Indications, Surgical Strategies And Hearing Outcomes of Revision Stapes Surgery for Otosclerosis: A Systematic Review and Meta‐analysis on 2602 Patients
Bibliographic record
Abstract
OBJECTIVE: To summarize current knowledge on the indications, surgical strategies, and auditory outcomes of revision stapes surgery (RSS) for otosclerosis. DATA SOURCES: The search was conducted in PubMed, Scopus, and Web of Science online databases, including papers published since 2000. REVIEW METHODS: The study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. We considered original series describing RSS for otosclerosis, reporting postoperative hearing outcomes according to the American Academy of Otolaryngology-Head and Neck Surgery guidelines for conductive hearing loss (CHL) for at least 30 consecutive cases. The quality of included studies was assessed with the Joanna Briggs Institute checklist. Pooled proportion and odds ratio (OR) meta-analysis were conducted using random effect models. RESULTS: Nineteen studies were included, for a total of 2602 patients (2735 ears) and 2359 postoperative hearing results. RSS was mostly performed for recurrent CHL with air-bone gap (ABG)>20 dB. Multiple concomitant causes were often present, with prosthesis placement defect and incus necrosis as the most common causes. The pooled proportion of postoperative ABG<10 dB and ABG<20 dB was 57.2% (95% confidence interval [CI]: 52.8%-61.4%) and 79% (95% CI: 76.0%-81.8%), respectively. Dead ears were 1.2% (95% CI: 0.7%-2.1%). Compared to primary surgery, RSS had a significantly lower rate of ABG<10 dB (OR = 0.36, 95% CI: 0.24%-0.54%; P < .001). Both revision incudostapedotomy with/without incus reconstruction and malleovestibulopexy are viable options with nonsignificant differences in ABG closure rates (P = .182). CONCLUSION: RSS is challenging and requires the surgeon to carefully evaluate all potential causes of previous failure and tailor the intervention according to intraoperative findings. In most cases, ABG closure within 20 dB can be achieved with a relatively low risk of dead ears.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.031 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".