Factors associated with exacerbations in patients with COPD: NOVELTY study
Bibliographic record
Abstract
Background: NOVELTY (NCT02760329) is a global, prospective, observational study of patients with physician-assigned asthma and/or COPD. At baseline, physicians were asked: “During the past 12 months, on how many occasions has your patient experienced an exacerbation of their asthma or COPD beyond the patient9s usual day to day variance?” Objective: To describe factors associated with exacerbations in patients with a physician label of COPD (± asthma) enrolled in NOVELTY. Methods: Patients in the NOVELTY baseline cohort were categorised by exacerbation history in the 12 months prior to baseline, with analysis limited to exacerbations that were moderate (managed with oral corticosteroids and/or antibiotics, or an emergency department visit) or severe (required hospital admission). Results: Overall, 5,072 patients had COPD (mean age 66 years, 41% female, mean post-bronchodilator FEV1 64% predicted); 16% reported 1 moderate exacerbation only (Table). Patients with exacerbations were more likely to have concomitant asthma, comorbidities, greater airflow limitation, poorer health status, more missed days of work and more impairment of work due to ill health vs patients without exacerbations. Conclusions: Patients with COPD and a history of exacerbations (even those with only one moderate exacerbation) had a considerably higher disease burden than those without exacerbations, including more work impairment and use of more healthcare resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".