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Predictors of Treatment Response and Length of Stay for Inpatients with Major Depression

並列摘要


Background/Purpose: Depressive illness is highly recurrent, frequently chronic and associated with a high level of functional disability. Studies have shown that depression combined with anxiety is the most common reason for admission worldwide. This study aimed to examine the variables associated with treatment response or length of stay (LOS) among a group of inpatients with major depression. Methods: The attending psychiatrist rated severity of depression (using the Hamilton Rating Scale for Depression, HAM-D) of the patients (n = 67), and the patients were asked to complete several self-rating scales (including the Beck Depression Inventory, BDI) on admission. Three days before discharge, these assessments were repeated. Logistic regression models were used to examine the variables of remission status (defined by the HAM-D or the BDI) and LOS (dichotomized by a median of 25 days), respectively. Results: The remission rates of depression at discharge defined by the HAM-D (≤ 7) and the BDI (≤ 8) were 40% and 16%, respectively. Lower socioeconomic status and less clinical severity at admission were associated with clinicians' objective assessment of remission, while suicide attempt during this index episode was associated with patients' subjective remission. LOS of depressive inpatients was neither related to baseline severity nor to remission status at discharge. Patients with positive family history and more frequent hospitalization were associated with a hospital stay of longer than 25 days. Conclusion: There was no evidence to show that patients with a long hospital stay would gain treatment benefits over patients with short stay. This study provides evidence to support that a structured inpatient treatment plan might gain some economic benefits without compromising treatment efficacy. The admission of hospitalization repeaters should be managed optimally based on the considerations of treatment efficacy and its impact on longer hospital stay.

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