Biofilm Formation by <i>Staphylococcus Aureus and Pseudomonas Aeruginosa</i> is Associated with an Unfavorable Evolution after Surgery for Chronic Sinusitis and Nasal Polyposis
Bibliographic record
Abstract
OBJECTIVES: To determine whether biofilm-forming capacity of bacteria demonstrated in chronic rhinosinusitis (CRS) has an impact on persistence of the disease following endoscopic sinus surgery (ESS). METHOD: Thirty-one bacterial strains recovered from 19 patients with CRS at least 1 year post-ESS. Evolution of disease was assessed by questionnaire and endoscopy as favorable or unfavorable. The bacteria were cultured on a 96-well culture plaque and a semi-quantitative method using crystal violet to quantify biofilm production was used. RESULTS: Twenty-two of 31 samples produced a biofilm thicker or equal to the positive control. Biofilm production was noted in 6/10 Pseudomonas aeruginosa isolates, 8/10 Staphylococcus aureus, and 8/11 coagulase-negative staphylococci. Biofilm formation was associated with a poor evolution for Pseudomonas aeruginosa and Staphylococcus aureus, but not coagulase-negative staphylococcus. CONCLUSION: There is a correlation between in vitro biofilm-producing capacity by Pseudomonas aeruginosa and Staphylococcus aureus and unfavorable evolution after ESS, suggesting a role for biofilm production in chronic sinusitis. EBM RATING: B-2b.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".