The real‐world relationship between naltrexone/bupropion treatment and weight loss in Canada: A retrospective chart review
Bibliographic record
Abstract
Summary This study examined the change in weight at 6 months of naltrexone/bupropion (NB), a combination pharmacological therapy for weight management, in real‐world practice in Canada. The study was conducted through an observational, retrospective, single‐arm chart review of adult patients who attended the Wharton Medical Clinic in Ontario, Canada, between 2018 and 2021. The patients had a body mass index ≥30 or ≥27 kg/m2 with at least one weight‐related comorbidity. They were prescribed NB, titrated from 1 (8 mg/90 mg) to 4 tablets daily, along with lifestyle modification. Approximately 52% of 468 participants completed 6 months of treatment and 48.7% titrated to the maximum dose of 4 tablets daily. Participants were mainly female, with mean age of 49.5 years and BMI 38.4 kg/m2. After 6 months, participants lost a mean of 4.23 kg (95% confidence interval [CI] −4.99, −3.47) or 4.05% (CI −4.77, −3.34) of body weight, with 42.5% losing at least 5% of their body weight and 15.5% losing at least 10%. The most frequent adverse events were nausea (5.7%), constipation (5.7%), and headache (2.5%). Participants also experienced decreased appetite (14.7%), decreased cravings (13.9%), decreased hunger (9.4%) and felt full sooner (2.5%), which are changes likely to result in sustained healthy food choices and improved quality of life. The 6‐month NB treatment adjunct to lifestyle modification in a real‐world population resulted in clinically significant weight loss.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".