Why Are Patients With Chronic Obstructive Pulmonary Disease at Increased Risk of Cardiovascular Diseases?
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) increases the risk of cardiovascular disease 2- to 3-fold. The factors responsible for this association remain largely unknown. METHODS AND RESULTS: We analyzed data from participants, > or =50 years of age, of the Third National Health and Nutrition Examination Survey (n=6629) to determine whether C-reactive protein (CRP) and other systemic inflammatory markers are present in participants with chronic airflow obstruction and are associated with cardiac injury. Participants with severe airflow obstruction had circulating leukocyte, platelet, and fibrinogen levels that were 460/ microL (95% confidence interval [CI], 30 to 890/ microL), 39 510/ microL (95% CI, 21 730 to 57 290/ microL), and 41.63 mg/dL (95% CI, 19.87 to 63.39 mg/dL) higher, respectively, than in those without airflow obstruction. They were also 2.18 times (95% CI, 1.46 to 3.27) more likely to have an elevated circulating CRP level. Moderate airflow obstruction was associated with smaller but still significant increases in these levels. Moderate and severe airflow obstruction was associated with increased occurrence of ischemic changes on electrocardiograms of participants. In the presence of both highly elevated CRP and moderate or severe airflow obstruction, the Cardiac Infarction Injury Score was 2.68 and 5.88 U higher, respectively, than in those without airflow obstruction and with low CRP, which suggests an additive effect of CRP and COPD on the risk of cardiac injury. CONCLUSION: Low-grade systemic inflammation was present in participants with moderate to severe airflow obstruction and was associated with increased risk of cardiac injury. This may in part explain the high rates of cardiovascular complications in COPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".