One-year change in health status and subsequent outcomes in COPD
Bibliographic record
Abstract
BACKGROUND: Poor health status has been associated with morbidity and mortality in patients with COPD. To date, the impact of changes in health status on these outcomes remains unknown. AIMS: To explore the relationship of clinically relevant changes in health status with exacerbation, hospitalisation or death in patients with COPD. METHODS: Characteristics and health status (St George's Respiratory Questionnaire, SGRQ) were assessed over a period of 3 years in 2138 patients with COPD enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study: a longitudinal, prospective, observational study. Associations between change in health status (=4 units in SGRQ score) during year 1 and time to first exacerbation, hospitalisation and death during 2-year follow-up were assessed using Kaplan-Meier plots and log-rank test. RESULTS: 1832 (85.7%) patients (age 63.4±7.0 years, 65.4% male, FEV1 48.7±15.6% predicted) underwent assessment at baseline and 1 year. Compared with those who deteriorated, patients with improved or stable health status in year 1 have a lower likelihood of exacerbation (HR 0.78 (95% CI 0.67 to 0.89), p<0.001 and 0.84 (0.73 to 0.97), p=0.016, respectively), hospitalisation (0.72 (0.58 to 0.90), p=0.004 and 0.77 (0.62 to 0.96), p=0.023, respectively) or dying (0.61 (0.39 to 0.95), p=0.027 and 0.58 (0.37 to 0.92), p=0.019, respectively) during 2-year follow-up. This effect persisted after stratification for age and the number of exacerbations and hospitalisations during the first year of the study. CONCLUSIONS: Patients with stable or improved health status during year 1 of ECLIPSE had a lower likelihood of exacerbation, hospitalisation or dying during 2-year follow-up. Interventions that stabilise and improve health status may also improve outcomes in patients with COPD. TRIAL REGISTRATION NUMBER: NCT00292552, registered at ClinicalTrials.gov.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".