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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Simple point of care risk stratification in acute coronary syndromes: the AMIS model
Organization Unit
  • D J Kurz
  • Abraham Bernstein
  • K Hunt
  • D Radovanovic
  • P Erne
  • Z Siudak
  • O Bertel
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Journal Title Heart
Publisher BMJ Publishing Group
Geographical Reach international
ISSN 1355-6037
Volume 95
Number 8
Page Range 662 - 668
Date 2009
Abstract Text Background: Early risk stratification is important in the management of patients with acute coronary syndromes (ACS). Objective: To develop a rapidly available risk stratification tool for use in all ACS. Design and methods: Application of modern data mining and machine learning algorithms to a derivation cohort of 7520 ACS patients included in the AMIS (Acute Myocardial Infarction in Switzerland)-Plus registry between 2001 and 2005; prospective model testing in two validation cohorts. Results: The most accurate prediction of in-hospital mortality was achieved with the “Averaged One-Dependence Estimators” (AODE) algorithm, with input of 7 variables available at first patient contact: Age, Killip class, systolic blood pressure, heart rate, pre-hospital cardio-pulmonary resuscitation, history of heart failure, history of cerebrovascular disease. The c-statistic for the derivation cohort (0.875) was essentially maintained in important subgroups, and calibration over five risk categories, ranging from <1% to >30% predicted mortality, was accurate. Results were validated prospectively against an independent AMIS-Plus cohort (n=2854, c-statistic 0.868) and the Krakow-Region ACS Registry (n=2635, c-statistic 0.842). The AMIS model significantly outperformed established “point-of-care” risk prediction tools in both validation cohorts. In comparison to a logistic regression-based model, the AODE-based model proved to be more robust when tested on the Krakow validation cohort (c-statistic 0.842 vs. 0.746). Accuracy of the AMIS model prediction was maintained at 12-months follow-up in an independent cohort (n=1972, c-statistic 0.877). Conclusions: The AMIS model is a reproducibly accurate point-of-care risk stratification tool for the complete range of ACS, based on variables available at first patient contact.
Digital Object Identifier 10.1136/hrt.2008.145904
PubMed ID 19066189
Other Identification Number merlin-id:222
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Additional Information Copyright: BMJ Publishing Group Ltd & British Cardiovascular Society