Recommendations for Diagnosing a Mild Traumatic Brain Injury: A National Academy of Neuropsychology Education Paper
Bibliographic record
Abstract
A special interest group of the American Congress of Rehabilitation Medicine [ACRM; Mild Traumatic Brain Injury Committee. (1993). Definition of mild traumatic brain injury. Journal of Head Trauma Rehabilitation, 8 (3), 86-87.] was the first organized interdisciplinary group to advocate four specific criteria for the diagnosis of a mild traumatic brain injury (TBI). More recently, the World Health Organization (WHO) Collaborative Center Task Force on Mild Traumatic Brain Injury [Carroll, L. J., Cassidy, J. D., Holm, L., Kraus, J., & Coronado, V. G. (2004). Methodological issues and research recommendations for mild traumatic brain injury: the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. Journal of Rehabilitation Medicine, (Suppl. 43), 113-125.] conducted a comprehensive review of the definitions utilized in evidence-based studies with mild TBI patients. Based on this review, the WHO task force maintained the same four criteria but offered two modifications. The similarities and differences between these two definitions are discussed. The authors of the ACRM and the WHO definitions do not provide guidelines or specific recommendations for diagnosing the four criteria. Thus, we provide recommendations for assessing loss of consciousness, retrograde and post-traumatic amnesia, disorientation and confusion as well as clarification of the neurologic signs that can be indicative of a diagnosis of mild TBI. Finally, confounding factors mentioned in both definitions that should exclude a mild TBI diagnosis are summarized.
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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 | 0.043 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.012 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.015 | 0.016 |
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".