Assessment of a Lateral Nasal Wall Block Technique for Endoscopic Sinus Surgery Under Local Anesthesia
Bibliographic record
Abstract
Introduction With increasingly limited operative resources and patient desires for minimally invasive procedures, there is a trend toward local endoscopic procedures being performed in the outpatient clinic setting. However, there remain limited data supporting a technique to adequately anesthetize the lateral nasal wall and provide patient comfort during these procedures. The objective of this study is to assess the efficacy of a novel lateral nasal wall block for use in office-based endoscopic sinus surgery. Methods A prospective cohort study assessing consecutive patients undergoing office-based endoscopic sinus surgery using our described lateral nasal wall block anesthesia technique. Procedural patient comfort was assessed using the Iowa Satisfaction with Anesthesia Scale (ISAS), completed by participants immediately following an office-based endoscopic procedure and prior to discharge from clinic. Postoperative analgesic use was assessed at the first postoperative visit. Results Thirty-five consecutive patients undergoing office-based outpatient endoscopic sinus surgery for chronic rhinosinusitis (with and without polyps) were assessed. The mean ISAS score was 2.83 (95% confidence interval: [2.69, 2.97]). All participants (100%) agree or strongly agree that they were satisfied with their anesthesia care and would want the same anesthetic again. No participant required narcotic analgesia, and 80% used no oral analgesia following the procedure. Conclusions Recent advances in office-based endonasal surgical procedures must be accompanied by the assessment and validation of local anesthetic techniques. The described novel lateral nasal wall block is well tolerated, provides patient satisfaction, and allows for limited use of postprocedure oral analgesics.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".