Short-Term Impact of the Frequency of COPD Exacerbations on Quality of Life
Bibliographic record
Abstract
Background: Chronic obstructive pulmonary disease (COPD) patients in the Simvastatin for the Prevention of Exacerbations in Moderate-to-Severe COPD (STATCOPE) and Azithromycin for Prevention of Exacerbations of COPD (MACRO) trials provide an opportunity to prospectively study the short-term effect of acute exacerbations of COPD (AECOPDs). Research Question: We hypothesized that those patients with frequent exacerbations (≥2 AECOPDs per patient year) would experience greater short-term decline in quality of life as measured by the St George's Respiratory Questionnaire (SGRQ). Study Design and Methods: A total of 1934 COPD patients were randomized in STATCOPE or MACRO. Patients who were randomized to azithromycin in MACRO or were followed less than 180 days were excluded. A total of 1219 patients were included. Patients were divided into 2 groups: infrequent exacerbators (< 2 exacerbations per patient year), and frequent exacerbators (≥2 exacerbations per year.) Data were collected at baseline, measured over time, and compared between groups. Results: Of the patients studied, 871 were in the infrequent exacerbators group. A total of 348 were in the frequent exacerbators group. Frequent exacerbators used more respiratory medications, were more likely to have used oxygen, steroids, or antibiotics in the 12 months preceding study entry, had more obstruction on spirometry, and had more severe symptoms as measured by SGRQ at baseline. Over at least 180 days, symptom scores worsened in frequent exacerbators and improved in infrequent exacerbators. Interpretation: Patients with frequent exacerbations of COPD experienced a short-term slight worsening of severely impaired SGRQ symptoms scores, while patients with infrequent exacerbations experienced improvement while on COPD therapies.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".