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Record W2150532926 · doi:10.1177/0009922808315214

Impact of Increasing Adiposity in Hyperlipidemic Children

2008· article· en· W2150532926 on OpenAlex
Saul Miller, Cedric Manlhiot, Nita Chahal, Geraldine Cullen-Dean, Louise Bannister, Brian W. McCrindle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Pediatrics · 2008
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineBody mass indexHyperlipidemiaInternal medicineOverweightTriglycerideLipid profileCholesterolEndocrinologyObesityHigh-density lipoproteinDiabetes mellitus

Abstract

fetched live from OpenAlex

Despite lifestyle management, children with high-risk hyperlipidemias may become overweight, and this may further adversely impact their lipid profile. Regression analysis was used to determine changes over time in adiposity and their association with lipid profiles and other risk factors for hyperlipidemic children followed in a lipid disorder clinic. 184 patients were included. Median age at presentation was 7 years (2-17 years), and median duration of follow-up was 9 years (5-20 years). Mean initial total cholesterol was 6.9+/-1.6 mmol/L, low-density lipoproteins were 5.2+/-1.7 mmol/L, high-density lipoproteins were 1.2 +/- 0.4 mmol/L, triglycerides were 1.1+/-0.8 mmol/L, and body mass index z score was +0.4+/-1.0. A significant increase in body mass index z score (+0.032/year, P< .001) was observed. There was an associated significant increase in total cholesterol and triglyceride levels and decrease in high-density lipoprotein levels over time. Worsening adiposity is prevalent in hyperlipidemic children and adversely affects their lipid profiles and cardiovascular risk.

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.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.372
Teacher spread0.323 · 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