Olfactory outcomes after endoscopic transsphenoidal pituitary surgery
Bibliographic record
Abstract
BACKGROUND: Olfaction has been demonstrated to have a great impact on patients' lives. Transsphenoidal endoscopic pituitary surgery is associated with potentially significant damage to olfactory tissues, but to date this issue has been only poorly documented in the literature. STUDY DESIGN: Prospective cohort study comparing olfactory outcomes pre- and postpituitary surgery. METHOD: Patients were administered the University of Pennsylvania Smell Identification Test (UPSIT) preoperatively and again at 6 months postoperatively. The endoscopic transsphenoidal pituitary surgery was carried out using a full middle turbinate preservation protocol. A Hadad-Bassagasteguy (HB) vascularized septal flap was raised in each case. Secondary outcomes included Lund-Kennedy endoscopy scores (LKES) and patient self-report of olfactory disturbance. The results were analysed using a paired t-tests. RESULTS: Seventeen patients met inclusion criteria for the study. Mean preoperative UPSIT value was 37.2 (normosmia), and mean postoperative UPSIT value was 30.8 (moderate hyposmia) (P < .001). All patients were fully healed with normal LKES scores by 6 months. All patients complained of their olfactory dysfunction. CONCLUSIONS: This study is the first to describe postoperative olfactory perturbations suffered by patients undergoing endoscopic transsphenoidal pituitary surgery. We hypothesize that olfactory impairment results from use of the HB flap. We recommend that the possibility of permanent olfactory changes be added to routine patient counseling and consent for this procedure, and that HB flaps be raised judiciously during trannssphenoidal endoscopic procedures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".