Weight loss medications in Canada – a new frontier or a repeat of past mistakes?
Bibliographic record
Abstract
Sean Wharton,1,2 Jasmine Lee,1 Rebecca AG Christensen1 1The Wharton Medical Clinic, Hamilton, ON, Canada; 2School of Kinesiology and Health Science, York University, Toronto, ON, Canada Abstract: Current methods for the treatment of excess weight can involve healthy behavior changes, pharmacotherapy, and surgical interventions. Many individuals are able to lose some degree of weight through behavioral changes; however, they are often unable to maintain their weight loss long-term. This is in part due to physiological processes that cannot be addressed through behavioral changes alone. Bariatric surgery, which is the most successful treatment for excess weight to date, does result in physiological changes that can help with weight loss and weight maintenance. However, many patients either do not qualify or elect to not have this procedure. Fortunately, research has recently identified changes in neurochemicals (i.e., orexigens and anorexigens) that occur during weight loss and contribute to weight regain. The neurochemicals and hormones may be able to be targeted by medications to achieve greater and more sustained weight loss. Two medications are approved in adjunction to lifestyle management for weight loss in Canada: orlistat and liraglutide. Both medications are able to target physiological processes to help patients lose weight and maintain a greater amount of weight loss than with just behavioral modifications alone. Two other weight management medications, which also target specific physiological processes to aid in weight loss and its maintenance, a bupropion/naltrexone combination and lorcaserin, are currently pending approval in Canada. Nonetheless, there remain significant barriers for health care professionals to prescribe medications for weight loss, such as a lack of training and knowledge in the area of obesity. Until this has been addressed, and we begin treating obesity as we do other diseases, we are unlikely to combat the increasing trend of obesity in Canada and worldwide. Keywords: weight loss, pharmacological intervention, liraglutide, weight loss medication
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".