Patient perception on the effectiveness of guideline-based treatment for chronic cough
Bibliographic record
Abstract
Background: Current ERS/ACCP guidelines recommend a range of treatments for chronic cough (CC), but it is unclear how effective these are at improving subjective cough outcome in clinical practice. Objective: To evaluate the effectiveness of guideline recommended treatment for CC on patient reported outcomes (PROs). Methods: Prospective observational single center cohort study. Treatments were based on recent ERS guideline. CC assessments included Leicester Cough Questionnaire (LCQ), cough severity visual analogue scale (VAS), and patient perception of treatment response using the Global Rating of Change (GROC). Results: 69 patients with CC (49 females; mean (S.D) age, 55.7±14.5yrs, cough duration 7yrs, VAS 62.33mm(22.96), LCQ 10.55(3.36)) were recruited. 33 patients reported no benefit, while 36 patients reported important improvement on the GROC. Of these, 10 reported an improvement between a ‘tiny bit better’ and ‘somewhat better’. 26 patients scored between ‘moderately better’ and ‘a very great deal better’. Mean LCQ change varied (0.35 to 9.85), VAS scores ranged (−1.0mm to -58.0mm). Mean values and responder groups achieving MID for LCQ and VAS across GROC responses are reported. Conclusions: Guideline-based treatments improved cough PROs in only half the patients with CC. The magnitude of effect was highly variable across GROC items but higher than MID thresholds were observed for ‘moderately better’ or greater. erj;64/suppl_68/PA330/F1 F1 F1
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".