Inpatient Physical Therapy in Moderate to Severe Traumatic Brain Injury in in Older Adults: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Around 500/100,000 Canadians experience a traumatic brain injury (TBI) resulting in long-term disabilities and premature death. Physiotherapy is known to positively impact the prognosis of young adults following a TBI. OBJECTIVE: This is a scoping review that aimed to identify research topics in physiotherapy interventions for seniors after a TBI, describe potential knowledge gaps, and uncover needs for future research. METHODOLOGY: Ten databases were interrogated (January-March 2022). We included texts published after 2010, in English or French, scientific papers, guidelines, and gray literature sources targeting in-hospital, acute-to-subacute interventions for people aged ≥55 years old with a moderate-to-severe TBI. The outcomes sought were physical/functional capacities, injury severity, and quality of life. RESULTS: From 1296 articles, 16 were selected. The number of participants from the studies altogether was 248,794. We identified eight retrospectives studies, three clinical trials, and five articles from the gray literature. Articles were classified according to the nature of their analysis and outcomes: (1) interventional studies including physiotherapy (at least 10 types of rehabilitative or preventive interventions were identified); (2) studies evaluating prognostic factors (five factors identified); and (3) recommendations from clinical practical guidelines and other sources (gray literature). Our results provide evidence that physiotherapy is effective in TBI acute rehabilitation for the elderly to prevent complications arising from the primary injury and to improve functional capacities. CONCLUSION: The heterogeneity of our results does not allow us to infer the effectiveness of one intervention over another. However, we found that the elderly population benefits from physiotherapy interventions as much as adults, but the gap must be filled with higher-quality studies to make definite recommendations.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".