Predicting Neurologically Intact Survival for Advanced Age Adults After Successful Resuscitation of Out-of-Hospital Cardiac Arrest

Author Department

Emergency Medicine

Document Type

Article, Peer-reviewed

Publication Date

9-2023

Abstract

We sought to predict survival to hospital discharge with favorable neurologic outcome for advanced age adults (≥65 years) after successful resuscitation of non-traumatic out-of-hospital cardiac arrest (OHCA). A retrospective observational cohort analysis was performed using the national Cardiac Arrest Registry to Enhance Survival database from January 1, 2013 to December 31, 2021. All nontraumatic OHCA occurring in advanced age adults who survived to hospital admission were included. The primary outcome was survival with favorable neurologic outcome defined as a cerebral performance category score of 1 or 2 at hospital discharge. Multivariable logistic regression including patient variables (age category, gender, co-morbidities) and OHCA characteristics (location, rhythm category, witnessed status, and who initiated cardiopulmonary resuscitation) were used to predict hospital outcome. 83,574 patients met study inclusion criteria with 19,298 (23.1%) surviving with favorable neurologic outcome. The median age was 75 years (interquartile range 69 to 82 years), 58.9% were male, and a majority of events occurred at home (67.3%). Age was found to have a linear, negative association with outcome. Survival with cerebral performance category 1 or 2 ranged from 28.8% in those between the age of 65 to 69 years (n = 23,161) and 13.7% for those age >90 years (n = 4,666). The regression model produced outcome probabilities ranging from 2.6% to 80.8% with a cross-validated AUROC of 0.742 (95% confidence interval 0.738 to 0.746) and a Brier score of 0.151. In conclusion, a simple model with basic patient and OHCA characteristics can predict hospital outcomes in advanced age adults with good discrimination and calibration.

Keywords: advanced age; out-of-hospital cardiac arrest; outcomes.

PMID

37757519

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