A Telerehabilitation Program for Maintaining Functional Capacity in Patients With Chronic Lung Diseases During a Period of COVID-19 Social Isolation: Quasi-Experimental Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Pulmonary diseases represent a great cause of disability and mortality in the world, and given the progression of these pathologies, pulmonary rehabilitation programs have proven to be effective for people with chronic respiratory diseases. During the COVID-19 pandemic, telerehabilitation has become an alternative for patients with such diseases. OBJECTIVE: The aim of this study was to compare the outcomes (ie, functional capacity and quality of life) of telerehabilitation to those of usual care among patients who previously participated in face-to-face pulmonary rehabilitation programs. METHODS: We conducted a quasi-experimental retrospective study from April 2020 to August 2021. A total of 32 patients with chronic lung diseases were included and divided into the control and intervention groups. The intervention group performed telerehabilitation synchronously twice per week and was supervised by a physical therapist during breathing, strengthening, and aerobic exercises. Changes in the degree of dyspnea and leg discomfort were assessed based on changes in Borg scale scores. The control group did not perform any activities during the period of social isolation. Functional capacity was assessed with the 6-minute walk test, and quality of life was assessed with the Medical Outcomes Study 36-item Short Form Health Survey. RESULTS: The telerehabilitation group's mean 6-minute walk distance decreased by 39 m, while that of the control group decreased by 120 m. There was a difference of 81 m between the groups' mean 6-minute walk distances (P=.02). In relation to the quality of life, telerehabilitation was shown to improve the following two domains: social functioning and mental health. CONCLUSIONS: Telerehabilitation programs for patients with chronic lung diseases can ease the deleterious effects of disease progression, be used to maintain functional capacity, and improve aspects of quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".