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BMC psychiatry · 2024

Efficacy of empagliflozin as adjunctive therapy to citalopram in major depressive disorder: a randomized double-blind, placebo-controlled clinical trial.

Рандомизированное исследованиеСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zandifar Atefeh, Panahi Maryam, Badrfam Rahim, Qorbani Mostafa

Аннотация

BACKGROUND: Major depressive disorder is one of the most common psychiatric disorders, which is associated with a high disease burden. Current treatments using antidepressants have limitations, so using medication with neuromodulating and anti-inflammatory properties alongside them could be helpful. In a clinical trial, we studied the effectiveness of empagliflozin, a blood sugar-lowering drug, as an adjunctive therapy to reduce the severity of depression symptoms.

METHODS: A number of outpatients with moderate to severe depression (Hamilton Depression Rating Scale (HDRS) > = 17) who were not under related medication or had not taken medication for at least the last two months, had an age range of 18-60 years and had written informed consent to enter the study (N = 90) were randomly divided into two groups receiving placebo or empagliflozin (10 mg daily) combined with citalopram (40 mg daily) based on permuted block randomization method in an 8-week randomized, double-blind, placebo-controlled clinical trial. They were evaluated using the HDRS in weeks 0, 4, and 8.

RESULTS: HDRS scores were equal to 28.42(± 3.83), 20.20(± 3.82), and 13.42(± 3.42) in the placebo group during weeks 0,4, and 8, respectively. These scores were 27.36(± 3.77), 13.76(± 1.40), and 7.00(± 1.13), respectively, for the group treated with empagliflozin. Compared to the control group, patients treated with empagliflozin using repeated-measures ANOVA showed greater improvement in reducing the severity of depression symptoms over time (p value = 0.0001).

CONCLUSIONS: Considering the promising findings in this clinical trial, further study of empagliflozin as adjunctive therapy in MDD with larger sample sizes and longer follow-ups is recommended.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты