Negative impacts of unreported COPD exacerbations on health-related quality of life at 1 year
Bibliographic record
Abstract
Unreported chronic obstructive pulmonary disease (COPD) exacerbations are common, but their intermediate-to-long-term impacts on health-related quality of life (HRQoL) are unknown. The aim of the present study was to examine the impact of unreported exacerbations on HRQoL at 1 yr. A multicentric prospective cohort study in 491 COPD patients was conducted in China. HRQoL was measured using the St George's Respiratory Questionnaire (SGRQ). Other measurements included sociodemographic, clinical, psychosocial and treatment profiles. Patients were monitored monthly for 12 months to document exacerbations (at least one symptom worsening for > or =48 h). Patients were categorised into six groups: no exacerbation, one unreported exacerbation only, more than one unreported exacerbation only, one reported exacerbation only, more than one reported exacerbation only, and both unreported and reported exacerbations. Generalised estimating equations were used to estimate the adjusted associations between exacerbations and HRQoL change. A total of 466 unreported and 410 reported exacerbations were recorded. Compared with patients with no exacerbations, the change in SGRQ total score was similar amongst patients with one unreported exacerbation (adjusted mean change 1.22 points (95% CI -4.05-6.48)), but significantly worse among patients with more than one unreported exacerbation (4.61 (95% CI 0.09-9.13)). Development and evaluation of self-management programmes emphasising early recognition of exacerbations and consequent action appear to be warranted.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".