Derivation and validation of the CREST model for very early prediction of circulatory etiology death in patients without ST-segment-elevation myocardial infarction after cardiac arrest.

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Critical Care, MMCRI

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BACKGROUND: No practical tool quantitates the risk of circulatory-etiology death (CED) immediately after successful cardiopulmonary resuscitation in patients without ST-segment-elevation myocardial infarction. We developed and validated a prediction model to rapidly determine that risk and facilitate triage to individualized treatment pathways.

METHODS: With the use of INTCAR (International Cardiac Arrest Registry), an 87-question data set representing 44 centers in the United States and Europe, patients were classified as having had CED or a combined end point of neurological-etiology death or survival. Demographics and clinical factors were modeled in a derivation cohort, and backward stepwise logistic regression was used to identify factors independently associated with CED. We demonstrated model performance using area under the curve and the Hosmer-Lemeshow test in the derivation and validation cohorts, and assigned a simplified point-scoring system.

RESULTS: Among 638 patients in the derivation cohort, 121 (18.9%) had CED. The final model included preexisting coronary artery disease (odds ratio [OR], 2.86; confidence interval [CI], 1.83-4.49;

CONCLUSIONS: The CREST model stratified patients immediately after resuscitation according to risk of a circulatory-etiology death. The tool may allow for estimation of circulatory risk and improve the triage of survivors of cardiac arrest without ST-segment-elevation myocardial infarction at the point of care.



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