A85 PATTERN OF SEMAGLUTIDE PRESCRIPTION IN A REAL-WORLD PATIENT COHORT
Bibliographic record
Abstract
Abstract Background The weight-loss effects of semaglutide has been studies in many randomized controlled trials. However, real-world data on its use is limited, particularly in the Canadian healthcare setting. Aims This study aims to explore the pattern of semaglutide prescription and associated outcomes in an academic family medicine practice in Canada. Methods We conducted a retrospective study of patients at the Sunnybrook Hospital family health team in Toronto, Ontario. Patients aged ≥18 years who were prescribed semaglutide between January 2018 and April 2024 were included. Baseline demographics and follow-up safety and efficacy measures were collected up to 16 months after semaglutide initiation. Results Of the 9930 rostered patients, 368 (3.71%) were prescribed semaglutide during the study period. The average age of patients who were prescribed semaglutide was 57.7±14.1 years and 63.3% were female. The average BMI was 36.6±7.84 kg/m2 and 189 patients (51.4%) had diabetes. The indication for semaglutide prescription was weight-loss for 206 patients (56.0%), diabetes for 118 patients (32.1%), and both weight-loss and diabetes for 39 patients (10.6%). We observed that since 2018, there has been a growing number of family physicians prescribing semaglutide compared to endocrinologists. In 2023 and 2024, over 80% of all semaglutide prescribers for our patients were family physicians, and endocrinologists were in the minority. Despite being prescribed semaglutide, 20 patients (5.4%) did not initiate the medication and 66 (17.9%) discontinued it within 16 months. Reasons for discontinuation included gastrointestinal adverse effects (26/66, 39.4%), difficulty in access (30/66, 54.5%), and perceived lack of response (6/66, 9.1%). Baseline and follow up weights were recorded for 211 patients (57.3%). Mean weight-loss was 7.36%. Mean weight-loss by 16 months was significantly greater in patients without diabetes (8.83% vs. 6.18%, p=0.003) and in females (8.30% vs. 5.90%, p=0.009), although there were more females without diabetes compared to males. The mean HbA1c at follow-up was 6.5±1.1%, which represents a significant reduction of 10.7% from baseline (p <0.001). Conclusions Our analysis of a real-world cohort of patients who used semaglutide demonstrated its wight-loss effects, particularly in those without diabetes. Understanding the demographics of patients using semaglutide and its potential effects will help inform future prescription practices. Funding Agencies None
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".