The Scale of Neurodegeneration in Moderate‐to‐Severe Traumatic Brain Injury: A Systematic Review of Longitudinal Studies
Bibliographic record
Abstract
OBJECTIVE: Although moderate-to-severe traumatic brain injury (msTBI) was once considered a static neural event following resolution of acute injuries, numerous studies now demonstrate progressive losses to volume and white matter integrity in the months and years postinjury, leading to a paradigm shift in our understanding. These findings have yet to be synthesized. Therefore, our objective was to assimilate longitudinal studies of chronic msTBI to better elucidate the scale and timelines of neurodegeneration, regions of vulnerability, and ongoing gaps in the literature. METHODS: As per our published systematic review protocol (see PROSPERO CRD42019117548), 6 electronic databases were searched from inception to June 2024. Included studies examined adults (> 17) with msTBI, were longitudinal with first acquisition at least 2 months postinjury, and reported whole brain and/or regional volumetrics or fractional anisotropy (FA). RESULTS: We identified 21 studies, with and without controls, and computed annualized percent change for the limited studies with overlapping regions and timelines with sufficient data. Overall, widespread progressive volumetric and FA losses were observed, with no evidence of accelerated progression across time. No volumetric but some FA increases (predominantly nonsignificant) were observed. Annualized percent changes in ascending order were: total grey matter volume (-0.28%), total white matter volume (-0.65%), hippocampal volume (-1.98%, bilaterally), and corpus callosum FA (-3.15%). INTERPRETATION: Gaps in our understanding include mechanisms of degeneration, whether progressive losses remain constant or attenuate with time, and how patterns vary by region. Longitudinal research with 3 timepoints, standardized reporting, and additional outcome modalities (eg, functional magnetic resonance imaging [fMRI], and blood biomarkers) would refine our understanding and inform treatment research. ANN NEUROL 2025;98:668-681.
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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 | 0.019 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".