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Medications and conditions associated with weight loss in patients prescribed semaglutide based on real-world data.

Obesity (Silver Spring) · 2023

Last updated 2026-05-28

In a study of 3,555 patients prescribed semaglutide, individuals lost an average of 4.44% of their starting weight over time, with men losing 3.66% and women losing 5.08%. Patients with diabetes lost less weight, while those with prediabetes or taking the medication linaclotide lost more. The weight loss observed was smaller than in previous clinical trials.

AI summary of the abstract below.

JournalObesity (Silver Spring), 2023
Citations22
Relative citation ratio2.68
NIH percentile81
Molecules semaglutide
Conditions studied Obesity

Abstract

OBJECTIVE: Approved by the Food and Drug Administration (FDA) in 2017 for diabetes and in 2021 for weight loss, semaglutide has seen widespread use among individuals who aim to lose weight. The aim of this study was to evaluate weight loss and the influence of clinical factors on semaglutide patients in real-world clinical practice. METHODS: Using data from 10 health systems within the Greater Plains Collaborative (a PCORnet Clinical Research Network), nearly 4000 clinical factors encompassing demographic, diagnosis, and prescription information were extracted for semaglutide patients. A gradient-boosting, machine-learning classifier was developed for weight-loss prediction and identification of the most impactful factors via SHapley Additive exPlanations (SHAP) value extrapolation. RESULTS: A total of 3555 eligible patients (539 of whom were observed 52 weeks following exposure) from March 2017 to April 2022 were studied. On average, individuals lost 4.44% (male individuals, 3.66%; female individuals, 5.08%) of their initial weight. History of diabetes mellitus diagnosis was associated with less weight loss, whereas prediabetes and linaclotide use were associated with more pronounced weight loss. CONCLUSIONS: Weight loss in patients prescribed semaglutide from real-world evidence was strong but attenuated compared with previous clinical trials. Machine-learning analysis of electronic health record data identified factors that warrant further research and consideration when tailoring weight-loss therapy.

Verbatim abstract via PubMed 37593896 ↗

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