Post-acute white matter microstructure predicts post-acute and chronic post-concussive symptom severity following mild traumatic brain injury in children
Bibliographic record
Abstract
INTRODUCTION: Mild traumatic brain injury (TBI) is a global public health concern that affects millions of children annually. Mild TBI tends to result in subtle and diffuse alterations in brain tissue, which challenges accurate clinical detection and prognostication. Diffusion tensor imaging (DTI) holds promise as a diagnostic and prognostic tool, but little research has examined DTI in post-acute mild TBI. The current study compared post-acute white matter microstructure in children with mild TBI versus those with mild orthopedic injury (OI), and examined whether post-acute DTI metrics can predict post-acute and chronic post-concussive symptoms (PCS). MATERIALS AND METHODS: Children aged 8-16.99 years with mild TBI (n = 132) or OI (n = 69) were recruited at emergency department visits to two children's hospitals, during which parents rated children's pre-injury symptoms retrospectively. Children completed a post-acute (<2 weeks post-injury) assessment, which included a 3T MRI, and 3- and 6-month post-injury assessments. Parents and children rated PCS at each assessment. Mean diffusivity (MD) and fractional anisotropy (FA) were derived from diffusion-weighted MRI using Automatic Fiber Quantification software. Multiple multivariable linear and negative binomial regression models were used to test study aims, with False Discovery Rate (FDR) correction for multiple comparisons. RESULTS: No significant group differences were found in any of the 20 white matter tracts after FDR correction. DTI metrics varied by age and sex, and site was a significant covariate. No interactions involving group, age, and sex were significant. DTI metrics in several tracts robustly predicted PCS ratings at 3- and 6-months post-injury, but only corpus callosum genu MD was significantly associated with post-acute PCS after FDR correction. Significant group by DTI metric interactions on chronic PCS ratings indicated that left cingulum hippocampus and thalamic radiation MD was positively associated with 3-month PCS in the OI group, but not in the mild TBI group. CONCLUSIONS: Post-acute white matter microstructure did not differ for children with mild TBI versus OI after correcting for multiple comparisons, but was predictive of post-acute and chronic PCS in both injury groups. These findings support the potential prognostic utility of this advanced DTI technique.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".