Prevalence of Adult Type 2 Diabetes Mellitus and Related Complications in Alberta, Canada: A Retrospective, Observational Study Using Administrative Data
Bibliographic record
Abstract
OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a prevalent chronic disease and a leading cause of morbidity/mortality in Canada. We evaluated the burden of T2DM in Alberta, Canada, by estimating the 5-year period prevalence of T2DM and rates of comorbidities and complications/conditions after T2DM. METHODS: We conducted a population-based, retrospective study linking administrative health databases. Individuals with T2DM (≥18 years of age) were identified between 2008-2009 and 2018-2019 using a published algorithm, with follow-up data to March 2020. The 5-year period prevalence was estimated for 2014-2015 to 2018-2019. Individuals with newly identified T2DM, ascertained between 2010-2011 and 2017-2018 with a lookback period between 2008-2009 and 2009-2010 and a minimum 1 year of follow-up data, were evaluated for subsequent cardiovascular, diabetic, renal, and other complication/condition frequencies (%) and rates (per 100 person-years). Complications/conditions were stratified by atherosclerotic cardiovascular disease (ASCVD) status at index and age. RESULTS: The 5-year period prevalence of T2DM was 11,051 per 100,000 persons, with the highest prevalence in men 65 to <75 years of age. There were 195,102 individuals included in the cohort (mean age 56.7±14.7 years). The most frequently reported complications/conditions (rates per 100 person-years) were acute infection (23.10, 95% confidence interval [CI] 23.00 to 23.30), hypertension (17.30, 95% CI 16.80 to 17.70), and dyslipidemia (12.20, 95% CI 11.90 to 12.40). Individuals who had an ASCVD event/procedure and those ≥75 years of age had higher rates of complications/conditions. CONCLUSIONS: We found that over half of the individuals had hypertension or infection after T2DM. Also, those with ASCVD had higher rates of complications/conditions. Strategies to mitigate complications/conditions after T2DM are required to reduce the burden of this disease on individuals and health-care systems.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".