Prediction of medical admissions after psychiatric inpatient hospitalization in bipolar disorder: a retrospective cohort study.

ABSTRACT:

Objective

Bipolar Disorder (BD) is a severe mental illness associated with high rates of general medical comorbidity, reduced life expectancy, and premature mortality. Although BD has been associated with high medical hospitalization, the factors that contribute to this risk remain largely unexplored. We used baseline medical and psychiatric records to develop a supervised machine learning model to predict general medical admissions after discharge from psychiatric hospitalization.

Methods

In this retrospective three-year cohort study of 71 patients diagnosed with BD (mean age=52.19 years, females=56.33%), lasso regression models combining medical and psychiatric records, as well as those using them separately, were fitted and their predictive power was estimated using a lea

SUBMITTER: Miola A 

PROVIDER: S-EPMC11406175 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature