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Record W2167410533

Feasibility of an interdisciplinary program for obesity management in Canada.

2012· article· en· W2167410533 on OpenAlexaffabout
Sean Wharton, Sarah VanderLelie, Arya M. Sharma, Saaqshi Sharma, Jennifer L. Kuk

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsHamilton Medical Research Group
Fundersnot available
KeywordsMedicineWeight lossBody mass indexObesityMedical recordAuditWeight managementRetrospective cohort studyBody weightPhysical therapyPediatricsSurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the feasibility of a medically supervised, publicly funded interdisciplinary program for obesity management in a Canadian setting. DESIGN: Retrospective chart audit using electronic medical records. SETTING: Wharton Medical Clinic in Hamilton and Burlington, Ont. PARTICIPANTS: A total of 2739 consenting patients attending the interdisciplinary obesity-management program at Wharton Medical Clinic. MAIN OUTCOME MEASURES: Three- and 6-month weight changes and factors affecting weight loss. RESULTS: The 1085 patients attending the clinic for at least 3 months (mean [SD] of 8.1 [6.1] visits and 5.4 [4.7] months) lost a mean (SD) of 4.2 (7.1) kg or 3.5% (6.8%) of their initial body weight, with 32% and 9% of these patients attaining weight reductions of 5% or greater and 10% or greater, respectively. The 289 patients attending the clinic for 6 months or more (mean [SD] of 13.2 [9.7] visits and 10.5 [6.9] months) lost a mean (SD) of 5.4 (10.6) kg or 4.3% (9.2%) of their initial body weight, with 47% and 17% attaining reductions of 5% or greater and 10% or greater, respectively. Visit frequency was positively associated with weight loss independent of age, sex, body mass index, and treatment duration. CONCLUSION: Preliminary data support the short-term effectiveness and clinical utility of this publicly funded program. Using this interdisciplinary model, approximately half of patients were able to attain clinically significant weight loss.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.132
GPT teacher head0.475
Teacher spread0.343 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations26
Published2012
Admission routes2
Has abstractyes

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