Diabetic Ketoacidosis (DKA) at Diabetes Diagnosis in Children (0-18 years) in Ontario, Canada: A Population-Based Retrospective Cohort Study of Health Administrative Data
Bibliographic record
Abstract
IntroductionDiabetic ketoacidosis (DKA), a life-threatening complication of diabetes, is the leading cause of mortality and disability in children. The high cost of care for DKA and negative consequences of DKA on child’s health are known; however, the pediatric DKA trends in Ontario were not studied in the last fifteen years. Objectives and ApproachTo examine time trends of the prevalence of pediatric DKA at diabetes diagnosis and socio-demographic characteristics associated with the DKA risk (child’s sex; age; geographic region; rural residence; material deprivation and ethnic concentration) in Ontario, Canada. Person-level de-identified data from the provincial registry for all Ontario children (0-18 years) newly diagnosed with diabetes (type 1 and 2) in 2004-2012 was linked with records in the national discharge abstract database (CIHI DAD) at the Institute for Clinical and Evaluative Sciences (ICES). SAS software (v.9.3) was used for Poisson and logistic regressions. ResultsOf 10,617 children diagnosed with diabetes, 15.5% were diagnosed during a hospital admission for DKA. Prevalence of DKA at diagnosis did not change over the nine-year period (ptrend =0.99). There were statistically significant within-province regional differences in DKA prevalence at diabetes diagnosis, with the highest prevalence in South-Western Ontario (17.2%). Younger children (0-6 years and 7-12 years) were at higher DKA risk than 13-18 years old children (adjusted odds ratio (OR) 2.5 95% CI 2.2-2.8 and 2.1 95% CI 1.9-2.4). DKA at diabetes diagnosis was associated with material deprivation in young children (0-6 years)(OR 1.9 95% CI 1.4-2.5 for “most deprived” versus “least deprived”). In the older group (13-18 years), boys were at higher DKA risk than girls (OR 1.4 95% CI 1.1-1.7). Conclusion/ImplicationsPrevalence of pediatric DKA at diabetes diagnosis in Ontario is among the lowest in the world; however, higher DKA prevalence among children residing in some geographic regions or most deprived neighbourhoods of the province despite the universal access to government-funded health care warrants further research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".