Risk of ketoacidosis in children at the time of diabetes mellitus diagnosis by primary caregiver status: a population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Diabetic ketoacidosis is the leading cause of death among children with type 1 diabetes mellitus, and is an avoidable complication at first-time diagnosis of diabetes. Because having a usual provider of primary care is important in improving health outcomes for children, we tested the association between having a usual provider of care and risk of diabetic ketoacidosis at onset of diabetes. METHODS: Using linked health administrative data for the province of Quebec, we conducted a population-based retrospective cohort study of children aged 1-17 years in whom diabetes was diagnosed from 2006 to 2015. We estimated adjusted risk ratios (RRs) for an episode of diabetic ketoacidosis at the time of diabetes diagnosis in relation to usual provider of care (family physician, pediatrician or none) using Poisson regression models with robust error variance. RESULTS: We identified 3704 new cases of diabetes in Quebec children from 2006 to 2015. Of these, 996 (26.9%) presented with diabetic ketoacidosis. A decreased risk of this complication was associated with having a usual provider of care; the association was stronger with increasing age, reaching statistical significance among those aged 12-17 years. Within this age group, those who had a family physician or a pediatrician were 31% less likely (adjusted RR 0.69, 95% confidence interval [CI] 0.56-0.85) or 38% less likely (adjusted RR 0.62, 95% CI 0.45-0.86), respectively, to present with diabetic ketoacidosis, relative to those without a usual provider of care. INTERPRETATION: For children with newly diagnosed diabetes, having a usual provider of care appears to be important in decreasing the risk of diabetic ketoacidosis at the time of diabetes diagnosis. Our results provide further evidence concerning the need for initiatives that promote access to primary care for children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".