Biofilm and Planktonic Antibiotic Resistance in Patients With Acute Exacerbation of Chronic Rhinosinusitis
Bibliographic record
Abstract
INTRODUCTION: The recalcitrant nature of patients with acute exacerbation of chronic rhinosinusitis (AECRS) potentially involves persisting colonization of the sinonasal mucosa by bacterial biofilms. Biofilms are known to be highly resistant to antibiotics, which may trigger or maintain chronic inflammation in the sinonasal mucosa. However, little is known about the relationship between the minimum inhibitory concentration (MIC) and antibiofilm concentrations of bacteria obtained from AECRS patients. MATERIAL AND METHODS: formation of biofilms (Modified Calgary Biofilm Device) and determination of minimum biofilm inhibitory concentration (MBIC) and minimum biofilm eradication concentration (MBEC) for amoxicillin, amoxicillin/clavulanic acid, clarithromycin, and levofloxacin. MIC of the planktonic forms was compared with MBIC and MBEC levels, according to the breakpoints established by the Clinical Laboratory Standards Institute guidelines. RESULTS: (n=23/30). The planktonic isolates presented high rates of resistance for amoxicillin (82.6%) and clarithromycin (39.1%), and lower rates for amoxicillin/clavulanic acid (17.4%). The biofilm-forming bacteria counterparts presented higher levels of MBIC and MBEC compared to the MIC levels for amoxicillin, amoxicillin/clavulanic acid, and clarithromycin. Levofloxacin was highly effective against both planktonic and biofilm forms. Planktonic resistant forms were associated with levels of antibiofilm concentrations (MBIC and MBEC). CONCLUSIONS: Biofilm-forming bacteria from AECRS patients are prevalent, and biofilm forms are highly resistant to antibiotics compared to their planktonic counterparts. Antibiotic resistance observed in planktonic forms is a good indicator of biofilm resistance, although near 20% of susceptible planktonic bacteria can produce antibiotic tolerant biofilms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".