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Record W2624368590 · doi:10.1210/jc.2017-00351

Letter to the Editor: “Pediatric Obesity—Assessment, Treatment, and Prevention: An Endocrine Society Clinical Practice Guideline”

2017· letter· en· W2624368590 on OpenAlexaff
Geoff D.C. Ball, Arnaldo Perez, James Nobles, Nicholas D. Spence, Joseph A. Skelton

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2017
Typeletter
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsUniversity of Alberta
FundersNational Institutes of Health
KeywordsGuidelineClinical PracticeEndocrine systemMedicineIntensive care medicineFamily medicineEndocrinologyPathologyHormone

Abstract

fetched live from OpenAlex

We read with interest the recently published clinical practice guidelines for preventing and treating childhood obesity (1). The authors reported their evaluation of the quality of the evidence and an assessment of the strength of recommendations according to objective criteria across a diverse literature. In our view, however, this excellent and comprehensive report does not mention two relevant issues: attrition and enrollment. These issues are likely to be of concern for clinicians, administrators, and researchers because they can have a substantial impact on clinical care. Recent reviews showed that attrition from pediatric weight management is common, with estimates varying widely across studies (4% to 83%; median, 37%) (2, 3). It is apparent that a large number of children with obesity (and their families) choose to discontinue weight management prematurely, an occurrence that can lead to inefficient use of clinical resources, can be discouraging for families, and can lead to frustration for clinicians who deliver services and interventions. Attrition has become increasingly well characterized over recent years, which reinforces the importance of acquiring empirical data through randomized controlled trials and quality improvement initiatives as next steps. This will inform evidence-based strategies for retaining families so they achieve optimal benefits. Comparatively, less data are available regarding treatment enrollment, but contemporary analyses are instructive. Shaffer et al. (4) found that of the 4783 children referred to one multidisciplinary pediatric weight management clinic over a 4.4-year period, only 41.2% attended at least one appointment. In preliminary analyses of a provincial data set of ∼2000 children referred to three different multidisciplinary weight management clinics over a 3-year period in Alberta, Canada, approximately two-thirds of families never attended a clinic appointment (5). These two reports are noteworthy because even the “best” intervention for treating pediatric obesity offers no benefit to families unless they are ready, willing, and able to enroll in care. In light of data suggesting that a minimum of 25 hours of clinical contact is necessary to achieve clinically meaningful weight loss (6), there is clear value in helping children and their families to enroll and remain engaged in services and interventions for treating pediatric obesity and improving health-related outcomes. In our collective experience, only the vast minority of children receive this intervention dose. We are confident that these new guidelines will have a positive influence on the prevention and treatment of pediatric obesity; they represent a meaningful and important step forward from the preexisting guidelines. With increased research and clinical attention on the imperative to mitigate attrition and enhance enrollment, we are optimistic that services and interventions for preventing and treating pediatric obesity will better optimize outcomes for children and families. Disclosure Summary: The authors have nothing to disclose.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0220.018
Insufficient payload (model declined to judge)0.0060.006

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 head0.093
GPT teacher head0.494
Teacher spread0.401 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2017
Admission routes1
Has abstractyes

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