Aminoglycoside-Induced Vestibular Injury: Maintaining a Sense of Balance
Bibliographic record
Abstract
OBJECTIVE: To describe the mechanism and risk factors for the development of aminoglycoside-induced vestibular injury and discuss their implications for therapeutic monitoring of aminoglycoside antibiotics. DATA SOURCES: A MEDLINE search (1975-January 2008) was performed to identify literature on aminoglycoside-induced vestibular injury and risk factors associated with this outcome and their impact on therapeutic drug monitoring. Additional references were identified through review of bibliographies of identified articles. STUDY SELECTION AND DATA EXTRACTION: Data on the mechanisms of vestibular toxicity and its development in association with aminoglycoside exposure were extracted from identified references. DATA SYNTHESIS: The mechanism leading to the development of irreversible vestibular injury from exposure to aminoglycosides appears to be through the excessive production of oxidative free radicals. This production and subsequent toxicity appears to be a time-dependent process and is unrelated to dose or serum concentration. For similarly designed studies, the pooled incidence of vestibular toxicity is 10.9% for gentamicin, 7.4% for amikacin, 3.5% for tobramycin, and 1.1% for netilmicin. Current evidence suggests that this form of drug toxicity is not restricted to traditionally dosed systemic therapy, since intraperitoneal administration, high-dose once-daily administration, topical inhalation, and eardrop administration have all been associated with the development of this adverse outcome. CONCLUSIONS: Given the lack of association between serum concentrations and vestibulotoxicity, it is imperative for the pharmacist to interview the patient and not focus solely on maintaining target range drug concentrations. Minimizing the duration of exposure to aminoglycosides is recommended to reduce the risk from this form of drug toxicity.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".