Chronic diseases and variations in rates of antimicrobial use in the community: a population-based analysis of linked administrative data in Quebec, Canada, 2002–2017
Bibliographic record
Abstract
BACKGROUND: Chronic diseases may increase risk of infection and complications from infections; fear of these risks may lower clinicians' tolerance threshold for the prescription of antimicrobials, thus increasing the risk of selecting resistant bacteria. We sought to describe rates of antimicrobial use in Quebec and measure the association between chronic diseases and utilization rates. METHODS: Using the Quebec Integrated Chronic Disease Surveillance System, we analyzed data of people covered by the public drug insurance plan in 2002-2017. Based on delivered prescriptions, we described trends in antimicrobial use in the population, and per category of select chronic diseases (i.e., none, respiratory, cardiovascular, diabetes, mental disorder), according to age group (0-17 yr, 18-64 yr and ≥ 65 yr). We computed ratios of extended-to-narrow-spectrum antimicrobials in 2014-2017. We used robust Poisson regression to quantify the association between chronic diseases and rates of antimicrobial use among children and adults (≥ 18 yr). RESULTS: Between 2002 and 2017, 4 231 724 prescriptions were received over 6 653 473 individual-years among children; 1 367 492 (20.6%) individual-years had at least 1 chronic disease. Among adults aged 18-64 years, 13 365 577 prescriptions were received over 24 935 592 individual-years; 9 533 493 (38.2%) individual-years had at least 1 chronic disease. Among adults 65 years or older, 11 689 365 prescriptions were received over 15 927 342 individual-years; 12 743 588 (80.0%) individual-years had least 1 chronic disease. Antimicrobial use decreased among children, remained stable among younger adults and increased among older adults. Trends were consistent across chronic disease categories in children and older adults. In 2014-2017, 19.9% of children, 39.1% of younger adults and 79.7% of older adults had at least 1 chronic disease. Claims for extended-spectrum antimicrobials were frequent in all age and chronic disease groups, relative to narrow-spectrum antimicrobials (ratios from 3.1:1 to 14.6:1). Antimicrobial use was higher among people with respiratory diseases (adults: relative rate [RR] 2.09, 95% confidence interval [CI] 2.07-2.10; children: RR 1.62, 95% CI 1.59-1.65), mental health diagnoses (adults: RR 1.48, 95% CI 1.46-1.49; children: RR 1.22, 95% 1.20-1.24), diabetes (adults: RR 1.40, 95% CI 1.28-1.41; children: RR 2.02, 95% CI 1.58-2.57) and cardiovascular diseases (adults: RR 1.31, 95% CI 1.30-1.32), compared with those with none of the studied chronic diseases. INTERPRETATION: During the study period, large proportions of antimicrobial prescriptions were for people with chronic diseases, across the age spectrum. Interventions to reduce antimicrobial use should be tailored for these populations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.009 |
| 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) | 0.003 | 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".