Neurological outcome following out of hospital cardiac arrest: Evaluation of performance of existing risk prediction models in a UK cohort

John A Livesey; Nazir Lone; Emily Black; Richard Broome; Alastair Syme; Sean Keating; Laura Elliott; Cara McCahill; Gavin Simpson; Helen Grant; Fiona Auld; Sweyn Garrioch; Alasdair Hay; Thomas H Craven

doi:10.1177/17511437231214146

Neurological outcome following out of hospital cardiac arrest: Evaluation of performance of existing risk prediction models in a UK cohort

J Intensive Care Soc. 2023 Dec 21;25(2):131-139. doi: 10.1177/17511437231214146. eCollection 2024 May.

Authors

Affiliations

¹ Edinburgh Critical Care Research Group, Department of Critical Care, Royal Infirmary of Edinburgh, Edinburgh, UK.
² Department of Critical Care, Royal Infirmary of Edinburgh, Edinburgh, UK.
³ Department of Critical Care, Victoria Hospital Kirkcaldy, Kirkcaldy, UK.
⁴ Department of Critical Care, St John's Hospital, Livingston, UK.
⁵ Department of Critical Care, Western General Hospital, Edinburgh, UK.
⁶ Department of Critical Care, Borders General Hospital, Melrose, UK.

Abstract

Introduction: Out of hospital cardiac arrest (OHCA) is a common problem. Rates of survival are low and a proportion of survivors are left with an unfavourable neurological outcome. Four models have been developed to predict risk of unfavourable outcome at the time of critical care admission - the Cardiac Arrest Hospital Prognosis (CAHP), MIRACLE₂, Out of Hospital Cardiac Arrest (OHCA), and Targeted Temperature Management (TTM) models. This evaluation evaluates the performance of these four models in a United Kingdom population and provides comparison to performance of the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score.

Methods: A retrospective evaluation of the performance of the models was conducted over a 43-month period in 414 adult, non-pregnant patients presenting consecutively following non-traumatic OHCA to the five units in our regional critical care network. Scores were generated for each model for where patients had complete data (CAHP = 347, MIRACLE₂ = 375, OHCA = 356, TTM = 385). Cerebral Performance Category (CPC) outcome was calculated for each patient at last documented follow up and an unfavourable outcome defined as CPC ⩾ 3. Performance for discrimination of unfavourable outcome was tested by generating receiver operating characteristic (ROC) curves for each model and comparing the area under the curve (AUC).

Results: Best performance for discrimination of unfavourable outcome was demonstrated by the high risk group of the CAHP score with an AUC of 0.87 [95% CI 0.83-0.91], specificity of 97.1% [95% CI 93.8-100] and positive predictive value (PPV) of 96.3% [95% CI 92.2-100]. The high risk group of the MIRACLE₂ model, which is significantly easier to calculate, had an AUC of 0.81 [95% CI 0.76-0.86], specificity of 92.3% [95% CI 87.2-97.4] and PPV of 95.2% [95% CI 91.9-98.4].

Conclusion: The CAHP, MIRACLE₂, OHCA and TTM scores all perform comparably in a UK population to the original development and validation cohorts. All four scores outperform APACHE-II in a population of patients resuscitated from OHCA. CAHP and TTM perform best but are more complex to calculate than MIRACLE₂, which displays inferior performance.

Keywords: Cardiac arrest; mechanical circulatory support; neuro-prognostication; percutaneous coronary intervention; risk score.