Does Physical Fitness Prior to Traumatic Brain Injury Affect Recovery Outcomes? A Scoping Review of Human and Animal Research
Bibliographic record
Abstract
The objective of this study was to identify whether physical fitness influences outcomes following traumatic brain injury (TBI) in humans and animals, and to highlight any knowledge gaps in the current literature. A search of EMBASE, MEDLINE, SCOPUS, BIOSIS, and Cochrane Libraries was performed on December 4, 2023 (from database inception), and a systematic scoping review of the resulting literature was conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews was used for reporting the results. An online systematic review management system was used to remove all duplicates and for subsequent article screening. Following the removal of duplicates, the search identified 6,818 articles for screening, of which 10 articles met the inclusion/exclusion criteria and were included. One study was conducted in humans, while the remaining nine utilized murine models. The available literature is limited and has investigated a large variety of outcomes that were not consistent across studies. Additionally, the pre-TBI exercise intervention or fitness assessment method varied between the studies. With the current literature, it is not possible to draw conclusions regarding the effects of physical fitness level and outcomes following a TBI.
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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 | 0.020 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".