Score helps predict 30-day readmission or death from heart failure
Researchers in Australia have developed a predictive score for the likelihood of 30-day readmission or death from heart failure that includes determinants such as echocardiography, mental health, cognitive function and individual socioeconomic status that were not incorporated in previous models.
Lead researcher Quan L. Huynh, BMed, PhD, of the University of Tasmania in Hobart, Australia, and colleagues published their results online in JAMA Cardiology on April 20.
“The model developed in the study has excellent internal and external validation and calibration, and might be used to predict both short-term mortality and readmission for [heart failure] with very good discrimination,” they wrote. “Further validation of the model in a larger sample of HF patients that can be generalized to other health systems is needed.”
To develop the score, the researchers analyzed data on 430 patients with heart failure who enrolled in a prospective study throughout Australia. They validated the score in a group of 161 patients with heart failure from the two largest public hospitals in Tasmania, Australia. Within 30 days of discharge, 27 percent of patients in the validation cohort died or were readmitted.
The median age was 74 years old in the prospective study and 78 years old in the validation cohort. In addition, 64 percent and 55 percent of patients, respectively, were males.
The researchers used logistic regression to determine the variables that best predicted readmission or death. They included the predictor in the model if it contributed by 0.01 or more units in the area under the curve.
The final prediction model included whether a patient lived alone; had life-threatening arrhythmia; were discharged during winter; heart rate measurement; New York Heart Association heart failure classification; Montreal Cognitive Assessment score; Patient Health Questionnaire score; right atrial pressure; left atrial volume index; blood urea nitrogen; and serum albumin.
Within 30 days of discharge, 9 percent of patients in the study died and 21 percent were readmitted. The final prediction model had very good discrimination when predicting 30-day death (C statistic, 0.83) or 30-day readmission (C statistic, 0.80), according to the researchers. They added that the final prediction model’s discriminatory power was much higher than that of the claims-based model. Further, the internal (C statistic, 0.82) and external (C statistic, 0.80) validation values showed stability and generalizability to the final prediction model.
“The model calibration across different risk categories showed a close association of predicted and observed outcomes,” the researchers wrote.
Executive Editor
Tim Casey joined TriMed Media Group in 2015 as Executive Editor. For the previous four years, he worked as an editor and writer for HMP Communications, primarily focused on covering managed care issues and reporting from medical and health care conferences. He was also a staff reporter at the Sacramento Bee for more than four years covering professional, college and high school sports. He earned his undergraduate degree in psychology from the University of Notre Dame and his MBA degree from Georgetown University.