Impact of COPD on cardiovascular risk factors and outcomes in people with established cardiovascular disease
Bibliographic record
Abstract
BACKGROUND: Little is known about the association between chronic obstructive pulmonary disease (COPD) and cardiovascular disease (CVD) in people with established CVD. Knowing if COPD is associated with a higher risk of cardiovascular events would guide appropriate secondary prevention. OBJECTIVE: To examine the risk of COPD on major adverse cardiac events (MACEs, acute myocardial infarction, stroke and cardiovascular death) in a complete real-world population of a large province, with known CVD. METHODS: We conducted a retrospective population cohort study using health administration, medication, laboratory, electronic medical record and other data from Ontario, Canada. All people with a history of CVD with and without physician-diagnosed COPD as of 2008 were followed until 2016 and cardiac risk factors, sociodemographic factors, comorbidities and other factors were compared. Sequential cause-specific hazard models adjusting for these factors determined the risk of MACE in people with COPD. RESULTS: Of 496 056 individuals with CVD in Ontario on 1 January 2008, 69 161 (13.9%) had COPD. MACE occurred more frequently among those with CVD (45.3 per 1000 person-years) and COPD compared with those with CVD alone (28.6 per 1000 person-years) (HR 1.24, 95% CI 1.21-1.26) after adjustment for cardiac risk factors, comorbidities, socioeconomic status and other factors. People with COPD were less likely to receive preventive CVD medications or see a cardiologist. CONCLUSION: In a large, real-world population of people with established CVD, COPD was associated with a higher rate of cardiovascular events but a lower rate of preventive therapy. Strategies are needed to improve secondary CVD prevention in the COPD population.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".