Prognostic value of neuron-specific enolase (NSE) for prediction of post-concussion symptoms following a mild traumatic brain injury: a systematic review
Bibliographic record
Abstract
BACKGROUND: This systematic review aimed to determine the prognostic value of neuron-specific enolase (NSE) to predict post-concussion symptoms following mild traumatic brain injury (TBI). METHODS: Seven databases were searched for studies evaluating the association between NSE levels and post-concussion symptoms assessed ≥ 3 months (persistent) or ≥ 7 days < 3 months (early) after mild TBI. Two researchers independently screened studies for inclusion, extracted data and appraised quality using the Quality in Prognostic Studies (QUIPS) tool. RESULTS: The search strategy yielded a total of 23,298 citations from which 8 cohorts presented in 10 studies were included. Studies included between 45 and 141 patients (total 608 patients). The outcomes most frequently assessed were post-concussion syndrome (PCS, 12 assessments) and neuropsychological performance deficits (10 assessments). No association was found between an elevated NSE serum level and PCS. Only one study reported a statistically significant association between a higher NSE serum level and alteration of at least three cognitive domains at 2 weeks but this association was no longer significant at 6 weeks. Overall, risk of bias of the included studies was considered moderate. CONCLUSIONS: Early NSE serum level is not a strong independent predictor of post-concussion symptoms following mild TBI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".