Providing rehabilitation to patients recovering from<scp>COVID‐19</scp>: A scoping review
Bibliographic record
Abstract
OBJECTIVE: To synthesize the nature and extent of research on rehabilitation care provision to patients with COVID-19. Specifically, we aimed to (1) describe the impact of COVID on patients and associated rehabilitation needs, (2) outline the adaptations and preparations required to enable the provision of COVID rehabilitation, (3) describe the types of rehabilitation services and treatments provided to COVID patients, and (4) identify barriers and facilitators to delivering COVID rehabilitation. LITERATURE SURVEY: We searched Medline, PsychINFO, Embase, and CINAHL on June 26, 2020 using key words such as "rehabilitation," "physical medicine," "allied health professionals," and variations of "COVID." The search was updated on October 13, 2020. We included articles published in English and that focused on some aspect of COVID rehabilitation for adults. We excluded articles focused on pediatric populations and those not focused (or minimally focused) on rehabilitation for COVID patients. METHODOLOGY: Data were charted based on article type (ie, primary data, secondary data, guidelines). Key information extracted included (1) COVID sequelae; (2) rehabilitation adaptations; (3) structure, function, and content of rehabilitation services/programs; (4) facilitators and/or barriers to providing COVID rehabilitation; and (5) recommendations for COVID rehabilitation programming. Data were synthesized narratively. SYNTHESIS: In total, 128 articles were included in the review that reported primary data (n = 33), secondary data (n = 82), and clinical practice/patient self-management guidelines (n = 13). Evidence begins to suggest that rehabilitation is necessary and valuable for addressing COVID-related declines in health, function, and well-being. Most articles recommended that an individualized rehabilitation program be provided across the continuum of care by an interdisciplinary team of professionals and that the nature and extent of rehabilitation be informed by the care setting and COVID severity. Most issues that challenged COVID rehabilitation delivery were directly addressed by the facilitators and adaptations identified. CONCLUSIONS: Future recommendations include a greater emphasis on the psychosocial aspects of COVID rehabilitation, inclusion of families in rehabilitation planning, and the use of qualitative approaches to complement clinical data.
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 | 0.016 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".