Steroids in aminoglycoside‐containing ear drops: Do they reduce cochlear toxicity?
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To determine whether betamethasone (BM) reduces the cochlear toxicity of otic gentamicin (GM) if given together. STUDY DESIGN: Controlled animal study. METHODS: Thirty-four mice were assigned at random to receive intratympanic injections of either 0.1 % BM (11 mice), 0.3% GM (13 mice), or a combination of both (GM/BM) with benzalkonium chloride (10 mice) in the left ear (treated) and saline on the right (untreated). Six injections were given on alternate days. Auditory brainstem response thresholds were assessed at 1 month, 2 months, and >2 months. RESULTS: There was a significantly greater degree of hearing loss in the BM-treated ears compared to the untreated ears (6.48 dB hearing loss, P = .007) and in the GM-treated ears compared to untreated ears (6.59 dB hearing loss, P = .010,). However, otic GM/BM and benzalkonium chloride did not cause significant additional hearing loss compared with the untreated ears (3.56 dB hearing loss, P = .242). CONCLUSIONS: Our data suggest that hearing loss caused by GM otic drops may be reduced by the inclusion of BM and benzalkonium chloride. Our finding that BM alone was associated with hearing loss suggests that the benzalkonium chloride may be the protective agent in combination otic drops.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".