Treatment of post-traumatic brain injury using high-dose neurotrophic factors – a case report study
Bibliographic record
Abstract
Introduction. Post-traumatic brain injury (TBI) dementia is a serious neurodegenerative condition, with or without behavioral disturbances, that can dramatically change the quality of life of both patients and their caretakers, and without an available effective treatment, the prognosis of these patients is not favorable. Objective. The purpose of this case report study was to present the effects of the porcine brain-derivate hydrolysate (PBDH) in a severe case of post-TBI dementia and the gradual improvement of symptoms based on cognitive function tests. Methodology. A high-dose regimen of neurotrophic factors was initiated, consisting of PDBH 30 mL/administration, 10 days/month, for three months, while the treatment efficacy was monitored using the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Global Assessment of Functioning Scale (GAFS). Conclusions. Following the completion of the PBDH regimen, the patient registered an improvement in the cognitive function, from severe impairment to moderate impairment, and in the functionality as well. The same regimen will be repeated three months later to maintain or improve the current results, which reflected the efficacy of PBDH in post-TBI dementia.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".