EXAcerbations of COPD and their OutcomeS on CardioVascular diseases (EXACOS-CV) Programme: protocol of multicountry observational cohort studies
Bibliographic record
Abstract
INTRODUCTION: In patients with chronic obstructive pulmonary disease (COPD), the risk of certain cardiovascular (CV) events is increased by threefold to fivefold in the year following acute exacerbation of COPD (AECOPD), compared with a non-exacerbation period. While the effect of severe AECOPD is well established, the relationship of moderate exacerbation or prior exacerbation to elevated risk of CV events is less clear. We will conduct cohort studies in multiple countries to further characterise the association between AECOPD and CV events. METHODS AND ANALYSIS: Retrospective longitudinal cohort studies will be conducted within routinely collected electronic healthcare records or claims databases. The study cohorts will include patients meeting inclusion criteria for COPD between 1 January 2014 and 31 December 2018. Moderate exacerbation is defined as an outpatient visit and/or medication dispensation/prescription for exacerbation; severe exacerbation is defined as hospitalisation for COPD. The primary outcomes of interest are the time to (1) first hospitalisation for a CV event (including acute coronary syndrome, heart failure, arrhythmias or cerebral ischaemia) since cohort entry or (2) death. Time-dependent Cox proportional hazards models will compare the hazard of a CV event between exposed periods following exacerbation (split into these periods: 1-7, 8-14, 15-30, 31-180 and 181-365 days) and the unexposed reference time period, adjusted on time-fixed and time-varying confounders. ETHICS AND DISSEMINATION: Studies have been approved in Canada, Japan, the Netherlands, Spain and the UK, where an institutional review board is mandated. For each study, the results will be published in peer-reviewed journals.
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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 | 0.082 | 0.059 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".