Pituitary Dysfunction in Idiopathic Intracranial Hypertension: An Analysis of 80 Patients
Bibliographic record
Abstract
BACKGROUND: Empty sella is a commonly described imaging entity in patients with idiopathic intracranial hypertension (IIH). Though menstrual and hormonal disturbances have been associated with IIH, available literature lacks systematic analysis of pituitary hormonal disturbances in IIH. More so, the contribution of empty sella in causing pituitary hormonal abnormalities in patients of IIH has not been described. We carried out this study to systematically assess the pituitary hormonal abnormalities in patients with IIH and its relation to empty sella. METHODS: Eighty treatment naïve patients of IIH were recruited as per a predefined criterion. Magnetic resonance imaging (MRI) brain with detailed sella imaging and pituitary hormonal profile were done in all patients. RESULTS: Partial empty sella was seen in 55 patients (68.8%). Hormonal abnormalities were detected in 30 patients (37.5%), reduced cortisol levels in 20%, raised prolactin levels in 13.8%, low thyroid-stimulating hormone (TSH) levels in 3.8%, hypogonadism in 1.25%, and elevated levels of gonadotropins were found in 6.25% of participants. Hormonal disturbances were independent and were not associated with the presence of empty sella (p = 0.493). CONCLUSION: Hormonal abnormalities were observed in 37.5% patients with IIH. These abnormalities did not correlate with the presence or absence of empty sella. Pituitary dysfunction appears to be subclinical in IIH and responds to intracranial pressure reduction, not requiring specific hormonal therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".