Branched Chain Amino Acids (BCAAs) and Traumatic Brain Injury: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Despite the prevalence of traumatic brain injury (TBI), pharmaceutical treatment options for brain injury remain limited. However, nutritional intervention (such as with branched chain amino acids [BCAAs]) has emerged as a promising treatment option for TBI. OBJECTIVES: (1) To determine whether TBI patients have lower levels of endogenous BCAAs postinjury; and (2) to evaluate whether post-TBI BCAA supplementation improves clinical outcome. DESIGN: A systematic review of primary research articles examining the relationship between BCAAs and TBI recovery indexed in Ovid/MEDLINE, EMBASE, and PsycINFO. RESULTS: Of the 11 studies identified, 3 examined the effects of TBI on endogenous BCAA levels and consistently reported that BCAA concentrations were depressed postinjury. The remaining 8 studies examined the effects of BCAA supplementation on TBI outcome in animals (n = 3) and humans (n = 5). The animal studies (in mild-to-moderate TBI) showed that BCAAs improved post-TBI outcome. Similar results were found in human trials (conducted primarily in patients with severe TBI), with 4 of the 5 studies reporting improved outcome with BCAA supplementation. CONCLUSION: Although our review demonstrates an overall positive association between BCAAs and TBI outcome, the evidence of the efficacy of supplementation has been limited to severe TBI. To date, there is insufficient evidence to determine the benefits of BCAAs in mild TBI. Given the high frequency of mild TBI and the promise of BCAAs as an intervention in severe TBI, future research should examine the effects of BCAAs in milder brain injury.
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".