COVID-19 Rehabilitation With Herbal Medicine and Cardiorespiratory Exercise: Protocol for a Clinical Study
Bibliographic record
Abstract
BACKGROUND: Recent studies have revealed that many discharged patients with COVID-19 experience ongoing symptoms months later. Rehabilitation interventions can help address the consequences of COVID-19, including medical, physical, cognitive, and psychological problems. To our knowledge, no studies have investigated the effects of rehabilitation following discharge from hospital for patients with COVID-19. OBJECTIVE: The specific aims of this project are to investigate the effects of a 12-week exercise program on pulmonary fibrosis in patients recovering from COVID-19. A further aim will be to examine how Chinese herbal medicines as well as the gut microbiome and its metabolites regulate immune function and possibly autoimmune deficiency in the rehabilitation process. METHODS: In this triple-blinded, randomized, parallel-group, controlled clinical trial, we will recruit adult patients with COVID-19 who have been discharged from hospital in Hong Kong and are experiencing impaired lung function and pulmonary function. A total of 172 eligible patients will be randomized into four equal groups: (1) cardiorespiratory exercise plus Chinese herbal medicines group, (2) cardiorespiratory exercise only group, (3) Chinese herbal medicines only group, and (4) waiting list group (in which participants will receive Chinese herbal medicines after 24 weeks). These treatments will be administered for 12 weeks, with a 12-week follow-up period. Primary outcomes include dyspnea, fatigue, lung function, pulmonary function, blood oxygen levels, immune function, blood coagulation, and related blood biochemistry. Measurements will be recorded prior to initiating the above treatments and repeated at the 13th and 25th weeks of the study. The primary analysis is aimed at comparing the outcomes between groups throughout the study period with an α level of .05 (two-tailed). RESULTS: The trial has been approved by the university ethics committee following the Declaration of Helsinki (approval number: REC/19-20/0504) in 2020. The trial has been recruiting patients. The data collection will be completed in 24 months, from January 1, 2021, to December 31, 2022. CONCLUSIONS: Given that COVID-19 and its sequelae would persist in human populations, important findings from this study would provide valuable insights into the mechanisms and processes of COVID-19 rehabilitation. TRIAL REGISTRATION: ClinicalTrials.gov NCT04572360; https://clinicaltrials.gov/ct2/show/NCT04572360. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25556.
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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 | 0.025 | 0.018 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.066 | 0.017 |
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".