QRISK3 underestimates the risk of cardiovascular events in patients with COPD
Bibliographic record
Abstract
BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of cardiovascular disease (CVD). The extent to which the excess CVD risk is captured by risk factors in QRISK, a widely used CVD risk scoring tool, is not well studied. METHODS: We created an incidence cohort of diagnosed COPD patients from the United Kingdom (UK) Clinical Practice Research Datalink GOLD database (January 1998-July 2018). The outcome was a composite of fatal or non-fatal CVD events. Sex-specific age-standardised incidence ratios (SIR) were compared with values for the UK primary-care population. The observed 10-year CVD risk was derived using the Kaplan-Meier estimator and was compared with predicted 10-year risk from the QRISK3 tool. RESULTS: 13 208 patients (mean age 64.9 years, 45% women) were included. CVD incidence was 3.53 events per 100 person-years. The SIR of CVD was 1.71 (95% CI 1.61 to 1.75) in women and 1.62 (95%CI 1.54-1.64) in men. SIR was particularly high among patients younger than 65 years (women=2.13 (95% CI 1.94 to 2.19); men=1.86 (95% CI 1.74 to 1.90)). On average, the observed 10-year risk was 52% higher than QRISK predicted score (33.5% vs 22.1%). The difference was higher in patients younger than 65 years (observed risk 82% higher than predicted). CONCLUSION: People living with COPD are at a significantly heightened risk of CVD over and beyond their predicted risk. This is particularly the case for younger people whose 10-year CVD risk can be >80% higher than predicted. Risk scoring tools must be validated and revised to provide accurate CVD predictions in patients with COPD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".