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Record W2548378272 · doi:10.1093/jnen/nlw092

Chronic Traumatic Encephalopathy-Like Abnormalities in a Routine Neuropathology Service

2016· article· en· W2548378272 on OpenAlexaff
Shawna Noy, Sherry Krawitz, Marc R. Del Bigio

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of ManitobaShared Health
Fundersnot available
KeywordsChronic traumatic encephalopathyNeuropathologyMedicineAthletesPopulationHead injuryInternal medicineDiseaseConcussionPsychiatryPhysical therapyPoison controlInjury preventionEmergency medicine

Abstract

fetched live from OpenAlex

Chronic traumatic encephalopathy (CTE) has been described mainly in professional athletes and military personnel and is characterized by deposition of hyperphosphorylated tau at the depths of cortical sulci and around blood vessels. To assess CTE-like changes in a routine neuropathology service, we prospectively examined 111 brains (age 18-60 years). The presence of tau-immunoreactive deposits was staged using guidelines described by others and was correlated with the medical history. 72/111 cases were negative for CTE-like changes; 34/111 were CTE stage <1; 3/111 were CTE stage 1; and 2/111 were CTE stage 2. The combined history of head injury and alcohol and/or drug abuse was a significant predictor of any CTE-like changes. Age was also a significant predictor; most with any CTE-like changes were >40 years old. CTE-like changes were not identified at sites of contusion. Among a separate group studied retrospectively, we identified 4 cases that met full criteria for CTE. We conclude that CTE-like findings are not confined to professional athletes; the risk factors of head injury and substance abuse are similar in the routine population. However, the significance of very small hyperphosphorylated tau deposits remains to be determined. In addition, the absence of typical CTE-like deposits near contusion sites keeps open the question of pathogenesis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.329
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations69
Published2016
Admission routes1
Has abstractyes

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