Rehabilitation of Individuals With Severe Stroke: Synthesis of Best Evidence and Challenges in Implementation
Bibliographic record
Abstract
PURPOSE: The rehabilitation of patients who are recovering from severe stroke is associated with a substantial use of resources but limited potential for functional improvement. As a result, these individuals are not perceived as being ideal candidates for inpatient stroke rehabilitation. The objective of this review was to describe the evidence for and discuss some of the challenges of providing inpatient rehabilitation services for individuals with severe stroke. METHODS: A literature search was conducted to identify relevant studies. Studies were included if (a) inpatient rehabilitation was compared to other rehabilitation settings and (b) the study population included individuals with severe stroke-related disability. Following data abstraction, the methodological quality of randomized controlled trials (RCTs) that met inclusion criteria was assessed using the PEDro scale. RESULTS: Fourteen studies (including 4 RCTs) met inclusion criteria. Despite making limited functional improvement, persons with severe strokes who received inpatient rehabilitation had reduced mortality, decreased lengths of hospital stay, and increased likelihood of discharge home when compared to those who received rehabilitation in other settings. Rehabilitation on specialized stroke units resulted in better outcomes than other forms of inpatient rehabilitation for this group. CONCLUSION: Inpatient rehabilitation is beneficial for individuals with severe stroke. However, for this group, it may be necessary to rethink the emphasis on functional improvement and focus more on discharge planning. These individuals may still have restricted access to rehabilitation as a result of limited resources, the perception that they have poor rehabilitation potential, limited understanding of the goals of rehabilitation for this population, and a lack of research.
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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 | 0.072 | 0.249 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".