New Score Allows Early Prediction of AMI Readmission Risk

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A new “AMI READMITS” score—based on renal function, diabetes, and low blood pressure, among other factors in the first 24 hours in the hospital—identifies patients at high risk of readmission after acute myocardial infarction, reports a study in the open-access Journal of the American Heart Association.

Using data from consecutive AMI hospitalizations to six diverse Texas hospitals in 2009–2010, the researchers sought to develop a pragmatic model to predict the risk of all-cause, nonelective hospital readmission within 30 days. The model was derived using data on 826 patients, 13% of whom were readmitted within 30 days. Two separate

A new “AMI READMITS” score—based on renal function, diabetes, and low blood pressure, among other factors in the first 24 hours in the hospital—identifies patients at high risk of readmission after acute myocardial infarction, reports a study in the open-access Journal of the American Heart Association.

Using data from consecutive AMI hospitalizations to six diverse Texas hospitals in 2009–2010, the researchers sought to develop a pragmatic model to predict the risk of all-cause, nonelective hospital readmission within 30 days. The model was derived using data on 826 patients, 13% of whom were readmitted within 30 days. Two separate AMI-specific models were developed and evaluated: a “first-day” model using only data from the first 24 hours in the hospital and a “full-stay” model including data from the full hospital stay.

The first-day model, called AMI READMITS, consisted of seven predictors: renal function (serum creatinine greater than 2 mg/dL), elevated brain natriuretic peptide, age, history of diabetes, nonmale sex, absence of timely percutaneous coronary intervention; and systolic blood pressure less than 100 mm Hg. This score provided good discrimination, C-statistic 0.75, and identified a broad range of risk categories, with average risks of 2.1% to 41.1% by decile. About one-third of patients classified as high risk (AMI READMITS score 20 or higher) had 30-day readmission, compared to 2% of those classified as low risk (score 13 or lower).

The full-stay model added three further predictors: intravenous diuretic use, anemia at discharge, and discharge to postacute care. However, it provided minimal net reclassification improvement and calibration. Both models appeared to have better performance compared to other models.

Readmission after AMI is a common problem, but current models have modest predictive value and do not provide readily actionable data to reduce risk. The new AMI READMITS score is a parsimonious model that includes clinically relevant risk factors and provides actionable data to identify patients at high risk of readmission during their first 24 hours in the hospital. The researchers note, “[C]linical severity measures directly related to the AMI (shock, heart strain or failure, renal dysfunction) and timely percutaneous coronary intervention were strong predictors of readmission risk” [Nguyen OK, et al. 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. J Am Heart Assoc 2018; 7:e008882. DOI: 10.1161/JAHA.118.008882].

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