Underreporting Exacerbation of Chronic Obstructive Pulmonary Disease in a Longitudinal Cohort
Bibliographic record
Abstract
RATIONALE: Unreported exacerbations and failure to seek medical attention may have consequences on the health of patients with chronic obstructive pulmonary disease. OBJECTIVES: This study aims to determine the incidence of reported and unreported exacerbations, to identify predictors of reporting, and to compare the impact of reported and unreported exacerbations on health status. METHODS: The study is based on a multicenter Canadian cohort of patients with chronic obstructive pulmonary disease. MEASUREMENTS AND MAIN RESULTS: Patients completed a daily diary from which exacerbations were defined as a worsening of at least one key symptom (dyspnea, sputum amount, sputum color) recorded on at least 2 consecutive days. Patients were asked to contact the study center if there was a sustained worsening of symptom. Reported exacerbations were events that led to contacting study center or health care visit. The study enrolled 421 patients. The overall incidence of diary exacerbations was 2.7 per person per year, but only 0.8 per person per year was reported. Predictors of reporting included age (HR [hazard ratio], 0.90; 95% confidence interval [CI], 0.81-0.98 per 5-yr increase), FEV(1)% predicted (HR, 0.84; 95% CI, 0.70-0.99 per 10% increase), number of symptoms at onset (HR, 1.59; 95% CI, 1.37-1.84 per additional symptom), and time of the week (HR, 0.35; 95% CI, 0.22-0.56 weekend vs. weekday). There was a clinically important decline in health status for 52% of patients with reported exacerbation and 43% with unreported exacerbations. CONCLUSIONS: This study has shown that less than one-third of the exacerbations were reported. The number of symptoms at onset was the most important predictor of reporting an exacerbation, and both reported and unreported exacerbations had an impact on health status.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".