In-Hospital Endocrinology Consultation After Transsphenoidal Surgery: Is It Always Necessary?
Bibliographic record
Abstract
BACKGROUND: Patients with sellar masses undergoing transsphenoidal surgery (TSS) frequently develop endocrine dysfunction; therefore, in-hospital endocrinology consultation (IHEC) is recommended. However, we wondered whether routine endocrinology assessment of all TSS patients is always necessary. METHODS: We developed an IHEC Physician's Guide to identify patients who would require peri-operative IHEC. An analysis of all patients undergoing TSS for a sellar mass over a 4-year period was conducted to assess the predictive value of the IHEC Physician's Guide in identifying patients who required IHEC. RESULTS: A total of 116 patients underwent TSS; 24 required IHEC. As expected, the risk of endocrine complications requiring peri-operative endocrine management was significantly higher in the IHEC group versus no-IHEC group (96% vs. 1%; p < 0.001). The negative predictive value of the IHEC Physician's Guide in identifying patients who did not require IHEC was 0.99 (95% CI 0.9409-0.9997); Fisher's exact test, p < 0.001), meaning that the IHEC Physician's Guide successfully identified all but one patient who truly required IHEC. CONCLUSION: Results from our study show that most patients do not need IHEC after TSS and that those patients requiring IHEC can be reliably predicted at surgery by using a simple IHEC Physician's Guide.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".