External validation of the CREST model to predict early circulatory-etiology death after out-of-hospital cardiac arrest without initial ST-segment elevation myocardial infarction
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Background: The CREST model is a prediction model, quantitating the risk of circulatory-etiology death (CED) after cardiac arrest based on variables available at hospital admission, and intend to guide the triage of comatose patients without ST-segment-elevation myocardial infarction after successful cardiopulmonary resuscitation. This study assessed performance of the CREST model in the Target Temperature Management (TTM) trial cohort. Methods: We retrospectively analyzed data from resuscitated out-of-hospital cardiac arrest (OHCA) patients in the TTM-trial. Demographics, clinical characteristics, and CREST variables (history of coronary artery disease, initial heart rhythm, initial ejection fraction, shock at admission and ischemic time > 25 min) were assessed in univariate and multivariable analysis. The primary outcome was CED. The discriminatory power of the logistic regression model was assessed using the C-statistic and goodness of fit was tested according to Hosmer-Lemeshow. Results: Among 329 patients eligible for final analysis, 71 (22%) had CED. History of ischemic heart disease, previous arrhythmia, older age, initial non-shockable rhythm, shock at admission, ischemic time > 25 min and severe left ventricular dysfunction were variables associated with CED in univariate analysis. CREST variables were entered into a logistic regression model and the area under the curve for the model was 0.73 with adequate calibration according to Hosmer-Lemeshow test (p = 0.602). Conclusions: The CREST model had good validity and a discrimination capability for predicting circulatory-etiology death after resuscitation from cardiac arrest without ST-segment elevation myocardial infarction. Application of this model could help to triage high-risk patients for transfer to specialized cardiac centers.
Original language | English |
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Article number | 311 |
Journal | BMC Cardiovascular Disorders |
Volume | 23 |
Issue number | 1 |
ISSN | 1471-2261 |
DOIs | |
Publication status | Published - 2023 |
Bibliographical note
Funding Information:
The Target Temperature Management trial and the present study were funded by independent research grants from the following nonprofit or governmental agencies: Swedish Heart–Lung Foundation (Grant No 20090275); AFA-Insurance Foundation (Grant No 100001); the Swedish Research Council (Grant Nos 134281, 296161, 286321); Regional research support, Region Skane (Sweden), Governmental funding of clinical research within the Swedish National Health Service (Grant Nos M2010/1837, M2010/1641, 353301); Skane University Hospital, Sweden; TrygFonden, Denmark; Thelma Zoegas Foundation, Krapperup Foundation, Thure Carlsson Foundation, Hans-Gabriel and Alice Trolle-Wachtmeister Foundation for Medical Research and European Clinical Research Infrastructures Network.
Publisher Copyright:
© 2023, The Author(s).
- Cardiac arrest, Prediction model, Resuscitation
Research areas
ID: 372695328