Evaluation of 3-day azithromycin or 5-day cefaclor in comparison with 10-day amoxicillin for treatment of tonsillitis in children
Bibliographic record
Abstract
To evaluate the clinical efficacy of azithromycin, cefaclor, and amoxicillin in treatment of pediatric tonsillitis, a total of 256 children with Group A β-hemolytic streptococcus (GAS) tonsillitis were randomly divided into 3 groups. Only patients assessed with streptococcus-positive tonsillitis, considered to be compliant with treatment and complete clinical and microbiological evaluations at the end of therapy (day 14) and follow-up (day 30) were included in the efficacy analysis. Our study demonstrated that 96.4% of patients in the azithromycin group, 92.4% of patients in the cefaclor group, and 91.0% of patients in the amoxicillin group were recorded as clinical success at the end of therapy. Bacteriological eradication rates of the 3 groups at the end of therapy were 94.0%, 89.9%, and 88.5%, respectively. A pathogen recurrence rate was evaluated as 2.6%, 7.0%, and 5.9% at the follow-up. Treatment-stimulated adverse events occurred in 2.4% of patients in the azithromycin group, 11.3% in the cefaclor group, and 11.4% in the amoxicillin group. In summary, azithromycin showed an effective tendency for the treatment of pediatric tonsillitis with lower occurrence rate of adverse reactions, although there is no statistical significance for the clinical and bacteriological eradication efficacy between these 3 groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 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".