Trends in management of cardiovascular risk factors in young adults who go on to develop coronary artery disease
Bibliographic record
Abstract
Abstract Background Rates of premature coronary artery disease (CAD) have remained stagnant in many countries in the past two decades. While guidelines on cardiovascular prevention are evolving to improve risk assessment, more data are needed to evaluate changes in risk management in younger patients with high cardiovascular risk. Purpose To investigate the trends in pre-presentation prevalence and management of major cardiovascular risk factors (CVRFs) and predictors of initiation of lipid-lowering therapy (LLT) in patients with premature coronary artery disease. Methods In this retrospective cohort study, we identified women <55 years old and men <50 years old who presented with obstructive CAD (stenosis >50% or history of coronary revascularization) between 2000 and 2017. Data were collected from administrative databases and provincial cardiac information system and included demographics, all outpatient visits, hospitalizations, pharmacy dispenses in the period of 3 years prior to CAD, presentation characteristics, and results of invasive coronary angiography. Results In total, 14,470 patients (29.7% females) met the study criteria. During the study period, prevalence decreased for dyslipidemia and smoking and increased for hypertension, diabetes and obesity (Figure 1). Over 96.5% of patients were eligible for lipid screening 3 years prior to presentation with CAD, 93.5% had visits with primary care physicians, and 57.4% had visits with specialist physicians. Only 20.5% received LLT, with rates rising from 19% in the year 2000 to 24% in 2017 (p=0.023). Additionally, 38.1% of patients received medical treatment for other CVRFs. Figure 2 presents risk management and rates of LLT initiation in patients with five major CVRFs. In multivariable logistic regression analysis, LLT was more likely in patients with diabetes (odds ratio [OR] 3.04, 95% CI 2.74–3.36), hypertension (OR 1.44, 95% CI 1.30–1.58), chronic kidney disease (OR 1.79, 95% CI 1.44–2.23), and depression (OR 1.25, 95% CI 1.11–1.40). Later year of presentation (OR 1.04, 95% CI 1.03–1.05), older age at presentation (OR 1.03, 95% CI 1.02–1.04) and residing in urban areas vs rural (OR 1.36, 95% CI 1.16–1.58) were also positively associated with LLT. Male sex (OR 0.88, 95% CI 0.78–0.98) and smoking (OR 0.68, 95% CI 0.62–0.76) were associated with lower likelihood of treatment. Obesity, hypothyroidism, chronic inflammatory conditions, and malignancies were not significantly associated with LLT. Conclusion Despite the rising prevalence of CVRFs, high eligibility for lipid screening, and availability of care, rates of LLT initiation in patients who go on to develop premature CAD remain very low, representing a major missed opportunity for cardiovascular disease prevention. Many of the major CVRFs and risk enhancers endorsed in current guidelines were not associated with treatment initiation, suggesting that new approaches may be required to increase appropriate use LLT in these patients. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): St. Pauls Hospital Foundation, Vancouver, BC, CanadaVancouver General Hospital Foundation, Vancouver, BC, Canada
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".