Histologic study of the human pituitary gland in acute traumatic brain injury
Bibliographic record
Abstract
PURPOSE: Approximately 25% of patients with traumatic brain injury (TBI) may develop partial or complete hypopituitarism. The causative mechanisms involved in its development are not clear. To the authors' knowledge, there have been no recent morphologic studies of the pituitary following TBI. METHODS: To characterize the resultant histologic changes, this study investigated the pituitaries of 42 patients who died following a motor vehicle accident, all from the Mayo Tissue Registry. Twelve patients died instantly at the scene of the accident (Group I) whereas 30 survived between 3 hours and 7 days (Group II). All pituitary specimens were obtained at autopsy, formalin-fixed and paraffin-embedded. Hematoxylin-eosin sections cut in horizontal or sagittal plane were examined light-microscopically. RESULTS: No infarction was noted in the pituitary specimens from group I. In group II, 13 of 30 (43%) showed acute infarcts of varying size. The extent of infarction in group II ranged from focal to sub-total necrosis involving 90% of the adenohypophysis. CONCLUSIONS: Underlying adenohypophysial pathology in patients dying after TBI is acute infarction. Loss of large numbers of adenohypophysial cells causes reduced secretion of adenohypophysial hormones and may contribute to post-traumatic hypopituitarism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".