Systemic inflammation and mortality in chronic obstructive pulmonary diseaseThis paper is one of a selection of papers published in this Special Issue, entitled Young Investigators' Forum.
Bibliographic record
Abstract
Cardiovascular diseases and cancer (especially lung cancer) are leading causes of morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD). Some have implicated systemic inflammation, which is commonly observed in COPD, as the potential mechanistic bridge between COPD and these disorders. This concept has been supported by animal studies especially in rabbits, which have clearly demonstrated the effect of local lung inflammation on systemic inflammation and on the progression of atherosclerosis and by cross-sectional population-based studies, which have shown a significant relationship between systemic inflammation, as measured by circulating C-reactive protein (CRP) and the risk of cardiovascular diseases in COPD patients. These data have been further extended by a recent study that has elucidated the temporal nature of the relationship between systemic inflammation and the risk of cardiovascular events and cancer in COPD patients. This study showed that baseline CRP levels predicted the incidence of cardiovascular events and cancer-specific mortality over 7 to 8 years of follow-up. CRP levels also predicted all-cause mortality. Collectively, these data indicate that systemic inflammation may play an important role in mediating the extra-pulmonary complications of COPD. Systemic inflammation may contribute substantially to the overall morbidity and mortality of COPD patients.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".