A cross-sectional study evaluating cardiovascular risk and statin prescribing in the Canadian Primary Care Sentinel Surveillance Network database
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is a major cause of morbidity and mortality in Canada. Assessment and management of CVD risk is essential in reducing disease burden. This includes both clinical risk factors and socioeconomic factors, though few studies report on socioeconomic status in relation to CVD risk and treatment. The primary objective of this study was to estimate the cardiovascular risk of patients attending primary care practices across Canada; secondly, to evaluate concordance with care indicators suggested by current clinical practice guidelines for statin prescribing according to patients' cardiovascular risk and socioeconomic status. METHODS: This cross-sectional observational study used the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database, which is comprised of clinical data from primary care electronic medical records. Patients aged 35-75y with at least one visit to their primary care provider between 2012 and 2016 were included. Patients were assigned to a CVD risk category (high, medium, low) and a deprivation quintile was calculated for those with full postal code available. Descriptive analyses were used to determine the proportion of patients in each risk category. Logistic regression was used to evaluate the consistency of statin prescribing according to national clinical guidelines by risk category and deprivation quintile. RESULTS: A total of 324,526 patients were included. Of those, 116,947 (36%) of patients were assigned to a high CVD risk category, primarily older adults, males, and those with co-morbidities. There were statistically significant differences between least (quintile 1) and most (quintile 5) deprived socioeconomic quintiles, with those at high CVD risk disproportionately in Q5 (odds ratio 1.4). Overall, 48% of high-risk patients had at least one statin prescription in their record. Patients in the lower socioeconomic groups had a higher risk of statin treatment which deviated from clinical guidelines. CONCLUSIONS: Primary care patients who are at high CVD risk are more often male, older, have more co-morbidities and be assigned to more deprived SES quintiles, compared to those at low CVD risk. Additionally, patients who experience more challenging socioeconomic situations may be less likely to receive CVD treatment that is consistent with care guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".