Associations between Serum Tau, Neurological Outcome, and Cognition following Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: To investigate the dynamic change in the serum Tau protein early after acute traumatic brain injury (TBI) and its association with neurological outcome and cognitive function. SUBJECTS AND METHODS: Around 229 patients with acute TBI and 30 healthy subjects were evaluated for the serum levels of Tau protein on 1, 3, 5, 7, and 14 days after TBI. The relationships of the serum levels of Tau protein and initial GCS and GOS at 6 months post-injury were also analyzed. Further, 95 TBI patients were assessed with their cognitive function with Montreal cognitive assessment (MoCA) score. RESULTS: Serum Tau was significantly higher in patients with TBI at 1, 3, 5, 7, and 14 days. The serum Tau at each point was significantly lower respectively in the patients with mild TBI than that in medium and severe TBI. The serum Tau was significantly lower in patients with good outcome compared to the poor outcome group. The early serum Tau was negatively correlated with both GCS and GOS. In the TBI group, 39 (41%) out of 95 patients developed cognitive dysfunction assessed by MoCA. Tau protein at day 1, 3, and 5 after TBI was significantly correlated with cognitive dysfunction at 6 months after TBI. CONCLUSIONS: Acute Tau associations with neurological outcomes and cognition may implicate white matter damage and neuronal degeneration. Serum Tau may be used as a reliable biological marker for early diagnosis and cognitive recovery following TBI.
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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) | 0.001 | 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".