Simple point-of-care risk stratification in acute coronary syndromes: the AMIS model

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 seven variables available at first patient contact: age, Killip class, systolic blood pressure, heart rate, pre-hospital cardiopulmonary 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-month 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.

[1]  F. Van de Werf,et al.  Intervention in acute coronary syndromes: do patients undergo intervention on the basis of their risk characteristics? The Global Registry of Acute Coronary Events (GRACE) , 2005, Heart.

[2]  David A Morrow,et al.  A simple risk index for rapid initial triage of patients with ST-elevation myocardial infarction: an InTIME II substudy , 2001, The Lancet.

[3]  A. Peel,et al.  A CORONARY PROGNOSTIC INDEX FOR GRADING THE SEVERITY OF INFARCTION , 1962, British heart journal.

[4]  E. Antman,et al.  Application of the Thrombolysis in Myocardial Infarction risk index in non-ST-segment elevation myocardial infarction: evaluation of patients in the National Registry of Myocardial Infarction. , 2006, Journal of the American College of Cardiology.

[5]  D. Fuchs,et al.  Predicting Mortality in Patients With ST-Elevation Myocardial Infarction Treated With Primary Percutaneous Coronary Intervention (PAMI Risk Score) , 2004 .

[6]  E. Antman,et al.  Validation of the thrombolysis in myocardial infarction (TIMI) risk score for unstable angina pectoris and non-ST-elevation myocardial infarction in the TIMI III registry. , 2002, The American journal of cardiology.

[7]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[8]  Z. Siudak,et al.  More aggressive pharmacological treatment may improve clinical outcome in patients with non-ST-elevation acute coronary syndromes treated conservatively , 2007, Coronary artery disease.

[9]  Á. Avezum,et al.  Predictors of hospital mortality in the global registry of acute coronary events. , 2003, Archives of internal medicine.

[10]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.

[11]  E W Steyerberg,et al.  Predictors of outcome in patients with acute coronary syndromes without persistent ST-segment elevation. Results from an international trial of 9461 patients. The PURSUIT Investigators. , 2000, Circulation.

[12]  David W. Aha,et al.  A Comparative Evaluation of Sequential Feature Selection Algorithms , 1995, AISTATS.

[13]  Z. Siudak,et al.  Management of myocardial infarction with ST-segment elevation in district hospitals without catheterisation laboratory--Acute Coronary Syndromes Registry of Małopolska 2002-2003. , 2006, Kardiologia polska.

[14]  G. Taffet,et al.  In-hospital cardiopulmonary resuscitation. , 1988, JAMA.

[15]  Geoffrey I. Webb,et al.  Averaged One-Dependence Estimators: Preliminary Results , 2002, AusDM.

[16]  J Col,et al.  Predictors of 30-day mortality in the era of reperfusion for acute myocardial infarction. Results from an international trial of 41,021 patients. GUSTO-I Investigators. , 1995, Circulation.

[17]  Deepak L. Bhatt,et al.  Utilization of early invasive management strategies for high-risk patients with non-ST-segment elevation acute coronary syndromes: results from the CRUSADE Quality Improvement Initiative. , 2005, JAMA.

[18]  E. Antman,et al.  Application of the TIMI risk score for ST-elevation MI in the National Registry of Myocardial Infarction 3. , 2001, JAMA.

[19]  B. McNeil,et al.  Using admission characteristics to predict short-term mortality from myocardial infarction in elderly patients. Results from the Cooperative Cardiovascular Project. , 1996, JAMA.

[20]  E. Antman,et al.  TIMI Risk Score for ST-Elevation Myocardial Infarction: A Convenient, Bedside, Clinical Score for Risk Assessment at Presentation: An Intravenous nPA for Treatment of Infarcting Myocardium Early II Trial Substudy , 2000, Circulation.

[21]  William Wijns,et al.  [Guidelines for the diagnosis and treatment of non-ST-segment elevation acute coronary syndromes]. , 2007, Revista portuguesa de cardiologia : orgao oficial da Sociedade Portuguesa de Cardiologia = Portuguese journal of cardiology : an official journal of the Portuguese Society of Cardiology.

[22]  P. Erne,et al.  Trends in reperfusion therapy of ST segment elevation myocardial infarction in Switzerland: six year results from a nationwide registry , 2005, Heart.

[23]  A. Albert,et al.  Short‐term risk stratification at admission based on simple clinical data in acute myocardial infarction , 1989, The American journal of cardiology.

[24]  B. Gersh,et al.  Prediction of mortality after primary percutaneous coronary intervention for acute myocardial infarction: the CADILLAC risk score. , 2005, Journal of the American College of Cardiology.

[25]  Doug Fisher,et al.  Learning from Data: Artificial Intelligence and Statistics V , 1996 .

[26]  P. Brandt,et al.  A new coronary prognostic index. , 1969, American heart journal.

[27]  Angelo Branzi,et al.  Guidelines for the diagnosis and treatment of non-ST-segment elevation acute coronary syndromes: the task force for the diagnosis and treatment of non-ST-segment elevation acute coronary syndromes of the European Society of Cardiology. , 2007, European heart journal.

[28]  J. Basile,et al.  Systolic blood pressure , 2002, BMJ : British Medical Journal.

[29]  L. Pierard,et al.  Short-term risk stratification at admission based on simple clinical data in acute myocardial infarction. , 1988 .

[30]  G. Stone,et al.  Predicting mortality in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention (PAMI risk score). , 2004, The American journal of cardiology.

[31]  E. Antman,et al.  The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. , 2000, JAMA.

[32]  J. Gore,et al.  Early assessment and in-hospital management of patients with acute myocardial infarction at increased risk for adverse outcomes: a nationwide perspective of current clinical practice. The National Registry of Myocardial Infarction (NRMI-2) Participants. , 1998, American heart journal.

[33]  D. Jacobs,et al.  PREDICT: A simple risk score for clinical severity and long-term prognosis after hospitalization for acute myocardial infarction or unstable angina: the Minnesota heart survey. , 1999, Circulation.

[34]  Geoffrey I. Webb,et al.  Not So Naive Bayes: Aggregating One-Dependence Estimators , 2005, Machine Learning.