Effect of telemonitoring and telerehabilitation on physical activity, exercise capacity, health-related quality of life and healthcare use in patients with chronic lung diseases or COVID-19: A scoping review
Bibliographic record
Abstract
BACKGROUND: Telemonitoring and telerehabilitation can support home-based pulmonary rehabilitation (PR) and benefit patients with lung diseases or COVID-19. This study aimed to (1) identify which telemonitoring and telerehabilitation interventions (e.g. videoconferencing) are used to provide telehealth care for people with chronic respiratory conditions or COVID-19, and (2) provide an overview of the effects of telemonitoring and telerehabilitation on exercise capacity, physical activity, health-related QoL (HRQoL), and healthcare use in patients with lung diseases or COVID-19. METHODS: A search was performed in the electronic databases of Ovid MEDLINE, EMBASE, and Cinahl through 15 June 2021. Subject heading and keywords were used to reflect the concepts of telemonitoring, telerehabilitation, chronic lung diseases, and COVID-19. Studies that explored the effect of a telerehabilitation and/or telemonitoring intervention, in patients with a chronic lung disease such as asthma, chronic obstructive pulmonary diseases (COPD), or COVID-19, and reported the effect of the intervention in one or more of our outcomes of interest were included. Excluding criteria included evaluation of new technological components, teleconsultation or one-time patient assessment. RESULTS: This scoping review included 44 publications reporting the effect of telemonitoring (25 studies), telerehabilitation (8 studies) or both (11 studies) on patients with COPD (35 studies), asthma (5 studies), COPD and asthma (1 study), and COVID-19 (2 studies). Patients who received telemonitoring and/or telerehabilitation had improvements in exercise capacity in 9 out of 11 (82%) articles, better HRQoL in 21 out of 25 (84%), and fewer health care use in 3 out of 3 (100%) articles compared to pre-intervention. Compared to controls, no statistically significant differences were found in the intervention groups' exercise capacity in 5 out 6 (83%) articles, physical activity in 3 out of 3 (100%) articles, HRQoL in 21 out of 25 (84%) articles, and healthcare use in 15 out of 20 (75%) articles. The main limitation of the study was the high variability between the characteristics of the studies, such as the number and age of the patients, the outcome measures, the duration of the intervention, the technological components involved, and the additional elements included in the interventions that may influence the generalization of the results. CONCLUSION: Telemonitoring and telerehabilitation interventions had a positive effect on patient outcomes and appeared to be as effective as standard care. Therefore, they are promising alternatives to support remote home-based rehabilitation in patients with chronic lung diseases or COVID-19.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".