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. 2022 Apr 11;26(1):95.
doi: 10.1186/s13054-022-03954-w.

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

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

Chun Song Youn et al. Crit Care. .

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.

Keywords: Cardiac arrest; Guideline algorithm; Outcome; Prognostic accuracy.

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Conflict of interest statement

None of the authors has declared a conflict of interest.

Figures

Fig. 1
Fig. 1
Flow diagram of included patients. Unconscious patients ≥ 72 h after ROSC without confounders (N = 660) were defined as the first cohort to test the GCS_M score as one variable in the algorithm. Unconscious patients with a GCS_M score ≤ 3 at ≥ 72 h after ROSC without confounders (N = 589) were defined as the second cohort
Fig. 2
Fig. 2
Prognostic performance of the 2020 ERC/ESICM prognostication strategy algorithm in cardiac arrest patients treated with targeted temperature management. A The 2020 ERC/ESICM prognostication strategy algorithm for the first cohort. The 2020 ERC/ESICM prognostication strategy algorithm predicted poor outcome without a false positive rate (FPR) and with sensitivities of 58.2%. B The 2020 ERC/ESICM prognostication strategy algorithm for the second cohort. The 2020 ERC/ESICM prognostication strategy algorithm predicted poor outcome without a false positive rate (FPR) and with sensitivities of 60.2%

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