Chlorhexidine ototoxicity in ear surgery, part 1: review of the literature.
Bibliographic record
Abstract
OBJECTIVE: Chlorhexidine is a common antiseptic used to prevent surgical infection. However, its exposure to the middle ear may lead to deafness. The mechanisms of the ototoxicity of chlorhexidine are reviewed. The importance of recognizing its toxicity cannot be overstated in preventing injury to patients undergoing ear surgery. METHODS: A systematic literature search was performed looking at data from human and animal studies. Search engines included MEDLINE, EMBASE, The Cochrane Library, CENTRAL, CINAHL, and Web of Science to November 1, 2010, for relevant studies published in all languages. Two independent reviewers (P.L. and D.D.P.) screened the references from published articles for additional relevant studies. Medical Subject Headings and key words including intervention (chlorhexidine, antiseptic), exposure (myringoplasty, intratympanic), and adverse effects (sensorineural hearing loss, ototoxicity, vestibular toxicity) were used. RESULTS: Twelve studies were identified, two of which were non-English and were excluded. Only 2 articles on human subjects and 12 articles on animal models concerning chlorhexidine ototoxicity were identified. CONCLUSIONS: Chlorhexidine in both human studies and animal models demonstrates ototoxicity if it reaches the inner ear. The toxicity of chlorhexidine appears to be related to its concentration and probable contact time with the round window membrane intraoperatively. It is conceivable that the incidence of chlorhexidine toxicity may be higher than stated if unrecognized or has resulted in subsequent medicolegal actions. From the evidence available, safer preparation solutions are available without clinical risks for ototoxicity should surgeons continue with this practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".