Major depressive disorder is a common psychiatric condition. Hospitalization is usually indicated for patients with more severe symptoms and severe functional impairment. Rehospitalization is known as the re-emergence of significant depressive symptoms. The purpose of the present study was to investigate the risk factors affecting time to rehospitalization. Rehospitalization status was monitored for all patients with major depressive disorder discharged from Kai-Suan Psychiatric Hospital between 1 January 2002 and 31 December 2003. Patients were followed up with respect to rehospitalization until 31 December 2004. The Kaplan-Meier method was used to calculate the median time to rehospitalization. Risk factors associated with rehospitalization were examined on Cox proportional hazards regression. Three hundred patients were recruited. Median time to readmission was 174 days (SD = 37). Comorbid alcohol abuse/dependence (hazard ratio [HR] = 1.841, 95% confidence interval [CI] = 1.229-2.758, P < 0.01), comorbid personality disorders (HR = 1.530, 95%CI = 1.053-2.223, P < 0.05), and the number of previous hospitalizations (HR = 1.121, 95%CI = 1.056-1.190, P < 0.001) were found to be predictors of the shorter time to rehospitalization over the 360-day study. Further research should be carried out to test risk factors in a prospective study, and to study the cost-effectiveness of interventions to reduce risk factors and rehospitalizations.

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Objectives: The main aim of this study is to investigate the capacity of a number of variables from four dimensions (clinical, psychosocial, cognitive and genetic domains) to predict the antidepressant treatment outcome, and combined the predictors in one integrate regression model with the aim to investigate which predictor contributed most. Methods: In a semi-naturalistic prospective cohort study with a total of 241 fully assessed MDD patients, decrease in HAM-D scores from baseline to after 6 weeks of treatment was used to measure the antidepressant treatment outcome. Results: The clinical and psychosocial model (R 2 =0.451) showed that HAM-D scores at baseline and MMPI-2 scale paranoia was the best clinical and psychosocial predictor of treatment outcome respectively. The cognitive model (R 2 =0.502) revealed that combination of better performance on TMT-B test and worse performance on TOH and WAIS-R Digit Backward testes could predict decline in HAM-D scores. The genetics analysis only found median of percent improvement in HAM-D scores in G-allele of GR gene BclI polymorphism carriers (72.2%) was significant lower than that in non-G allele carriers (80.1%). The integrate model showed that three predictors, combination of HAM-D scores at baseline, MMPI-2 scale paranoia and TMT-B test, explained 57.1% of the variance. Conclusion: Three markers, HAM-D scores at baseline, MMPI-2 scale paranoia and TMT-B test, might serve as predictor of antidepressant outcome in daily psychiatric practice.

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