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Pre-clinical Model of Cardiac Donation after Circulatory Death
Published on: August 2, 2019
Derivation and Validation of the CREST Model for Very Early Prediction of Circulatory Etiology Death in Patients
Karen E Bascom1, John Dziodzio2, Samip Vasaiwala1
1Departments of Cardiology (K.E.B., S.V.).
Insights
A new CREST score predicts circulatory-etiology death risk in cardiac arrest survivors without ST-elevation myocardial infarction. This tool aids in rapid risk stratification and personalized treatment after resuscitation.
Area of Science:
- Cardiology
- Critical Care Medicine
- Predictive Analytics
Background:
- No existing tool quantifies immediate circulatory-etiology death (CED) risk post-resuscitation in non-ST-elevation myocardial infarction patients.
- Accurate risk assessment is crucial for timely, individualized treatment pathways.
Purpose of the Study:
- To develop and validate a prediction model for immediate CED risk assessment.
- To facilitate rapid triage and personalized management of cardiac arrest survivors.
Main Methods:
- Utilized the International Cardiac Arrest Registry (INTCAR) data from 44 centers.
- Employed logistic regression to identify factors associated with CED.
- Validated the model's performance using area under the curve and Hosmer-Lemeshow tests.
Main Results:
- The CREST model identified key predictors: coronary artery disease, nonshockable rhythm, low ejection fraction, shock on presentation, and prolonged ischemic time.
- The model demonstrated good performance in both derivation (AUC 0.73) and validation (AUC 0.68) cohorts.
- A simplified point-scoring system (CREST score) was developed for clinical application.
Conclusions:
- The CREST model effectively stratifies patients by CED risk immediately after resuscitation.
- This tool can aid in point-of-care risk estimation and improve triage for cardiac arrest survivors.
- The CREST score offers a practical approach to managing circulatory risk in this patient population.
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.
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