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Record W4413108330 · doi:10.1503/cmaj.250502

Pharmacotherapy for obesity management in adults: 2025 clinical practice guideline update

2025· review· en· W4413108330 on OpenAlexaffvenueabout
Sue D. Pedersen, Priya Manjoo, Satya Dash, Akshay Jain, Nicole Pearce, Megha Poddar

Bibliographic record

VenueCanadian Medical Association Journal · 2025
Typereview
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsMcMaster UniversityUniversity Health NetworkUniversity of TorontoUniversity of VictoriaUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsPharmacotherapyGuidelineMedicineObesityManagement of obesityWeight managementMEDLINEIntensive care medicinePhysical therapyInternal medicineWeight lossPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Pharmacotherapy is a key component of comprehensive obesity management, alongside behavioural therapy and metabolic and bariatric surgery. In this guideline, we update the pharmacotherapy recommendations in the 2020 Canadian clinical practice guideline on obesity in adults and in the 2022 pharmacotherapy for obesity management revision to provide current recommendations for clinicians on the efficacy, safety, and appropriate use of pharmacotherapy in the management of obesity in adults. METHODS: This guideline update follows the same methodology as the 2020 Canadian guideline on obesity in adults, adhering to the Appraisal of Guidelines for Research and Evaluation instrument and using the Shekelle framework to assess and grade evidence and to formulate recommendations. Building on the search conducted for the 2022 pharmacotherapy revision, we conducted a systematic literature review (search dates January 2022 to July 2024), supplemented by relevant trials published through May 2025, to identify studies assessing the efficacy of pharmacotherapy for weight management. We also conducted 13 targeted searches on the management of weight-related complications in 13 subpopulations with important adiposity-related health issues. We engaged primary care physicians, obesity medicine specialists, and people with lived experience of obesity to provide feedback on the recommendations. RECOMMENDATIONS: This update includes 6 new and 7 revised recommendations since the 2022 pharmacotherapy guideline revision (all 2020 pharmacotherapy recommendations are updated). Measures of central adiposity, in addition to ethnicity-specific body mass index and adiposity-related complications, should be used to guide the decision to initiate pharmacotherapy. Obesity pharmacotherapy should be used in conjunction with health behaviour changes and individualized based on a person's specific health needs and in keeping with their values and preferences. Recommendations support long-term use of obesity pharmacotherapy for sustained weight loss and maintenance of weight loss. We provide recommendations for use of specific obesity pharmacotherapies with proven benefit in specific subpopulations - atherosclerotic cardiovascular disease, heart failure with preserved ejection fraction, metabolic dysfunction-associated steatohepatitis, prediabetes, type 2 diabetes, obstructive sleep apnea, osteoarthritis - and for those with certain specific monogenic causes of obesity. We recommend against the use of compounded medications or medications other than those approved for weight loss in people with excess adiposity. INTERPRETATION: Pharmacotherapy in obesity facilitates clinically meaningful weight loss and important improvements in obesity-related health complications. Clinicians who treat people with obesity with or without obesity-related health complications should appropriately use pharmacotherapy as an integral part of their treatment paradigm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.031
GPT teacher head0.454
Teacher spread0.423 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations39
Published2025
Admission routes3
Has abstractyes

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