Prevalence of polyp recurrence after endoscopic sinus surgery for chronic rhinosinusitis with nasal polyposis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Chronic rhinosinusitis with nasal polyposis (CRSwNP) is a disease process that is driven, in part, by intrinsic mucosal inflammation. Surgery plus continued medical therapy is commonly elected by medically recalcitrant, symptomatic patients. The objective was to evaluate the prevalence of nasal polyp recurrence up to 18 months after endoscopic sinus surgery (ESS) with congruent continuing medical management. STUDY DESIGN: Prospective, multicenter cohort of adult patients undergoing ESS for medically recalcitrant CRSwNP performed between August 2004 and February 2015. METHODS: All patients received baseline nasal endoscopy quantified using Lund-Kennedy grading. All patients included for final analysis provided at least 6 months of postoperative endoscopy examinations. Multivariate analysis was used to identify risk factors for polyp recurrence. RESULTS: Three hundred sixty-three CRSwNP patients having undergone ESS involving polypectomy were enrolled. A total of 244 (67%) participants had graded postoperative endoscopies with average of follow-up of 14.3 ± 7.0 months. Surgery plus postoperative medical management significantly improved endoscopy total scores at 6 months (P < .001). The recurrence of nasal polyposis 6 months after ESS was 35% (68/197), compared to 38% (48/125) after 12 months, and 40% (52/129) after 18 months. Multivariate analysis identified both prior ESS (odds ratio [OR]: 2.6, 95% confidence interval [CI]: 1.5-4.6; P = .001) and worse preoperative polyposis severity (OR: 1.4, 95% CI: 1.1-1.8; P = .016) as risk factors for recurrent polyposis. CONCLUSIONS: Polyp recurrence is common after ESS with control of polyps up to 18 months found in approximately 60% to 70% of patients. Investigation into both surgical and medical management strategies is warranted to improve upon the observed prevalence of recurrence. LEVEL OF EVIDENCE: 2c. Laryngoscope, 127:550-555, 2017.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".