Costs and Perioperative Outcomes Associated with Open versus Endoscopic Resection of Sinonasal Malignancies with Skull Base Involvement
Bibliographic record
Abstract
Background: Endoscopic approaches have been increasingly adopted in favor of traditional craniofacial resection in the surgical management of sinonasal malignancies. There is limited research comparing the costs, complications, and hospital length of stay (LOS) between surgical approaches, and no studies that have identified determinants of these outcomes. Methods: We performed a retrospective review of 106 patients at a tertiary care center undergoing surgical resection of a sinonasal malignancy. Financial data were obtained from our institution’s finance department. Linear regression was used to identify factors impacting in-hospital costs, complications, and LOS. Results: Of 106 patients, 91 received open surgery and 15 were treated with purely endoscopic approaches. There were no significant differences in cost ($19,157 versus $17,722; p = 0.69) or LOS (5.7 versus 7.4 days, p = 0.35) between the two groups. Patients in the endoscopic group had significantly higher rates of CSF leak (13% versus 1%, p < 0.01), hospital readmission (13% versus 3%, p < 0.04), and return to OR (13% versus 2%, p = 0.03). Multiple regression showed that free flap reconstruction was a significant predictor of costs, complications, and LOS ( p < 0.001, p = 0.001, and p = 0.04). Perioperative complication and ICU admission were also independently predictive of costs ( p < 0.001 and p < 0.001) and LOS ( p < 0.001 and p = 0.01). Surgical approach (open versus endoscopic) was not a significant predictor of any financial or perioperative outcome. Conclusion: Overall in-hospital costs are comparable between endoscopic and open approaches, and differences may be accounted for by higher rates of CSF leak in the endoscopic group. Physicians and policy makers should recognize the factors impacting financial and perioperative outcomes in the surgical management of sinonasal malignancies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".