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
© 2017 American Heart Association, Inc..
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.
| Errataetall: |
CommentIn: Circulation. 2018 Jan 16;137(3):283-285. - PMID 29335287 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2018 |
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| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:137 |
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| Enthalten in: |
Circulation - 137(2018), 3 vom: 16. Jan., Seite 273-282 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Bascom, Karen E [VerfasserIn] |
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| Links: |
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| Themen: |
Cardiomyopathies |
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| Anmerkungen: |
Date Completed 09.04.2019 Date Revised 10.12.2019 published: Print-Electronic CommentIn: Circulation. 2018 Jan 16;137(3):283-285. - PMID 29335287 Citation Status MEDLINE |
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| doi: |
10.1161/CIRCULATIONAHA.116.024332 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM277423880 |
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| 100 | 1 | |a Bascom, Karen E |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a 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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| 500 | |a Date Completed 09.04.2019 | ||
| 500 | |a Date Revised 10.12.2019 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a CommentIn: Circulation. 2018 Jan 16;137(3):283-285. - PMID 29335287 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2017 American Heart Association, Inc. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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% | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Validation Study | |
| 650 | 4 | |a cardiomyopathies | |
| 650 | 4 | |a cardiopulmonary resuscitation | |
| 650 | 4 | |a forecasting | |
| 650 | 4 | |a heart arrest | |
| 650 | 4 | |a prognosis | |
| 650 | 4 | |a shock | |
| 700 | 1 | |a Dziodzio, John |e verfasserin |4 aut | |
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| 700 | 1 | |a Patel, Nainesh |e verfasserin |4 aut | |
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| 700 | 1 | |a Riker, Richard R |e verfasserin |4 aut | |
| 700 | 1 | |a Kern, Karl B |e verfasserin |4 aut | |
| 700 | 1 | |a Duarte, Christine W |e verfasserin |4 aut | |
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| 700 | 0 | |a International Cardiac Arrest Registry (INTCAR) |e verfasserin |4 aut | |
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| 700 | 1 | |a Rubertsson, Sten |e investigator |4 oth | |
| 700 | 1 | |a Smid, Ondrej |e investigator |4 oth | |
| 700 | 1 | |a Soreide, Eldar |e investigator |4 oth | |
| 700 | 1 | |a Hand, Robert |e investigator |4 oth | |
| 700 | 1 | |a Rundgren, Malin |e investigator |4 oth | |
| 700 | 1 | |a Valsson, Felix |e investigator |4 oth | |
| 700 | 1 | |a Sadaka, Farid |e investigator |4 oth | |
| 700 | 1 | |a Bekkers, Bas |e investigator |4 oth | |
| 700 | 1 | |a Wanscher, Michael |e investigator |4 oth | |
| 700 | 1 | |a Lindell, Eva-Lotta |e investigator |4 oth | |
| 700 | 1 | |a Guldbrand, Pehr |e investigator |4 oth | |
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| 700 | 1 | |a Dybkowska, Krystyna |e investigator |4 oth | |
| 700 | 1 | |a Israelsson, Johan |e investigator |4 oth | |
| 700 | 1 | |a Skram, Ulrik |e investigator |4 oth | |
| 700 | 1 | |a Guzowski, Michelle |e investigator |4 oth | |
| 700 | 1 | |a Hopf, Hans-Bernd |e investigator |4 oth | |
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| 700 | 1 | |a Chang, Ira |e investigator |4 oth | |
| 700 | 1 | |a Samuelsson, Line |e investigator |4 oth | |
| 700 | 1 | |a Oddby, Eva |e investigator |4 oth | |
| 700 | 1 | |a Savolainen, Kristina |e investigator |4 oth | |
| 700 | 1 | |a Zätterman, Richard |e investigator |4 oth | |
| 700 | 1 | |a Rodriguez, Daniel |e investigator |4 oth | |
| 700 | 1 | |a Mayer, Stephan |e investigator |4 oth | |
| 700 | 1 | |a Födisch, Markus |e investigator |4 oth | |
| 700 | 1 | |a Oscarsson, Beata |e investigator |4 oth | |
| 700 | 1 | |a Scheer, Håkan |e investigator |4 oth | |
| 700 | 1 | |a Sarbinowski, Roman |e investigator |4 oth | |
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| 700 | 1 | |a Lindbom, Anna |e investigator |4 oth | |
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| 700 | 1 | |a Forsberg, Sune |e investigator |4 oth | |
| 700 | 1 | |a Ericsson, Anders B |e investigator |4 oth | |
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