Rehabilitation Needs of Long COVID Patients in British Columbia
Bibliographic record
Abstract
Introduction: COVID-19 causes persistent symptoms that impair daily functioning, highlighting the need for targeted rehabilitation. Aim: Estimate the rehabilitation needs of Long COVID patients in British Columbia (BC) to inform care planning. Methods: A retrospective, cross-sectional study reviewed data from patients’ first post-COVID clinic visit. Long COVID was defined as symptoms >3 months, with clinic visits <6 months post-infection. Rehabilitation needs were based on predefined thresholds (Wong AW et al. Eur Respir J 2020). Results: Long COVID patients were mostly women (65%), white (57%), aged 49±14. Two-thirds were hospitalized. Visits occurred 136±34 days post-infection. At 3-6 months, 40% had muscle/joint aches, 52% muscle weakness, and 62% fatigue. Overall, 98% exceeded at least one rehab threshold. Based on the UCSD Shortness of Breath Questionnaire, 83% exceeded the rehab threshold. 65% reported activity restrictions due to poor health. Reductions ≥25% in 6 min walk distance and ≥50% in the sit-to-stand test were seen in 26% and 55%, respectively. Quality of life was significantly impaired for 80%. About one-third exceeded the Frailty Index threshold and 78% on the Fatigue Severity Scale. Depression, anxiety, and PTSD were observed in 36%, 42%, and 58%, respectively. Types of rehab are shown below. erj;66/suppl_69/PA5971/F1 F1 F1 Conclusion: Most Long COVID patients in BC need rehabilitation, particularly pulmonary and mental health support, 3-6 months post-infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".