Development of a predictive model of hospitalization in primary care patients with heart failure.

ABSTRACT:

Background

Heart failure (HF) is the leading cause of hospitalization in people over age 65. Predictive hospital admission models have been developed to help reduce the number of these patients.

Aim

To develop and internally validate a model to predict hospital admission in one-year for any non-programmed cause in heart failure patients receiving primary care treatment.

Design and setting

Cohort study, prospective. Patients treated in family medicine clinics.

Methods

Logistic regression analysis was used to estimate the association between the predictors and the outcome, i.e. unplanned hospitalization over a 12-month period. The predictive model was built in several steps. The initial examination included a set of 31 predictors. Bootstrapping was used for inter

SUBMITTER: Garcia-Olmos L 

PROVIDER: S-EPMC6697326 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature