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Record W2324839627 · doi:10.5414/cn107241

Are Canadian pediatric nephrology patients really overweight?

2012· article· en· W2324839627 on OpenAlexaffabout
Abeer Yasin, Andréanne Benidir, Guido Filler

Bibliographic record

VenueClinical Nephrology · 2012
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsChildren's Hospital of Western OntarioLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineNephrologyPercentileOverweightNational Health and Nutrition Examination SurveyBody mass indexInternal medicineKidney diseaseObesityPopulationStandard scorePediatricsDemographyEnvironmental health

Abstract

fetched live from OpenAlex

AIMS: To assess the influence of height age and short stature on BMI z-scores in children with chronic kidney disease (CKD) in view of the pandemic increase of childhood obesity. MATERIALS: Pediatric nephrology patients older than 2 years of age from 2 tertiary centers in Ontario and age- and gender matched controls from a local reference population. METHODS: We estimated height, weight and body mass index (BMI) z-scores of 705 nephrology patients (319 female) and 4,196 controls aged 2.01 - 19.92 years with chronological and height-adjusted age (corresponding age for a given height plotted on the 50th percentile). The National Health and Nutrition Examination Survey (NHANES III) was used for the z-score Estimation. RESULTS: Chronological age-based patient weight z-scores were significantly heavier than in the NHANES data (median weight z-score +0.29, BMI z-score +0.51; significantly non-zero), not significantly different from height-adjusted age-based BMI z-score (+0.51). The children with kidney problems were shorter (-0.10 SD) than controls. CONCLUSION: The proportion of overweight nephrology patients was similar to matched controls and BMI z-score diminished with worsening GFR.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.049
GPT teacher head0.347
Teacher spread0.298 · 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 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

Citations5
Published2012
Admission routes2
Has abstractyes

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