A novel cardiac arrest severity score for the early prediction of hypoxic-ischemic brain injury and in-hospital death
Out-of-hospital cardiac arrest (OHCA) outcomes are unsatisfactory despite postcardiac arrest care. Early prediction of prognoses might help stratify patients and provide tailored therapy. In this study, we derived and validated a novel scoring system to predict hypoxic-ischemic brain injury (HIBI) a...
Saved in:
Published in | The American journal of emergency medicine Vol. 66; pp. 22 - 30 |
---|---|
Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.04.2023
Elsevier Limited |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Out-of-hospital cardiac arrest (OHCA) outcomes are unsatisfactory despite postcardiac arrest care. Early prediction of prognoses might help stratify patients and provide tailored therapy. In this study, we derived and validated a novel scoring system to predict hypoxic-ischemic brain injury (HIBI) and in-hospital death (IHD).
We retrospectively analyzed Korean Hypothermia Network prospective registry data collected from in Korea between 2015 and 2018. Patients without neuroprognostication data were excluded, and the remaining patients were randomly divided into derivation and validation cohorts. HIBI was defined when at least one prognostication predicted a poor outcome. IHD meant all deaths regardless of cause. In the derivation cohort, stepwise multivariate logistic regression was conducted for the HIBI and IHD scores, and model performance was assessed. We then classified the patients into four categories and analyzed the associations between the categories and cerebral performance categories (CPCs) at hospital discharge. Finally, we validated our models in an internal validation cohort.
Among 1373 patients, 240 were excluded, and 1133 were randomized into the derivation (n = 754) and validation cohorts (n = 379). In the derivation cohort, 7 and 8 predictors were selected for HIBI (0–8) and IHD scores (0−11), respectively, and the area under the curves (AUC) were 0.85 (95% CI 0.82–0.87) and 0.80 (95% CI 0.77–0.82), respectively. Applying optimum cutoff values of ≥6 points for HIBI and ≥7 points for IHD, the patients were classified as follows: HIBI (−)/IHD (−), Category 1 (n = 424); HIBI (−)/IHD (+), Category 2 (n = 100); HIBI (+)/IHD (−), Category 3 (n = 21); and HIBI (+)/IHD (+), Category 4 (n = 209). The CPCs at discharge were significantly different in each category (p < 0.001). In the validation cohort, the model showed moderate discrimination (AUC 0.83, 95% CI 0.79–0.87 for HIBI and AUC 0.77, 95% CI 0.72–0.81 for IHD) with good calibration. Each category of the validation cohort showed a significant difference in discharge outcomes (p < 0.001) and a similar trend to the derivation cohort.
We presented a novel approach for assessing illness severity after OHCA. Although external prospective studies are warranted, risk stratification for HIBI and IHD could help provide OHCA patients with appropriate treatment. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
ISSN: | 0735-6757 1532-8171 |
DOI: | 10.1016/j.ajem.2023.01.003 |