Development of prognostic models for predicting 90-day neurological function and mortality after cardiac arrest - 13/04/24
, Yi Chen, MD,PhD a, b, ⁎ 
Abstract |
Background |
The survivors of cardiac arrest experienced vary extent of hypoxic ischemic brain injury causing mortality and long-term neurologic disability. However, there is still a need to develop robust and reliable prognostic models that can accurately predict these outcomes.
Objectives |
To establish reliable models for predicting 90-day neurological function and mortality in adult ICU patients recovering from cardiac arrest.
Methods |
We enrolled patients who had recovered from cardiac arrest at Binhaiwan Central Hospital of Dongguan, from January 2018 to July 2021. The study's primary outcome was 90-day neurological function, assessed and divided into two categories using the Cerebral Performance Category (CPC) scale: either good (CPC 1–2) or poor (CPC 3–5). The secondary outcome was 90-day mortality. We analyzed the relationships between risk factors and outcomes individually. A total of four models were developed: two multivariable logistic regression models (models 1 and 2) for predicting neurological function, and two Cox regression models (models 3 and 4) for predicting mortality. Models 2 and 4 included new neurological biomarkers as predictor variables, while models 1 and 3 excluded. We evaluated calibration, discrimination, clinical utility, and relative performance to establish superiority between the models.
Results |
Model 1 incorporates variables such as gender, site of cardiopulmonary resuscitation (CPR), total CPR time, and acute physiology and chronic health evaluation II (APACHE II) score, while model 2 includes gender, site of CPR, APACHE II score, and serum level of ubiquitin carboxy-terminal hydrolase L1 (UCH-L1). Model 2 outperforms model 1, showcasing a superior area under the receiver operating characteristic curve (AUC) of 0.97 compared to 0.83. Additionally, model 2 exhibits improved accuracy, sensitivity, and specificity. The decision curve analysis confirms the net benefit of model 2. Similarly, models 3 and 4 are designed to predict 90-day mortality. Model 3 incorporates the variables such as site of CPR, total CPR time, and APACHE II score, while model 4 includes APACHE II score, total CPR time, and serum level of UCH-L1. Model 4 outperforms model 3, showcasing an AUC of 0.926 and a C-index of 0.830. The clinical decision curve analysis also confirms the net benefit of model 4.
Conclusions |
By integrating new neurological biomarkers, we have successfully developed enhanced models that can predict 90-day neurological function and mortality outcomes more accurately.
Le texte complet de cet article est disponible en PDF.Keywords : Cardiac arrest, Risk factors, New neurological biomarkers, Prognostic models, Cerebral performance category, Mortality
Plan
Vol 79
P. 172-182 - mai 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
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