Symptom Reporting Compared with Audiometry for the Detection of Cochleotoxicity in Patients on Long-Term Aminoglycoside Therapy
Bibliographic record
Abstract
BACKGROUND: Aminoglycoside-associated auditory toxicity (cochleotoxicity) is a major concern in patients receiving prolonged aminoglycoside therapy. There are no published data comparing symptom monitoring to audiometry testing for the detection of aminoglycoside-induced cochleotoxicity; thus, agreement regarding the optimal monitoring of these patients for early detection of this effect is lacking. OBJECTIVE: To compare the sensitivity of symptom monitoring to that of audiometry in identifying cochleotoxicity in patients on prolonged aminoglycoside therapy. METHODS: A retrospective chart review of adult inpatients at Sunnybrook Health Sciences Centre prescribed prolonged aminoglycoside therapy (≥21 days) who completed at least 1 audiometry test between January 1, 1999, and December 31, 2009, was conducted. Data pertaining to results of audiometry testing and development of symptoms of auditory toxicity were collected. Symptom monitoring was compared with audiology testing for the detection of cochleotoxicity. RESULTS: Forty eligible patients were included for analysis. Audiometry was significantly better than symptom monitoring to identify early cochleotoxicity (absolute risk reduction = 17.5% and number needed to treat = 6; p = 0.023). Compared to audiometry, symptom monitoring has a sensitivity, negative predictive value, and accuracy for the detection of early cochleotoxicity of 61%, 75%, and 82%, respectively. CONCLUSIONS: Audiometry testing is significantly better than monitoring symptoms to identify early aminoglycoside-induced auditory toxicity in patients prescribed prolonged aminoglycoside therapy (≥21 days). Subclinical cochleotoxicity identified with audiometry may allow early termination of aminoglycoside therapy to prevent progression of cochlear damage to the audible frequency range.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".