Could Hearing Loss Be Related to Delay in Administration of Other Antibiotics Rather Than Early Use of Vancomycin?
Bibliographic record
Abstract
To the Editor.—We read with interest the article “Early Vancomycin Therapy and Adverse Outcomes in Children With Pneumococcal Meningitis.”1 An unexpected finding was the association between hearing loss as a complication of meningitis and early administration of vancomycin relative to other antibiotics. The study showed that, “[a]mong children with hearing loss, the median vancomycin start time was <1 hour (interquartile range: 0–1.5 hours), whereas that of children without hearing loss was 4 hours (interquartile range: 1–12 hours; P < .0005). With increasing vancomycin start time, the proportion of tested children with hearing loss decreased in stepwise fashion: <1 hour, 18 (78%) of 23; 1 to 2 hours, 6 (67%) of 9; 2 to 5 hours, 3 (33%) of 9; >5 hours, 5 (28%) of 18 (P < .006).”Is it possible that the majority of the children who had hearing loss had, in fact, received vancomycin at 0 hour (ie, vancomycin was given before the other antibiotics)? Studies in adults have shown that delayed administration of appropriate antibiotics for severe infections and sepsis is strongly associated with poor outcome.2 If early vancomycin administration often reflected delayed administration of a β-lactam antibiotic with better cerebrospinal penetration than vancomycin, that could account for the findings of the study.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.014 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".