Effects of the selective serotonin reuptake inhibitors citalopram and escitalopram on glucolipid metabolism: a systematic review

Mian Li, Sugai Liang, Zhonglin Tan, Mengfei Ye, Yajing Dai, Mingzhe Zhao, JinQi Ding
2025-06-17

SCID:  54.1/zhag2q78
Objectives: Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) frequently co-occur, highlighting the need to understand the metabolic effects of antidepressants. This systematic review evaluated the impact of citalopram and escitalopram on glucose and lipid metabolism, focusing on glycemic control. Methods: A comprehensive search of PubMed, Embase, Web of Science, PsycINFO, the Cochrane Library and Google Scholar was conducted. Primary outcomes included changes in glycosylated hemoglobin (HbA1c) and fasting blood glucose (FBG). Secondary outcomes assessed lipid profiles (triglycerides, cholesterol, high-density lipoprotein, and low-density lipoprotein) and depressive symptom scales. Subgroup analyses were conducted to evaluate outcomes in patients with comorbid T2DM and MDD and those with MDD only. Results: Thirteen studies involving 502 participants met the inclusion criteria. Six randomized controlled trials, four prospective studies, one cohort trial, one single-arm trial and one three-arm trial. The findings suggest that both citalopram and escitalopram tend to reduce HbA1c and FBG levels. No significant effects on lipid profiles were observed across the included studies. Conclusion: Citalopram and escitalopram appear to exert beneficial effects on glycemic control, as evidenced by reductions in HbA1c and FBG. Further high-quality investigations are warranted to validate these findings and guide individualized treatment strategies. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024544963, identifier CRD42024544963.
Publication Details
Publication Date
2025-06-17
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Mian Li
Sugai Liang
Zhonglin Tan
Mengfei Ye
Yajing Dai
Mingzhe Zhao
JinQi Ding
Explore More Research
Use the citation graph to discover related papers and expand your research horizons.
Click any node to explore
Download PDF
100%