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: Bascom Karen E. , Dziodzio John , Vasaiwala Samip , Mooney Michael , Patel Nainesh , McPherson John , McMullan Paul , Unger Barbara , Nielsen Niklas , Friberg Hans , Riker Richard R. , Kern Karl B. , Duarte Christine W. , Seder David B. , May Teresa , Sunde Kjetil , Rubertsson Sten , Smid Ondrej , Soreide Eldar , Hand Robert , Rundgren Malin , Valsson Felix , Sadaka Farid , Bekkers Bas , Wanscher Michael , Lindell Eva-Lotta , Guldbrand Pehr , Torstensson Anders , Dybkowska Krystyna , Israelsson Johan , Skram Ulrik , Guzowski Michelle , Hopf Hans-Bernd , Persson Stefan , Chang Ira , Samuelsson Line , Oddby Eva , Savolainen Kristina , Zätterman Richard , Rodriguez Daniel , Mayer Stephan , Födisch Markus , Oscarsson Beata , Scheer Håkan , Sarbinowski Roman , Hyddmark Ulf , Deye Nicolas , Lindbom Anna , Armani Claudia , Forsberg Sune , Ericsson Anders B. 
Published: October 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<30% (OR, 2.11; CI, 1.32–3.37;
P
=0.002), shock at presentation (OR, 2.27; CI, 1.42–3.62; P<0.001), and ischemic time >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 >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.