Costs and Perioperative Outcomes Associated with Open versus Endoscopic Resection of Sinonasal Malignancies with Skull Base Involvement
Bibliographic record
Abstract
Objective To compare financial and perioperative outcomes between endoscopic and open surgical approaches in the surgical management of sinonasal malignancies. Design Retrospective chart review. Setting Tertiary care hospital. Participants Patients undergoing surgical resection of a sinonasal malignancy from January 2000 to December 2014. Main Outcome Measures In-hospital costs, complications, and length of stay (LOS). Results Of 106 patients, 91 received open surgery (19 free flap and 72 non-free flap) and 15 were treated with purely endoscopic approaches. Free flaps had a significantly higher average cost, operative time, and LOS compared to both non-free flap (p < 0.001, < 0.001, and < 0.01) and endoscopic (p = 0.01, 0.04, and < 0.01) groups. There were no significant differences in average costs between endoscopic and non-free flap groups ($19,157 vs. $14,806, p = 0.20) or LOS (5.7 vs. 6.4 days, p = 0.72). Compared with the non-free flap group, the endoscopic group had a longer average operative time (8.3 vs. 5.5 hours, p < 0.01) and higher rates of cerebrospinal fluid (CSF) leak (13 vs. 0%, p = 0.01) and intensive care unit (ICU) admission (80 vs. 36%, p < 0.01). Surgical approach (open vs. endoscopic) was not a significant predictor of any financial or perioperative outcome on multivariable analysis. Conclusion Hospital costs are comparable between endoscopic and open approaches when no free tissue reconstruction is required. Longer operative times, higher CSF leak rates, and our institutional protocol necessitating ICU admission for endoscopic cases may account for the failure to demonstrate cost savings with endoscopic surgery.
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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 | 0.006 |
| 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 | 0.001 | 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".