Cardiovascular Risk Assessment and Management in a Systemic Sclerosis Cohort: A Quality Improvement Initiative
Bibliographic record
Abstract
Objectives Macrovascular atherosclerotic disease is a major cause of mortality in systemic sclerosis (SSc). We aimed to examine the current quality of cardiovascular risk assessment and management among patients with systemic sclerosis (SSc), to identify gaps in risk management that could be optimized. Methods SSc patients with no coronary artery disease (CAD) history followed in a clinical practice at the CHUM in the past 2 years were included. A retrospective chart review was performed to extract variables required to calculate the Framingham Risk Score (FRS) and the QRISK3 score. Patients with a lipid screening done in the last 5 years (if FRS <5%) or in the last year (if FRS ≥5%) were classified as having adequate lipid screening based on FRS guidelines, whereas all patients ≤ 40 years and patients older than 40 years with a lipid screening done in the last year were classified as having adequate lipid screening according to QRISK3 guidelines. Family history of CAD was assumed negative when missing. Characteristics associated with inadequate risk assessment and high FRS risk of cardiovascular events were evaluated using Student’s t tests and Fisher’s exact tests. Results A total of 61 SSc patients were evaluated (mean age 63 years, 92% female, 77% White, 22% diffuse SSc, 2% diabetes). Lipid screening was inadequate in 39% of patients, more frequently adequate among patients with family medicine follow-up (67% vs 36%, p=0.03), and numerically more often female (63% vs 40%, p=0.36) and White (67% vs 38%, p=0.10) using FRS. FRS and QRISK3 scores were estimated for 51 and 59 patients respectively. Around half (47% and 53%) of patients were classified as low risk based on FRS and QRISK3. Patients with high FRS (8/51) were older (mean age 71 vs 57 years, p=0.01) and numerically more often male (13% vs 0%, p=0.25), White (100% vs 74%, p=0.30), current smokers (25% vs 0%, p=0.06), with body mass index ≥25 (100% vs 36%, p=0.08) and systolic blood pressure ≥140mmHg (57% vs 0%, p=0.003). Finally, 84% of moderate-risk and 100% of high-risk patients did not achieve the lipid target according to FRS guidelines. Conclusion In this quality improvement project, nearly 40% of patients did not have adequate lipid screening and a high proportion of patients with moderate/high-risk profiles did not meet lipid targets. Rheumatologists should consider evaluating or referring for cardiovascular risk assessment and management, especially in patients without family medicine follow-up.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".