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Record W4282935512 · doi:10.1136/bmjopen-2021-058857

Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children

2022· article· en· W4282935512 on OpenAlexafffundabout
Lisa Kakinami, Anna Smyrnova, Gilles Paradis, Angelo Tremblay, Mélanie Henderson

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité LavalMcGill UniversityUniversité de MontréalConcordia University
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéCanadian Society of Endocrinology and MetabolismConcordia UniversityUniversité de MontréalUniversité LavalMcGill UniversityHeart and Stroke Foundation of CanadaAstraZeneca
KeywordsMedicinePercentileBlood pressureCohortObesityInternal medicineReceiver operating characteristicBody mass indexInsulin resistanceMetabolic syndromeCohort studyProspective cohort studyDemography

Abstract

fetched live from OpenAlex

Objectives Severe obesity (SO) prevalence varies between reference curve-based definitions (WHO: ≥99th percentile, Centers for Disease Control and Prevention (CDC): >1.2×95th percentile). Whether SO definitions differentially predict cardiometabolic disease risk is critical for proper clinical care and management but is unknown. Design Prospective cohort study Setting SO definitions were applied at baseline (2005–2008, M age =9.6 years, n=548), and outcomes (fasting lipids, glucose, homoeostatic model assessment (HOMA-IR) and blood pressure) were assessed at first follow-up (F1: 2008–2011, M age =11.6 years) and second follow-up (2015–2017, M age =16.8 years) of the Quebec Adipose and Lifestyle Investigation in Youth cohort in Montreal, Quebec. Participants Respondents were youth who had at least one biological parent with obesity. Primary outcome measures Unfavourable cardiometabolic levels of fasting blood glucose (≥6.1 mmol/L), insulin resistance (HOMA-IR index ≥2.0), high-density lipoprotein <1.03 mmol/L, low-density lipoprotein ≥2.6 mmol/L and triglycerides > 1.24 mmol/L. Unfavourable blood pressure was defined as ≥90th percentile for age-adjusted, sex-adjusted and height-adjusted systolic or diastolic blood pressure. Analysis Area under the receiver operating characteristic curve (AUC) and McFadden psuedo R 2 for predicting F1 or F2 unfavourable cardiometabolic levels from baseline SO definitions were calculated. Agreement was assessed with kappas. Results Baseline SO prevalence differed (WHO: 18%, CDC: 6.7%). AUCs ranged from 0.52 to 0.77, with fair agreement (kappa=37%–55%). WHO-SO AUCs for detecting unfavourable HOMA-IR (AUC>0.67) and high-density lipoprotein (AUC>0.59) at F1 were statistically superior than CDC-SO (AUC>0.59 and 0.53, respectively; p<0.05). Only HOMA-IR and the presence of more than three risk factors had acceptable model fit. WHO-SO was not more predictive than WHO-obesity, but CDC-SO was statistically inferior to CDC-obesity. Conclusion WHO-SO is statistically superior at predicting cardiometabolic risk than CDC-SO. However, as most AUCs were generally uninformative, and obesity definitions were the same if not better than SO, the improvement may not be clinically meaningful.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.206
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.362
Teacher spread0.304 · 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 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

Citations2
Published2022
Admission routes3
Has abstractyes

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