Chronic traumatic encephalopathy-neuropathologic change in a routine neuropathology service: 7-year follow-up
Bibliographic record
Abstract
To follow our 2016 study of chronic traumatic encephalopathy neuropathologic change (CTE-NC) in our forensic autopsy service, we prospectively screened all cases with clinical histories of multiple concussions, persistent post-head injury symptoms, or ≥3 hospital investigations for head injuries from 2016 to 2022 inclusive using hyperphosphorylated tau (p-tau) immunostaining. The cases had routine brain sampling plus 4-6 additional lateral hemisphere samples. When "pathognomonic" CTE-NC lesions were identified, additional p-tau immunostaining was done for CTE-NC staging. Of ∼1100 adult brains aged 18-65 years examined, 85 were screened, and 16 were positive for CTE-NC (2 women, 14 men, ages 35-61 years, median 47 years). Alcohol abuse was documented in 14 of 16 (8 in combination with other substances); 5 had developmental brain anomalies (2 presumed genetic, 3 from acquired perinatal insults). Widespread p-tau deposits (high CTE-NC) were found in 7 of 16. Old brain contusions were present in 9 of 16, but CTE-NC did not colocalize. Of particular interest were (1) a man with FGFR3 mutation/hypochondroplasia and life-long head banging, (2) a woman with cerebral palsy and life-long head banging, and (3) a man with bilateral peri-Sylvian polymicrogyria, alcohol abuse, and multiple head injuries. Thus, CTE-NC occurs in association with repeated head trauma outside contact sports. Substance abuse is a common determinant of risk behavior. The utility of diagnosing mild-/low-stage CTE-NC in this population remains to be determined.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".