Safety and Efficacy of Pulmonary Rehabilitation for Long COVID Patients Experiencing Long-Lasting Symptoms
Bibliographic record
Abstract
Due to the high prevalence and persistence of long COVID, it is important to evaluate the safety and efficacy of pulmonary rehabilitation (PR) for patients who experience long-lasting symptoms more than six months after initial COVID-19 onset. Enrolled patients were admitted for a four-week in-patient-PR due to long COVID symptoms (n = 47). The safety of PR was confirmed by the absence of adverse events. Symptom-related outcomes were evaluated pre- and post-PR with significant score changes for: 6 min walking distance (61 [28 to 103] m), quality of life (mental Short Form-12: 10 [6 to 13], and physical: 9 [6 to 12]), Montreal Cognitive Assessment (1 [0 to 3]), fatigue (MFI-20: -19 [-28 to -8]), dyspnea (DYSPNEA-12: -7 [-9 to -2] and mMRC; -1 [-1 to 0]), Nijmegen questionnaire (-8 [-11 to -5]), anxiety and depression (HADS:-4 [-5 to -2] and -2 [-4 to -1], respectively) and posttraumatic stress disorder checklist scale (-8 [-12 to -4]). At the individual level, the percentage of symptomatic patients for each outcome decreased, with a high response rate, and the number of persistent symptoms per patient was reduced from six at PR initiation to three at the end of the program. Our results show that in-PR is safe and efficient at decreasing long-lasting symptoms experienced by long COVID patients at more than six months after initial disease onset.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".