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Record W4409404236 · doi:10.1503/cmaj.241456

Managing obesity in children: a clinical practice guideline

2025· article· en· W4409404236 on OpenAlexafffundvenue
Geoff D.C. Ball, Roah Merdad, Catherine S. Birken, Tamara R. Cohen, Stasia Hadjiyannakis, Jill Hamilton, Mélanie Henderson, John Lammey, Katherine M. Morrison, Sarah A. Moore, Aislin R. Mushquash, Ian Patton, Nicole Pearce, Joshua Ramjist, Tracy Lebel, Brian W. Timmons, Annick Buchholz, Jennifer Cantwell, Jennifer Cooper, Julius Erdstein, Donna Fitzpatrick‐Lewis, Dawn Hatanaka, Patrice Lindsay, Tasneem Sajwani, Meghan Sebastianski, Diana Sherifali, Julie St‐Pierre, Muhammad Usman Ali, Jessica Wijesundera, Angela S. Alberga, Christine Ausman, Trisha C Baluyot, Emily Burke, Kara Dadgostar, Bronwyn Delacruz, Elizabeth Dettmer, Maegan Dymarski, Zahra Esmaeilinezhad, Ilona Hale, Soren Harnois‐Leblanc, Josephine Ho, Nicole D. Gehring, Marsha Kucera, Jacob C. Langer, Amy C. McPherson, Leen Naji, Krista Oei, Grace O’Malley, Angelica M Rigsby, Gita Wahi, Ian Zenlea, Bradley C. Johnston

Bibliographic record

VenueCanadian Medical Association Journal · 2025
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Toronto
FundersObesity CanadaAlberta Health Services
KeywordsGuidelineMedicineObesityComputer scienceData scienceFamily medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity is a complex, chronic, stigmatized disease whereby abnormal or excess body fat may impair health or increase the risk of medical complications, and can reduce quality of life and shorten lifespan in children and families. We developed this guideline to provide evidence-based recommendations on options for managing pediatric obesity that support shared decision-making among children living with obesity, their families, and their health care providers. METHODS: We followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We used the Guidelines International Network principles to manage competing interests. Caregivers, health care providers, and people living with obesity participated throughout the guideline development process, which optimized relevance. We surveyed end users (caregivers, health care providers) to prioritize health outcomes, completed 3 scoping reviews (2 on minimal important difference estimates; 1 on clinical assessment), performed 1 systematic review to characterize families' values and preferences, and conducted 3 systematic reviews and meta-analyses to examine the benefits and harms of behavioural and psychological, pharmacologic, and surgical interventions for managing obesity in children. Guideline panellists developed recommendations focused on an individualized approach to care by using the GRADE evidence-to-decision framework, incorporating values and preferences of children living with obesity and their caregivers. RECOMMENDATIONS: Our guideline includes 10 recommendations and 9 good practice statements for managing obesity in children. Managing pediatric obesity should be guided by a comprehensive child and family assessment based on our good practice statements. Behavioural and psychological interventions, particularly multicomponent interventions (strong recommendation, very low to moderate certainty), should form the foundation of care, with tailored therapy and support using shared decision-making based on the potential benefits, harms, certainty of evidence, and values and preferences of children and families. Pharmacologic and surgical interventions should be considered (conditional recommendation, low to moderate certainty) as therapeutic options based on availability, feasibility, and acceptability, and guided by shared decision-making between health care providers and families. INTERPRETATION: This guideline will support children, families, and health care providers to have informed discussions about the balance of benefits and harms for available obesity management interventions to support value- and preference-sensitive decision-making.

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)0.027
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.032
GPT teacher head0.474
Teacher spread0.442 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations42
Published2025
Admission routes3
Has abstractyes

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