Scoping review of rehabilitation care models for post COVID-19 condition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: To systematically map the current evidence about the characteristics of health systems, providers and patients to design rehabilitation care for post coronavirus disease 2019 (COVID-19) condition. Methods: We conducted a scoping review by searching the databases: MEDLINE®, Embase®, Web of Science, Cochrane COVID-19 Registry and Cochrane Central Register of Controlled Trials, from inception to 22 April 2022. The search strategy included terms related to (i) post COVID-19 condition and other currently known terminologies; (ii) care models and pathways; and (iii) rehabilitation. We applied no language or study design restrictions. Two pairs of researchers independently screened title, abstracts and full-text articles and extracted data. We charted the evidence according to five topics: (i) care model components and functions; (ii) safe delivery of rehabilitation; (iii) referral principles; (iv) service delivery settings; and (v) health-care professionals. Findings: We screened 13 753 titles and abstracts, read 154 full-text articles, and included 37 articles. The current evidence is conceptual and expert based. Care model components included multidisciplinary teams, continuity or coordination of care, people-centred care and shared decision-making between clinicians and patients. Care model functions included standardized symptoms assessment, telehealth and virtual care and follow-up system. Rehabilitation services were integrated at all levels of a health system from primary care to tertiary hospital-based care. Health-care workers delivering services within a multidisciplinary team included mostly physiotherapists, occupational therapists and psychologists. Conclusion: Key policy messages include implementing a multilevel and multiprofessional model; leveraging country health systems' strengths and learning from other conditions; financing rehabilitation research providing standardized outcomes; and guidance to increase patient safety.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it