Correlation of Pituitary Descent and Diabetes Insipidus After Transsphenoidal Pituitary Macroadenoma Resection
Bibliographic record
Abstract
BACKGROUND: Endoscopic transsphenoidal surgery remains the technique of choice for resection of pituitary adenoma. Postoperative diabetes insipidus (DI) is most often transient and observed in 1.6% to 34% of patients, whereas permanent DI has been reported in 0% to 2.7% of patients. The proposed mechanism was the transduction of traction forces exerted by the surgeon on the descended diaphragma sellae and through the pituitary stalk. OBJECTIVE: To quantify and correlate the degree of pituitary gland descent with postoperative DI. METHODS: Of 374 patients who underwent transsphenoidal resection of a pituitary adenoma between 2010 and 2020 at our institution, we report a cohort of 30 patients (Group A) DI. We also report a matched cohort by tumor volume of 30 patients who did not develop DI (Group B). We quantified the tension on the pituitary stalk by calculating pituitary descent interval (PDI) by comparing preoperative and postoperative position of the pituitary gland and using Pythagoras' formula where , with craniocaudal (CC) and anterior-posterior (AP) representing measurements of pituitary translation in respective directions after resection. RESULTS: Patients who developed DI had significantly greater pituitary gland translations in the craniocaudal (23.0 vs 16.3 mm, P = .0015) and anteroposterior (2.4 vs 1.5 mm, P = .0168) directions. Furthermore, Group A had a statistically greater PDI, which was associated with development of DI (23.2 vs 16.6 mm, P = .0017). CONCLUSION: We were able to quantify pituitary descent and subsequent tension on the pituitary stalk, while also associating it with development of postoperative DI after pituitary adenoma resection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".