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Published on: December 2, 2015
Diagnosis-Specific Clinical and Longitudinal Predictors of Suicide Attempts in Early-Onset Mood Disorders
Yaerim Nam1,2, Jaegwon Jeong1,2, Sojeong Kim3
1Department of Psychiatry, Korea University College of Medicine, Seoul, Republic of Korea.
Objective:
To identify diagnosis-specific clinical and longitudinal predictors of suicide attempts in early-onset mood disorders, comparing major depressive disorder (MDD), bipolar I disorder (BD-I), and bipolar II disorder (BD-II) within a single cohort to inform targeted risk stratification.
Methods:
We analyzed 430 patients aged under 35 years (a proxy for early-onset) with MDD, BD-I, or BD-II from a prospective South Korean cohort. Diagnoses were based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and the Mini International Neuropsychiatric Interview. Lifetime and follow-up suicide attempts and suicidal ideation (Beck Scale for Suicide Ideation, SSI-beck) were assessed using structured interviews and standardized scales. Logistic regression examined predictors of lifetime suicide attempts, and Cox proportional hazards models evaluated baseline predictors of time to first suicide attempt over approximately 60 weeks of follow-up.
Results:
At baseline, 40.5% of patients reported a lifetime suicide attempt, and 62 patients attempted suicide during follow-up. In the total patients, earlier age at onset, longer untreated duration, alcohol use problems, psychiatric family history, and higher SSI-beck scores were associated with lifetime suicide attempts. Diagnosis-specific analyses showed distinct patterns. Prospectively, depressive severity and SSI-beck scores predicted first suicide attempts, with alcohol use and impulsivity additionally important in MDD.
Conclusion:
Suicidal ideation and depressive severity are key transdiagnostic predictors of suicide attempts in early-onset mood disorders, while alcohol use, impulsivity, psychiatric family history, and illness burden mark diagnosis-specific risk profiles guiding tailored monitoring and interventions.
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