Pain during exacerbation of chronic obstructive pulmonary disease: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Pain, a symptom often present in patients with Chronic Obstructive Pulmonary Disease (COPD), alters quality of life. COPD exacerbation augments several mechanisms that may cause pain (dyspnea, hyperinflation and inflammation) and therefore we hypothesized that pain might be increased during exacerbation. METHODS: A prospective cohort study was conducted in patients admitted for acute exacerbations of COPD (AECOPD) in two emergency departments in France and Canada. Patients with cancer-related pain or recent trauma were not included. The Short Form McGill Pain Questionnaire (SF-MPQ) and the Brief Pain Inventory (BPI) scale were used to evaluate pain intensity and location. Patients also completed the Borg Dyspnea Scale and Hospital Anxiety and Depression Scale. The questionnaires were completed again during an outpatient assessment in the stable phase. The primary outcome was difference in pain intensity (SF-MPQ) between the exacerbation and stable phases. RESULTS: Fifty patients were included. During exacerbation, 46 patients (92%) reported pain compared to 29 (58%) in the stable phase (p<0.001). Pain intensity was higher during exacerbation (SF-MPQ 29.7 [13.6-38.2] vs. 1.4 [0.0-11.2]; p<0.001). Pain was predominantly located in the chest during exacerbation and in the limbs during the stable phase. Pain intensity during exacerbation correlated with anxiety score. CONCLUSION: The frequency and intensity of pain were higher during AECOPD, with a specific distribution. Pain should therefore be routinely assessed and treated in patients with AECOPD.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".