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Record W2891756143 · doi:10.1111/obr.12748

Continuous cardiometabolic risk score definitions in early childhood: a scoping review

2018· review· en· W2891756143 on OpenAlexafffund
Margret Kamel, Brendan T. Smith, Gita Wahi, Sarah Carsley, Catherine S. Birken, Laura N. Anderson

Bibliographic record

VenueObesity Reviews · 2018
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsHospital for Sick ChildrenPublic Health OntarioSickKids FoundationUniversity of TorontoMcMaster UniversityInstitute for Clinical Evaluative SciencesImpact
FundersCanadian Institutes of Health Research
KeywordsMedicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiometabolic risk (CMR) in young children has been measured using various approaches, including a continuous summary score that incorporates components such as adiposity, lipids, metabolic factors and blood pressure. OBJECTIVES: The objective of this study was to comprehensively review definitions of continuous CMR scores in children <10 years of age. METHODS: A scoping review was conducted using a systematic search of four scientific databases up to June 2016. Inclusion criteria were children <10 years of age and report of a continuous CMR score. RESULTS: Ninety-one articles were included. Most studies were published from 2007 to 2016 (96%). Nearly all continuous CMR scores (90%) were calculated using the sum or the mean of z-scores, and many articles age-standardized and sex-standardized components within their own population. The mean number of variables included in the risk scores was 5 with a range of 3-11. The most commonly included score components were waist circumference (52%), triglycerides (87%), high-density lipoprotein cholesterol (67%), glucose (43%) and systolic blood pressure (52%). IMPORTANCE: Continuous CMR scores are emerging frequently in the child health literature and are calculated using numerous methods with diverse components. This heterogeneity limits comparability across studies. A harmonized definition of CMR in childhood is needed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0140.004
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.006

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 head0.088
GPT teacher head0.349
Teacher spread0.261 · 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 designSystematic review
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

Citations65
Published2018
Admission routes2
Has abstractyes

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