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
Authors: Karen E. Bascom, John Dziodzio, Samip Vasaiwala, Michael Mooney, Nainesh Patel, John McPherson, Paul McMullan, Barbara Unger, Niklas Nielsen, Hans Friberg, Richard R. Riker, Karl B. Kern, Christine W. Duarte, David B. Seder, Teresa May, Kjetil Sunde, Sten Rubertsson, Ondrej Smid, Eldar Soreide, Robert Hand, Malin Rundgren, Felix Valsson, Farid Sadaka, Bas Bekkers, Michael Wanscher, Eva-Lotta Lindell, Pehr Guldbrand, Anders Torstensson, Krystyna Dybkowska, Johan Israelsson, Ulrik Skram, Michelle Guzowski, Hans-Bernd Hopf, Stefan Persson, Ira Chang, Line Samuelsson, Eva Oddby, Kristina Savolainen, Richard Zätterman, Daniel Rodriguez, Stephan Mayer, Markus Födisch, Beata Oscarsson, Håkan Scheer, Roman Sarbinowski, Ulf Hyddmark, Nicolas Deye, Anna Lindbom, Claudia Armani, Sune Forsberg, Anders B. Ericsson
Journal: Circulation (2017)

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; P ≤0.001), nonshockable rhythm (OR, 1.75; CI, 1.10–2.77; P=0.017), initial ejection fraction&lt;30% (OR, 2.11; CI, 1.32–3.37; P =0.002), shock at presentation (OR, 2.27; CI, 1.42–3.62; P&lt;0.001), and ischemic time &gt;25 minutes (OR, 1.42; CI, 0.90–2.23; P=0.13). The derivation model area under the curve was 0.73, and Hosmer-Lemeshow test P=0.47. Outcomes were similar in the 318-patient validation cohort (area under the curve 0.68, Hosmer-Lemeshow test P=0.41). When assigned a point for each associated factor in the derivation model, the average predicted versus observed probability of CED with a CREST score (coronary artery disease, initial heart rhythm, low ejection fraction, shock at the time of admission, and ischemic time &gt;25 minutes) of 0 to 5 was: 7.1% versus 10.2%, 9.5% versus 11%, 22.5% versus 19.6%, 32.4% versus 29.6%, 38.5% versus 30%, and 55.7% versus 50%. 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.