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Presentation and course of Type 2 diabetes in youth in a large multi‐ethnic city

2004· article· en· W2029395942 on OpenAlexaffabout
Vera Zdravković, Denis Daneman, Jill Hamilton

Bibliographic record

VenueDiabetic Medicine · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicinePresentation (obstetrics)Ethnic groupCourse (navigation)Type 2 diabetesDiabetes mellitusGerontologyEndocrinologySurgeryAnthropology

Abstract

fetched live from OpenAlex

AIM: To review the clinical experience of children and teens diagnosed with Type 2 diabetes (T2DM) at a paediatric hospital serving a large urban multi-ethnic population. METHODS: Retrospective chart review of patients with T2DM followed in the diabetes clinic at the Hospital for Sick Children (HSC) over an 8-year period. Patients who were included were younger than 18, referred at the onset of diabetes, and where presentation and/or clinical course was 'typical' of T2DM. RESULTS: Of 1020 children with diabetes followed at HSC, 4% were identified as having T2DM in 2002. There was a sixfold increase in new cases from 1994 to 2002. The mean age at diagnosis was 13.5 +/- 2.2 years (range 8.8-17.5) with a female-to-male ratio of 1.7. Most had a first- or second-degree relative with T2DM. There was an overrepresentation of children with T2DM from Asian and African Canadian ethnic groups relative to the regional population. The majority of teens were asymptomatic at presentation, with a smaller number in diabetic ketoacidosis (DKA) at diagnosis. Mean HbA1c at diagnosis was 10 +/- 3.4%. Approximately one half of patients were initially treated by diet and exercise with many requiring intensification of therapy over a short period of time. CONCLUSIONS: We report a similar increase in T2DM incidence and clinical presentation at HSC to other clinic reports in large North American urban centres. Of note is the high prevalence of children of South/South-East Asian descent.

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)0.000
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 score0.025
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.286
Teacher spread0.270 · 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

Citations70
Published2004
Admission routes2
Has abstractyes

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