THE NEURORADIOLOGY OF ACUTE HEAD INJURY AND LONGTERM OUTCOME
Bibliographic record
Abstract
Traumatic brain injury (TBI) is a frequent reason for hospital admission in a paediatric population. Recent studies reveal significant outcome problems even after mild TBI. With the modern possibility of imaging, especially magnetic resonance (MR) imaging a correlation of imaging findings during the acute and chronic phase help in evaluation of these problems. Prediction of outcome could be established by degree of brainedema, especially worsened in case of coexistence with small deep-seated intraparenchymal hemorrhagic foci and/or intraventricular haemorrhage. Outcome of closed TBI is essentially influenced by the degree and localisation of axonal injury, represented by small (<2cm) intracranial lesions. Not only number but even more important localisation of small intracranial lesions account for outcome: bilateral are worse than unilateral lesions, additional lesions in brainstem more so in pons than mesencephalon worsen prognosis. Important for evaluation is also injury to the corpus callosum, either by small haemorrhagic lesions, prognostically better by focal areas of oedema. Choice of imaging modalities for this early evaluation is important, so are DWI, T2*-GE and less important T2-FSE or T2 weighted images the most adequate modalities. Besides anatomical changes also metabolic changes visualized by MR spectroscopy are helpful for prognostic work up: increased lactate levels as well as lower NAA/Cre or NAA/Cho; or higher Cho/Cre peaks are related to poor outcome. After the acute phase localisation and degree of atrophy, especially white matter atrophy can predict degree and variant from neuropsychological problems. Whole brain volume loss corresponds with intelligence quotient, whereas atrophy in hippocampus predicts memory problems, in frontal lobe attention and other executive problems and in corpus callosum slowed mental processing. In conclusion early and late neuroimaging after TBI is helpful in predicting outcome, especially neuropsychological outcome. Therefore these imaging modalities are important for organisation of rehabilitation after head trauma.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".