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Table 3_Algorithm-guided treatment for major depressive disorder versus treatment as usual: a systematic review.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Table_3_Algorithm-guided_treatment_for_major_depressive_disorder_versus_treatment_as_usual_a_systematic_review_docx/31849672
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IntroductionA substantial proportion of patients with major depressive disorder do not remit after the initial pharmacological treatment, and a major obstacle is that progression to subsequent treatment steps often occurs too slowly, highlighting the need for more structured and effective therapeutic strategies. Algorithm-guided treatments (AGTs) provide a systematic, stepwise framework for clinical decision-making, potentially improving acute treatment outcomes compared to treatment as usual (TAU). MethodsThis systematic review, conducted according to PRISMA 2020 guidelines, evaluated randomized controlled trials (RCTs) comparing AGTs to TAU in adult patients with major depressive disorder. Databases searched included PubMed, Scopus, Embase, PsychInfo, and the Cochrane Library up to June 2025. Trials investigating adults diagnosed with major depressive disorder, utilizing clinician-rated depression scales, and with a trial duration of four weeks or more were included. ResultsSeven RCTs met the criteria, encompassing over 3,500 participants. Most studies demonstrated superior outcomes in participants allocated to AGT compared to TAU, including significantly shorter time to remission, a higher proportion of patients achieving remission and response, as well as better adherence to treatment protocols. Some studies found marginal or nonsignificant differences between interventions in some of the outcomes, particularly those involving comorbid populations. DiscussionThese findings suggest that implementing structured, algorithm-based treatment strategies can improve the quality and efficacy of care for patients diagnosed with major depressive disorder, supporting their wider integration into clinical practice.
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2026-03-25
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