Cough Assessment and Management in Pulmonary Rehabilitation– A Canadian Survey
Bibliographic record
Abstract
Pulmonary rehabilitation is a cornerstone intervention for controlling respiratory symptoms in people with chronic respiratory diseases. Chronic cough affects up to 90% of people with chronic respiratory diseases, however, it is currently unknown whether chronic cough is assessed and/or managed in pulmonary rehabilitation. This study aimed to determine if and how chronic cough is assessed and managed in pulmonary rehabilitation. This was a cross-sectional study. Pulmonary rehabilitation programs in Canada were identified via online websites. A representative from each program was invited to complete an online survey including the following topics: program demographics, assessment and management practices, and barriers and facilitators. Of 133 programs contacted, 31 returned a completed survey (23% response rate). Approximately half (52%) of respondents reported enrolling patients with chronic cough. Of those, 45% reported assessing and 62% reported intervening in chronic cough. Inadequate knowledge of assessment and management techniques was commonly identified to be a barrier and increased education was suggested as a possible facilitator. Based on pulmonary rehabilitation programs that responded to our survey, chronic cough is a prevalent symptom; however, it is scarcely assessed and managed. A need for structured education and the use of standardised strategies were reported as facilitators to the assessment and management of chronic cough in pulmonary rehabilitation.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".