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Record W2002553811 · doi:10.1515/jpem.2009.22.11.1051

A Novel, Non-Invasive 13C-Glucose Breath Test to Estimate Insulin Resistance in Obese Prepubertal Children

2009· article· en· W2002553811 on OpenAlexafffund
Mary Jetha, U. Nzekwu, R LEWANCZUK, Geoff D.C. Ball

Bibliographic record

VenueJournal of Pediatric Endocrinology and Metabolism · 2009
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineInsulin resistanceInsulinInternal medicineQuantitative insulin sensitivity check indexGold standard (test)Homeostatic model assessmentEndocrinologyDiabetes mellitusArea under the curveIngestionInsulin sensitivity

Abstract

fetched live from OpenAlex

Insulin resistance (IR) is an important risk factor for the development of type 2 diabetes mellitus in obese boys and girls. Because needle-associated fear and anxiety are common in children, non-invasive methods to determine IR are desirable. Our objective in this cross-sectional study of obese prepubertal children (n = 39) was to compare estimates of IR using a novel, non-invasive technique (13C-glucose breath test) with common indices of IR derived from an oral glucose tolerance test (OGTT). For the 13C-glucose breath test, samples were collected before and 90 minutes after ingestion of 25 mg 13C-labelled glucose. For the OGTT, glucose and insulin samples were collected at 0, 15, 30, 45, 60, 90 and 120 minutes. The homeostatic model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), insulin area-under-the-curve (AUC), and sum-of-insulin were calculated as indices of IR. Pearson correlations revealed significant, but moderate, associations between the 13C-glucose breath test and fasting insulin (r = -0.50; p < 0.01), 2-hour insulin (r = plots showed acceptable levels of agreement between indices of IR. In obese prepubertal children, the 13C-glucose breath test can provide a proxy estimate of IR when gold-standard techniques are either unavailable or impractical.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.081
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.009
GPT teacher head0.291
Teacher spread0.282 · 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 teacher head, 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

Citations18
Published2009
Admission routes2
Has abstractyes

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