Impact of updated recommendations on acetylsalicylic acid use for primary prevention of cardiovascular disease in Canada: a population-based survey
Bibliographic record
Abstract
BACKGROUND: The debate over acetylsalicylic acid (ASA) therapy for primary prevention of cardiovascular disease (CVD) has recently resurfaced, but scarce data are available on prophylactic ASA use in Canada for this purpose. This study aimed to evaluate the prevalence and factors associated with ASA use, and the potential impact of implementing the most recent (2016) US Preventive Services Task Force recommendations for primary CVD prevention in a Canadian setting. METHODS: = 20 004) of the 2018 general population of the province of Quebec. We assessed eligibility for ASA treatment using US Preventive Services Task Force criteria (age 50-69 yr, no past history of myocardial infarction or stroke, and 10-year risk of CVD of at least 10%). We extrapolated to the entire 2018 Quebec population the number of people who would need to start ASA treatment. RESULTS: A total of 6231 respondents in the CARTaGENE study (54.2% of those aged 50-69 yr with no prior history of CVD) were found to be potentially eligible for ASA use for primary CVD prevention. Of the 6231, 1379 (22.1%) were receiving prophylactic ASA treatment. Factors found to be related to ASA use included age, male sex, regular medical visits, lower education level, obesity, hypertension, diabetes and dyslipidemia. Income and smoking status were not found to be significantly associated with ASA use. Our results indicate that 885 261 people would potentially have started ASA treatment if the US Preventive Services Task Force recommendations had been implemented in Quebec in 2018. INTERPRETATION: Prevalent ASA use for primary CVD prevention was low. Implementation of the 2016 US Preventive Services Task Force recommendations would require initiating ASA treatment in a substantial proportion of people, with undetermined potential benefits.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".