Efficacy of an Algorithm-Guided Treatment Compared With Treatment as Usual: A Randomized, Controlled Study of Inpatients With Depression

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Abstract

Objective:

Medication algorithms have been proposed as effective means to offer optimal treatment and improved outcome for patients with severe mental illness. This single-center prospective study compared the efficacy and effects on treatment prescriptions of an algorithm-guided treatment regimen with treatment as usual (TAU) in depressed inpatients.

Methods:

Depressed inpatient participants were randomized to an algorithm-guided standardized stepwise drug treatment regimen (SSTR, n = 74) or TAU (n = 74). The SSTR regimen included sleep deprivation, antidepressant monotherapy, lithium augmentation, monoamine oxidase inhibitor therapy, or electroconvulsive therapy guided by scores on the clinician-rated Bech-Rafaelsen Melancholia Scale. The primary outcome was time to remission (defined as a Bech-Rafaelsen Melancholia Scale score of ≤7). Secondary outcomes were remission rates, number of changes in treatment strategies (types), and the number of different prescribed medications over the treatment period.

Results:

Patients receiving SSTR had a significantly shorter time to remission (7.0 ± 0.9 weeks vs 12.3 ± 1.8 weeks for TAU). Compared with that in remitters in SSTR, the number of strategy changes was significantly higher in TAU remitters (3.0 ± 2.7 and 1.0 ± 1.5) and had more psychotropic medications (fix agents: 3.0 ± 1.5 and 1.9 ± 1.1; optional agents: 1.5 ± 1.0 and 0.9 ± 0.7). Although more patients dropped out of the SSTR group (33 of SSTR, 12 of TAU), the probability of remission tended to be higher in SSTR.

Conclusions:

Algorithm-guided treatment produces better outcomes and less frequent medication changes than TAU. A systematic, stepwise, measurement-based approach to the treatment of depressed inpatients is warranted.

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