Intraoperative Bleeding and the Risk of Residual Cholesteatoma: A Multivariate Analysis
Bibliographic record
Abstract
OBJECTIVE: Residual cholesteatoma most frequently occurs where visualization and surgical access are restricted by anatomic constraints. Other factors that compromise surgical field visualization might also increase rates of residual cholesteatoma. We evaluated whether impaired surgical field clarity from bleeding increases rates of residual cholesteatoma. STUDY DESIGN: Prospective cohort study. SETTING: Tertiary care hospital. PATIENTS: Consecutive series of children having intact canal wall surgery for cholesteatoma. INTERVENTIONS: Impact of bleeding on surgical field clarity was assessed intraoperatively on a six-point scale. MAIN OUTCOME MEASURES: Presence of residual cholesteatoma was established at follow up clinical encounters, second stage procedures, and with magnetic resonance imaging. Multiple logistic regression was used to determine the influence of surgical field clarity and other factors on rates of residual cholesteatoma. RESULTS: Surgery was completed on 232 ears and residual cholesteatoma found in 45 (19%) ears. Multivariate regression analysis of cases completed with atticotomy or tympanoplasty demonstrated that surgical field clarity was a significant predictor of residual cholesteatoma (OR [odds ratio] 4, 95%CI 1.05-15; p = 0.04). Cholesteatoma extent was the most significant predictor of residual cholesteatoma when including cases requiring combined approach tympanomastoidectomy (OR 2.2, 95%CI 1.4-3.3; p < 0.001). CONCLUSIONS: Impaired surgical field clarity from intraoperative bleeding is associated with increased risk of residual cholesteatoma in surgery for meso/epitympanic cholesteatoma. These findings are of particular significance for endoscopic ear surgery in which management of bleeding can be more difficult and support the use of techniques, such as hypotensive general anesthesia, that minimize surgical site bleeding and improve surgical field visualization.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".