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Record W2948859911 · doi:10.2337/db19-234-lb

234-LB: Incidence Trends of Diabetic Ketoacidosis at and after Diagnosis of Type 1 Diabetes in British Columbia, Canada

2019· article· en· W2948859911 on OpenAlexaboutno aff
Kung‐Ting Kao, Nazrul Islam, Danya A. Fox, Shazhan Amed

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetic ketoacidosisMedicineType 1 diabetesPoisson regressionIncidence (geometry)PediatricsRate ratioDiabetes mellitusPopulationCohortInternal medicineEndocrinologyEnvironmental health

Abstract

fetched live from OpenAlex

Objective: Diabetic ketoacidosis (DKA) is a preventable complication in youth with type 1 diabetes (T1D). This study aimed to estimate the incidence trend of DKA at T1D diagnosis (DKA-AT, defined as DKA within 14 days of T1D diagnosis) and after T1D diagnosis (DKA-AFTER, defined as DKA after 14 days of T1D diagnosis) from 2002 to 2012 in British Columbia, Canada. Methods: We used a previously described population-based cohort of individuals diagnosed with T1D at <20 years of age. DKA episodes were identified using ICD9/10 codes (250.1X/E101X). Incidence rate ratio (IRR) was estimated using Poisson regression and trends in DKA rates were examined using Joinpoint regression analyses. Results: 2615 incident cases of T1D were identified between 2002 and 2012, of which 847 (32.4%) were diagnosed with DKA-AT. 52% were male. The rates of DKA-AT by year ranged between 24.1% (2008) and 37.3% (2006). No sex differences were observed. The IRR was 2.0 (95% CI: 1.6, 2.5; p<0.001) for those diagnosed with T1D at 0-4 years compared to those diagnosed at 15-19 years old, after adjusting for the trend by fiscal year. In the same period, 1886 episodes of DKA-AFTER were identified with a consistent increase from 5.3% (2002) to 9.5% (2012). The IRR for DKA-AFTER in children 0-4 years old at diabetes diagnosis was 9.13 (95% CI: 7.73, 10.77; p<0.001). After adjusting for the increasing trend by fiscal year, females had higher rates of DKA-AFTER than males (IRR 1.45, 95% CI: 1.33, 1.59; p<0.001). The average annual percent change for DKA-AFTER was 4.91% (95% CI: 2.69, 7.18; p<0.001). Conclusions: DKA-AT incidence remained unchanged while the incidence of DKA-AFTER increased over time, with the greatest burden in those diagnosed at a younger age. Targeted interventions are needed to raise public awareness to prevent DKA-AT and to educate patients and families in preventing DKA-AFTER. Disclosure K. Kao: None. N. Islam: None. D.A. Fox: None. S. Amed: None.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.002
GPT teacher head0.175
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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