Predicting functional impairment in euthymic patients with mood disorder: A 5-year follow-up.

Major Depressive Disorder and Bipolar Disorder are psychiatric disorders associated with psychosocial impairment. Despite clinical improvement, functional complaints usually remain, mainly impairing occupational and cognitive performance. The aim of this study was to use machine learning techniques to predict functional impairment in patients with mood disorders. For that, analyzes were performed using a population-based cohort study. Participants diagnosed with a mood disorder at baseline and reassessed were considered (n = 282). Random forest (RF) with previous recursive feature selection and LASSO algorithms were applied to a training set with imputed data by bagged trees resulting in two main models. Following recursive feature selection, 25 variables were retained. The RF model had the best performance compared to LASSO. The most important variables in predicting functional impairment were sexual abuse, severity of depressive, anxiety, and somatic symptoms, physical neglect, emotional abuse, and physical abuse. The model demonstrated acceptable performance to predict functional impairment. However, our sample is composed of young participants and the model may not generalize to older individuals with mood disorders. More studies are needed in this direction. The presented calculator has clinical, sociodemographic, and environmental data, demonstrating that it is possible to use such information to predict functional performance.

Incidence and Risk Factors for Suicide Attempts in Patients Diagnosed with Major Depressive Disorder.

OBJECTIVE: This study seeks to investigate the cumulative incidence and risk factors of suicide attempts in an outpatient sample of adults diagnosed with major depressive disorder (MDD). MATERIALS AND METHODS: This is a longitudinal study with 377 patients aged between 18 and 60 years. Those were diagnosed with MDD with no history of suicide attempts when they sought care at the Mental Health Outpatient Clinic of the Catholic University of Pelotas and evaluated again 3 years after. Participants were evaluated with the Mini International Neuropsychiatric Interview (MINI Plus) and answered instruments of clinical investigation and a sociodemographic questionnaire. RESULTS: The cumulative incidence of suicide attempts in the sample was 10.1%. Youths aged up to 29 years (OR 2.23; 95% CI 1.13 to 4.64), with low schooling (OR 2.35; 95% CI 1.15 to 4.80), who suffered intense physical abuse during childhood (OR 2.77; 95% CI 1.31 to 5.84) and were at prior suicide risk (OR 3.39; 95% CI 1.56 to 7.37) were more likely to attempt suicide. CONCLUSION: The findings of this study may help health professionals identify depressed patients at greater risk for a first suicide attempt, supporting clinical decision and therapeutic planning.