Clinical Factors Associated with Bacterial Biofilm Formation in Chronic Rhinosinusitis
Bibliographic record
Abstract
OBJECTIVES: Bacterial biofilms appear to contribute to chronic rhinosinusitis. However, the mechanism behind biofilm formation in chronic rhinosinusitis remains poorly defined. The aim of this study is to evaluate clinical factors that may be associated with bacterial biofilm formation in chronic rhinosinusitis. STUDY DESIGN: Cross-sectional study. SETTING: Department of Otorhinolaryngology-Head and Neck Surgery at the Hospital of the University of Pennsylvania. SUBJECTS AND METHODS: Five hundred eighteen patients with chronic rhinosinusitis were enrolled from 2007 to 2010. Samples were taken to evaluate for biofilm formation in vitro using a modified Calgary Biofilm Detection Assay. Clinical data were collected from chart review. Pearson's χ(2) and logistic regression were used for the analyses. RESULTS: Of the patients, 108 (20.9%) showed biofilm formation in vitro. Bacterial biofilm formation in vitro was not significantly associated with polyps, allergy, Samter's triad, sleep apnea, smoking status, age, or gender. However, it was significantly associated with positive culture results (odds ratio [OR] = 3.13; 95% confidence interval [CI], 1.85-5.29; P < .001), prior sinus surgeries (1.93; 1.01-3.69; P = .046), and nasal steroid use in the month prior to sample collection (2.09; 1.07-4.08; P = .030). Polymicrobial cultures, Pseudomonas aeruginosa, and Staphylococcus aureus comprised most of the samples. CONCLUSION: The results of this study suggest that the probability of bacterial biofilm formation is independent of many clinical factors considered to be risk factors for chronic rhinosinusitis. Further studies are needed to clarify the nature of the associations between prior sinus surgeries, nasal steroid use, and biofilm formation.
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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) | 0.001 | 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 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".