Characterization of Polybacterial versus Monobacterial Conjunctivitis Infections in Pediatric Subjects Across Multiple Studies and Microbiological Outcomes with Besifloxacin Ophthalmic Suspension 0.6%
Bibliographic record
Abstract
Joseph M Blondeau,1 Howard M Proskin,2 Christine M Sanfilippo,3 Heleen H DeCory3 1Clinical Microbiology, Royal University Hospital, Saskatoon, SK, Canada; 2Howard M. Proskin & Associates, Rochester, NY, USA; 3Pharmaceutical Medical Affairs, Bausch + Lomb, Rochester, NY, USACorrespondence: Heleen H DeCoryPharmaceutical Medical Affairs, 1400 North Goodman Street, Rochester, NY, 14609, USATel +1 585 338-8161Email Heleen.DeCory@bausch.comIntroduction: The choice of empiric therapy for bacterial conjunctivitis should be guided by an awareness of typical causative pathogen distributions. Bacterial conjunctivitis can be polybacterial, although pediatric-specific data are lacking.Methods: This was a post-hoc analysis of data in pediatric subjects (1– 17 years) from five bacterial conjunctivitis trials evaluating besifloxacin ophthalmic solution 0.6%.Results: Of the 730 pediatric subjects with culture-confirmed conjunctivitis, nearly one-fourth (23.6%) had polybacterial infections and three-fourths (76.4%) had monobacterial infections at baseline. In both polybacterial and monobacterial infections, the most prevalent organisms were Haemophilus influenzae, Streptococcus pneumoniae, Staphylococcus aureus, and Streptococcus mitis/S. mitis group. In polybacterial versus monobacterial infections, S. mitis/S. mitis group (8.7% vs 4.3%; P=0.032) and Moraxella catarrhalis (4.7% vs 0.5%; P< 0.001) were identified more frequently, whereas S. pneumoniae (14.0% vs 28.1%; P< 0.001) was identified less frequently, as the dominant infecting species. MICs for individual species were similar for tested antibiotics regardless of polybacterial or monobacterial infection, except Staphylococcus epidermidis for which fluoroquinolone MICs were ≥ 3 dilutions higher for isolates of this species sourced from polybacterial compared to monobacterial infections. Treatment with besifloxacin resulted in microbial eradication in 79.1% of polybacterial and 92.3% of monobacterial infections (P≤ 0.005 vs vehicle).Discussion: One in four pediatric bacterial conjunctivitis infections is polybacterial, highlighting the need for a broad-spectrum antibiotic when choosing empiric therapy.Keywords: pediatric, conjunctivitis, polybacterial, besifloxacin, minimum inhibitory concentration
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".