Pituitary injury and persistent hypofunction resulting from a peripartum non-hemorrhagic, vaso-occlusive event
Bibliographic record
Abstract
UNLABELLED: Cerebral vascular accidents are caused by vasospasm when induced by preeclampsia or by dopamine agonists. However, six arteries nourish the pituitary and prevent against vasospasm-induced damage, which up until now has not been thought to occur. Bromocriptine was used to arrest lactation in a 31-year-old with secondary amenorrhea following preeclampsia and fetal demise at 28 weeks gestation. Tests and history revealed panhypopituitarism not associated with hemorrhage or mass infarction but instead caused by vasospasm. The present study is the first report of pituitary damage from a non-hemorrhagic, vaso-occlusive event in the literature. In keeping with Sheehan's and Simon's syndromes, we have named pituitary damage resulting from vaso-occlusion as Dahan's syndrome, and a literature review suggests that it may be a common and previously overlooked disorder. LEARNING POINTS: Vasospasm can cause damage to the pituitary gland, although it was not previously believed to do so.Preeclampsia and the use of a dopamine agonist, particularly in the peripartum state, may trigger vasospasm.Vasospasm resulting from dopamine agonists may be a common cause of injury to the pituitary gland, and it may have been overlooked in the past.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".