Cardiovascular events after exacerbations of chronic obstructive pulmonary disease: Results from the EXAcerbations of COPD and their OutcomeS in CardioVascular diseases study in Italy
Bibliographic record
Abstract
INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) can increase the risk of severe cardiovascular events. OBJECTIVE: Assess the crude incidence rates (IR) of cardiovascular events and the impact of exacerbations on the risk of cardiovascular events within different time periods following an exacerbation. METHODS: COPD patients aged ≥45 years between 01/01/2015 and 12/31/2018 were identified from the Fondazione Ricerca e Salute administrative database. IRs of severe non-fatal and fatal cardiovascular events were obtained for post-exacerbation time periods (1-7, 8-14, 15-30, 31-180, 181-365 days). Time-dependent Cox proportional hazard models compared cardiovascular risks between periods with and without exacerbations. RESULTS: Of 216,864 COPD patients, >55 % were male, mean age was 74 years, frequent comorbidities were cardiovascular, metabolic and psychiatric. During an average 34-month follow-up, 69,620 (32 %) patients had ≥1 exacerbation and 46,214 (21 %) experienced ≥1 cardiovascular event. During follow-up, 55,470 patients died; 4,661 were in-hospital cardiovascular-related deaths. Among 10,269 patients experiencing cardiovascular events within 365 days post-exacerbation, the IR was 15.8 per 100 person-years (95 %CI 15.5-16.1). Estimated hazard ratios (HR) for the cardiovascular event risk associated with periods post-exacerbation were highest within 7 days (HR: 34.3, 95 %CI: 33.1-35.6), especially for heart failure (HR 50.6; 95 %CI 48.6-52.7) and remained elevated throughout 365 days (HR 1.1, 95 %CI 1.02-1.13). CONCLUSIONS: COPD patients in Italy are at high risk of severe cardiovascular events following exacerbations, suggesting the need to prevent exacerbations and possible subsequent cardiovascular events through early interventions and treatment optimization.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".