Prescribing exercise training in pulmonary rehabilitation: A clinical experience
Bibliographic record
Abstract
Built around exercise training, pulmonary rehabilitation (PR) is a multidisciplinary, evidence‐based, comprehensive approach to working with the patient as a whole and not just the pulmonary component of the disease. Integrated into the individualized treatment, this intervention aims to reduce symptoms, optimize functional status, increase participation in daily life, and reduce health care costs through stabilizing or reversing systemic manifestations of the disease. Although there are many other components that should be considered to manage the impairment and symptom burden, supervised exercise training is considered the cornerstone of effective pulmonary rehabilitation. This paper addresses our clinical experience at Institut universitaire de cardiologie et de pneumologie de Québec to assess and manage exercise training in line with the current recommendations and guidelines surrounding PR. Construída com base no exercício físico, a reabilitação pulmonar (RP) é uma abordagem multidisciplinar, fundamentada e abrangente para trabalhar com o doente como um todo, e não apenas com a componente pulmonar da doença. Integrado no tratamento individual, esta intervenção visa reduzir os sintomas, optimizar o estado funcional, aumentar a participação na vida diária e reduzir os custos do tratamento de saúde, através da estabilização ou inversão das manifestações sistémicas da doença. Embora existam muitos outros componentes que devem ser tidos em consideração para gerir o peso da incapacidade e dos sintomas, o exercício físico supervisionado é considerado o fundamento da reabilitação pulmonar eficiente. Este documento trata da nossa experiência clínica no Institut universitaire de cardiologie et de pneumologie de Québec para avaliar e gerir o exercício físico em linha com as recomendações e orientações actuais envolvendo a RP.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".