Anatomic Findings in Revision Endoscopic Sinus Surgery: Case Series and Review of Contributory Factors
Bibliographic record
Abstract
BACKGROUND: It is recognized that patients who undergo endoscopic sinus surgery (ESS) do not always achieve control of their disease. The causes are multifactorial; variations in surgical practice have been identified as possible factors in refractory disease. OBJECTIVE: To reflect on the frequent anatomic findings of patients with chronic rhinosinusitis (CRS) who require revision ESS. METHODS: A retrospective review of patients who required revision ESS at a tertiary institution over a 3-year period. Patients for whom maximal medical therapy failed for CRS underwent computed tomography of the paranasal sinuses and image-guided surgery. Surgical records of anatomic findings were reviewed and analyzed. RESULTS: Over 3 years, a total of 75 patients underwent revision procedures, 28% of all ESS performed in the unit. The most frequent finding was a residual uncinate process in 64% of the patients (n = 48); other findings included a maxillary antrostomy not based on the natural ostium of the maxillary sinus in 47% (n = 35), an oversized antrostomy in 29% (n = 22), resected middle turbinates in 35% (n = 26), middle meatal stenosis in 15% (n = 11), synechiae in 29% (n = 22), and osteitic bone that required drilling in 13% (n = 10). CONCLUSION: Surgical technique can give rise to anatomic variations that may prevent adequate mucociliary clearance and medication delivery, which leads to failure in ESS in patients with CRS. This study demonstrated the surgical findings encountered in revision ESS that should be highlighted in the training of Ear, Nose and Throat surgeons to help prevent primary failure and reduce health care costs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".