy is rarely withdrawn, Youn et al reported a specificity of only 86% for the finding of a “poor CT” when evaluated by radiologists blinded to clinical data. 6 Similar results have been reported for diffusion-weighted sequences on MRI. 35 Although combinations of imaging techniques with other prognostic methods predicted poor outcome without false positive predictions in validation studies, the lack of a standardized radiological assessment of HIE may pose a risk for patients.…”

“… 35 Although combinations of imaging techniques with other prognostic methods predicted poor outcome without false positive predictions in validation studies, the lack of a standardized radiological assessment of HIE may pose a risk for patients. 6 , 29 , 36 , 37 For this reason, since decisions on WLST within the TTM2 trial could also be based on CT findings, we will evaluate how well our radiological assessments correlate with blood levels of a surrogate marker of brain injury, the serum concentration of NFL. We have previously demonstrated that low levels of NFL predicted good outcome in 95% of patients, and that by combining biomarkers with other prognostic methods, the risk of false pathological CT evaluations could be minimized.…”

“… 2 Its performance for outcome prediction in clinical practice is likely influenced by both interrater variability (at least partly due to lack of standardization of the CT evaluation process) and technical parameters – inter-scanner variability. 6 , 7 , 8 , 9 , 10 , 11 This potentially introduces a risk for a false pessimistic prediction of poor outcome. 7 , 8 …”

Association of ultra-early diffusion-weighted magnetic resonance imaging with neurological outcomes after out-of-hospital cardiac arrest

“…Third, it is important to achieve a FPR of zero because poor outcome predictors can be used to determine the WLST; but high sensitivity at FPR 0% is required to be useful as a predictive tool [33]. However, in the recently reported study, the external validation of the 2020 ERC/ESICM prognostic strategy algorithm after cardiac arrest, a FPR of 0% was achieved; but the sensitivity was at the level of 60% [34]. In this study, DW-MRI provided results within 6 h after ROSC, did not require specific expertise to discriminate P HSI only, and showed a sensitivity of 74.2% at FPR 0% to predict poor neurological outcome.…”

Sex difference on neurological outcomes and post-cardiac arrest care in out-of-hospital cardiac arrest patients treated with targeted temperature management

“…The prognosis was considered poor when there was one abnormal result for any single predictor (the absence of brainstem re exes, injury on brain CT or DWI, highly malignant EEG, high NSE level, and absence of the N20 wave on SSEP). We also used the multimodal algorithm recommended by the European Resuscitation Council/European Society of Intensive Care Medicine considering a combination of ≥ 2 abnormal results on any prognostic tests to indicate a poor outcome [15,21].…”