Extent of Surgery in Endoscopic Transsphenoidal Skull Base Approaches and the Effects on Sinonasal Morbidity
Bibliographic record
Abstract
BACKGROUND: Endoscopic transsphenoidal skull base surgery (ETSS) is now considered the criterion standard approach for resection of pituitary adenomas and other midline anterior skull base lesions. Normal sinonasal structures are resected during ETSS, which raises concerns for nasal morbidity and patient-based outcome. OBJECTIVE: To perform a surgical outcome assessment by examining whether the extent of ETSS approaches affected patient-specific sinonasal quality of life as measured by the 22-item Sino-Nasal Outcome Test (SNOT-22). METHODS: A single-center prospective cohort study of patients operated on by the same skull base team between 2012 and 2016. Patients with completed pre- and postoperative SNOT-22 were included. The primary outcome was SNOT-22 scores at preoperative, 0-1 month, 2-4 months, >5 months follow-up. Age, sex, tumor pathology, surgical procedure, and intraoperative cerebral spinal fluid leak repair were also obtained. RESULTS: Of the 249 ETSS performed, 148 patients (59%) had at least one completed SNOT-22; 45 (18%) met the inclusion criteria. Sinonasal quality of life based on SNOT-22 at the 0-1-month follow-up was significantly worse than the presurgical levels (p < 0.05). However, there was a return of SNOT-22 scores to preoperative levels at 2-4 months (p > 0.05), which was sustained at >5 months (p > 0.05). Factors such as the extent of ETSS, a previous nasal surgery, repair of an intraoperative cerebral spinal fluid leak, and the tumor pathology did not affect SNOT-22 scores at any follow-up intervals (p > 0.05). CONCLUSION: Sinonasal quality of life worsened after ETSS at 0-1 month follow-up but returned to preoperative levels at 2-4 months and remained at postoperative levels >5 months. Analysis of these data will allow us to educate our patients that the anticipated nasal morbidity after ETSS is usually only transient and should be expected to recover to preoperative levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".