Effects of Cardiopulmonary Rehabilitation on Cardiorespiratory Fitness and Clinical Symptom Burden in Long COVID
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to investigate the effectiveness of an 8-wk cardiopulmonary rehabilitation program on cardiorespiratory fitness (VO 2 peak) and key cardiopulmonary exercise test measures, quality of life, and symptom burden in individuals with long COVID. DESIGN: Forty individuals with long COVID (mean age 53 ± 11 yrs), were randomized into two groups: (1) rehabilitation group: center-based individualized clinical rehabilitation program (8 wks, 3 sessions per week of aerobic and resistance exercises, and daily inspiratory muscle training) and (2) control group: individuals maintained their daily habits during an 8-wk period. RESULTS: There was a significant difference between groups in mean VO 2 peak improvement ( P = 0.003). VO 2 peak improved significantly in the rehab group (+2.7 mL.kg.min; 95% CI = +1.6 to +3.8; P < 0.001) compared to the control group (+0.3 mL.kg.min; 95% CI = -0.8 to +1.3 P = 0.596), along with VE/VCO 2 slope ( P = 0.032) (-2.4; 95% CI = -4.8 to +0.01; P = 0.049 and +1.3; 95% CI = -1.0 to +3.6; P = 0.272, respectively) and VO 2 at first ventilatory threshold ( P = 0.045). Furthermore, all symptom impact scales improved significantly in the rehabilitation group compared to the control group ( P < 0.05). CONCLUSIONS: An individualized and supervised cardiopulmonary rehabilitation program was effective in improving cardiorespiratory fitness, ventilatory efficiency, and symptom burden in individuals with long COVID. Careful monitoring of symptoms is important to appropriately tailor and adjust rehabilitation sessions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".