CCS patients with polyvascular disease are a high risk but heterogenous subset of patients: insights from the CLARIFY registry
Bibliographic record
Abstract
Abstract Introduction Polyvascular disease constitutes a powerful predictor of cardiovascular events, is found in 10 to 15% of chronic coronary syndromes (CCS) patient. Smoking and diabetes mellitus are strongly associated with polyvascular disease. Risk stratification is key to select the most appropriate therapeutic strategy for a given patient. Purpose We aimed to describe 5-year ischaemic risk of CCS patients according to vascular disease phenotype and diabetic or smoking status. Method We analyzed data from 32 703 consecutive CCS outpatients (45 countries) enrolled between November 2009 to June 2010 in the prospective observational CLARIFY registry. Three mutually exclusive groups were compared: Coronary artery disease (CAD) alone, CAD with peripheral artery disease (PAD) or cerebrovascular disease (CVD) (CAD+1), CAD with CVD and PAD (CAD+2). Primary outcome was a composite of cardiovascular death, myocardial infarction or stroke, adjusted on age, sex and geographic origin at 5 years. Results At baseline, 26440 (80.8%) patients were diagnosed with CAD alone, 4967 (15.2%) had CAD+1, 1296 (4%) had CAD+2. Overall, 9501 (29%) patients were diabetics, 19184 (58.7%) were smokers or ex-smokers and only 9220 (28.2%) were free of these two major cardiovascular risk factors. Primary outcome increasing gradually according to the number of arterial diseases locations from 8.4% (95% CI 8.09–8.73) in patients with CAD alone to 17.4% (95% CI 16.95–17.83) of CAD+2 patients (p<0.001). Subgroup analysis according to diabetes or smoking status further enriched risk stratification from 7% (95% CI 6.48–7.59) in non-diabetic, non-smoking CAD alone patients to 20.3% (95% CI 19.08–21.44) in diabetics and smokers CAD+ 2 patients (Figure 1). Diabetic CAD alone patients had a comparable risk to that of non-diabetic and non-smoking polyvascular patients, 9.8% (95% CI 8.82–10.68) vs 10.3% (95% CI 9.61–10.96), p=0.38. Outcome was similar between polyvascular diabetic patients, regardless of the number of arterial diseases, 15.5% (95% CI 14.31–16.60) for CAD+1 and 15.0 (95% CI 13.88–16.13) for CAD+2, p=0.83. Smoking increased 5-year risk proportionally to the number of symptomatic arterial bed, 8.2% (95% CI 7.72–8.68) vs 11.8% (95% CI 11.18–12.31) vs 17.9% (95% CI 17.18–18.54), respectively for CAD alone, CAD+1 and CAD+2. Conclusion CCS patients with polyvascular disease remain at high risk of ischaemic events in the contemporary practice with widespread secondary prevention therapies. Polyvascular is a very heterogenous subset of patients with ischaemic risk varying not only according to the number of vascular bed diseased but also according to smoking and diabetes status, two conditions present in the vast majority of CCS patients. Diabetes confers upfront a maximal increased risk. Identification of higher risk subsets in polyvascular patients can potentially identify those that could derived the greatest benefit from new secondary prevention strategies. Figure 1 Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Assistance Publique-Hôpitaux de Paris
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".