1. Predicting 30-Day Hospital Readmissions in Acute Myocardial Infarction: The AMI "READMITS" (Renal Function, Elevated Brain Natriuretic Peptide, Age, Diabetes Mellitus, Nonmale Sex, Intervention with Timely Percutaneous Coronary Intervention, and Low Systolic Blood Pressure) Score.
- Author
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Nguyen, Oanh Kieu, Makam, Anil N, Clark, Christopher, Zhang, Song, Das, Sandeep R, and Halm, Ethan A
- Subjects
Humans ,Myocardial Infarction ,Diabetes Mellitus ,Natriuretic Peptide ,Brain ,Glomerular Filtration Rate ,Prognosis ,Patient Readmission ,Risk Factors ,Retrospective Studies ,Follow-Up Studies ,Blood Pressure ,Time Factors ,Aged ,Middle Aged ,Female ,Male ,Percutaneous Coronary Intervention ,acute myocardial infarction ,health services research ,hospital performance ,prediction ,readmission ,Cardiovascular ,Clinical Research ,Heart Disease - Coronary Heart Disease ,Prevention ,Patient Safety ,Heart Disease ,Cardiorespiratory Medicine and Haematology - Abstract
BACKGROUND:Readmissions after hospitalization for acute myocardial infarction (AMI) are common. However, the few currently available AMI readmission risk prediction models have poor-to-modest predictive ability and are not readily actionable in real time. We sought to develop an actionable and accurate AMI readmission risk prediction model to identify high-risk patients as early as possible during hospitalization. METHODS AND RESULTS:We used electronic health record data from consecutive AMI hospitalizations from 6 hospitals in north Texas from 2009 to 2010 to derive and validate models predicting all-cause nonelective 30-day readmissions, using stepwise backward selection and 5-fold cross-validation. Of 826 patients hospitalized with AMI, 13% had a 30-day readmission. The first-day AMI model (the AMI "READMITS" score) included 7 predictors: renal function, elevated brain natriuretic peptide, age, diabetes mellitus, nonmale sex, intervention with timely percutaneous coronary intervention, and low systolic blood pressure, had an optimism-corrected C-statistic of 0.73 (95% confidence interval, 0.71-0.74) and was well calibrated. The full-stay AMI model, which included 3 additional predictors (use of intravenous diuretics, anemia on discharge, and discharge to postacute care), had an optimism-corrected C-statistic of 0.75 (95% confidence interval, 0.74-0.76) with minimally improved net reclassification and calibration. Both AMI models outperformed corresponding multicondition readmission models. CONCLUSIONS:The parsimonious AMI READMITS score enables early prospective identification of high-risk AMI patients for targeted readmissions reduction interventions within the first 24 hours of hospitalization. A full-stay AMI readmission model only modestly outperformed the AMI READMITS score in terms of discrimination, but surprisingly did not meaningfully improve reclassification.
- Published
- 2018