Citation

Seegulam VL, Szentkúti P, Rosellini AJ, Horváth-Puhó E, Jiang T, Lash TL, Sørensen HT, Gradus JL. Gen. Hosp. Psychiatry 2022; 79: 76-117.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.genhosppsych.2022.09.004

PMID

36375345

Abstract

While suicide risk following psychiatric hospitalization has been studied extensively, risk following hospitalization for physical illness is less well understood. We used random forests to examine risk factors for suicide in the year following physical illness hospitalization in Denmark. In this case-cohort study, suicide cases were all individuals who died by suicide within one year of a hospitalization for a physical illness (n = 4563) and the comparison subcohort was a 5% random sample of individuals living in Denmark on January 1, 1995 who had a hospitalization for a physical illness between January 1, 1995 and December 31, 2015 (n = 177,664). We used random forests to examine identify the most important predictors of suicide stratified by sex. For women, the top 10 most important variables for random forest prediction were all related to psychiatric diagnoses. For men, many physical health conditions also appeared important to suicide prediction. Among the top 10 variables in the variable importance plot for men were influenza, injuries to the head, nervous system surgeries, and cerebrovascular diseases. Suicide prediction after a physical illness hospitalization requires comprehensive consideration of different and multiple factors for each sex.

Language: en

Keywords

Suicide; Machine learning; Case-cohort study; Physical illness hospitalization; Post discharge suicide; Suicide prediction