Telithromycin for the Treatment of Acute Bacterial Maxillary Sinusitis: A Review of a New Antibacterial Agent
Bibliographic record
Abstract
OBJECTIVE: Telithromycin, the first approved ketolide antibiotic, was developed to treat community-acquired respiratory tract infections, including acute bacterial maxillary sinusitis (ABMS). A previously published study showed that a 5-day course of 800 mg telithromycin once daily is as effective as a 10-day course in the treatment of ABMS. MATERIALS AND METHODS: Data were pooled from two controlled, multinational, prospective, randomized, double-blinded ABMS trials comparing 5-day telithromycin (800 mg once daily) with 10-day amoxicillin-clavulanate (500/125 mg 3 times daily) and cefuroxime axetil (250 mg twice daily). Clinical cure and bacteriologic eradication rates were compared by means of descriptive statistics. RESULTS: The clinical cure rate for telithromycin was 80.9% versus 77.4% for comparators; bacteriologic eradication rate for telithromycin was 84.9% versus 81.7% for comparators. Most adverse events were mild to moderate in intensity and, most commonly, gastrointestinal in nature. CONCLUSIONS: These results support the conclusion that 5 days of treatment with telithromycin is as safe and effective in patients with ABMS as a 10-day course of treatment with amoxicillin-clavulanate or cefuroxime axetil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".