The following is a summary of “A novel cardiac arrest severity score for the early prediction of hypoxic-ischemic brain injury and in-hospital death,” published in the April 2023 issue of Emergency Medicine by Bang, et al.

Out-of-hospital cardiac arrest (OHCA) is a life-threatening condition that often leads to poor outcomes despite post-cardiac arrest care. Early on, predicting the likelihood of hypoxic-ischemic brain injury (HIBI) and in-hospital death (IHD) could help healthcare professionals tailor treatment and improve patient outcomes. Researchers derived and validated a novel scoring system for a study to predict HIBI and IHD in OHCA patients.

They conducted a retrospective analysis of data collected from the Korean Hypothermia Network prospective registry between 2015 and 2018. 

Patients without neuro prognostication data were excluded, and the remaining patients were randomly divided into derivation and validation cohorts. HIBI was defined as at least one neuro prognostication predicting a poor outcome, while IHD referred to all deaths regardless of cause. Using the derivation cohort, they conducted stepwise multivariate logistic regression for HIBI and IHD scores and assessed model performance. They then classified patients into four categories based on their scores and analyzed associations between these categories and cerebral performance categories (CPCs) at hospital discharge. Finally, they validated their models in an internal validation cohort.

Of 1,373 patients, 240 were excluded, and 1,133 were randomized into the derivation (n = 754) and validation cohorts (n = 379). In the derivation cohort, the researchers selected seven and eight predictors for HIBI (score range 0-8) and IHD (score range 0-11) scores, respectively, and found that the area under the curve (AUC) was 0.85 (95% CI 0.82-0.87) and 0.80 (95% CI 0.77-0.82) for HIBI and IHD, respectively. Applying the optimum cutoff values of ≥6 points for HIBI and ≥7 points for IHD, they classified patients into four categories: Category 1 (n = 424), HIBI (−)/IHD (−); Category 2 (n = 100), HIBI (−)/IHD (+); Category 3 (n = 21), HIBI (+)/IHD (−); and Category 4 (n = 209), HIBI (+)/IHD (+). In addition, they found that 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.

The study provided a novel approach to assessing illness severity in OHCA patients by predicting the likelihood of HIBI and IHD. Although further external prospective studies were needed, risk stratification based on these scores could help healthcare professionals provide appropriate treatment to OHCA patients, ultimately improving their outcomes.

Reference: sciencedirect.com/science/article/abs/pii/S0735675723000050