Gram‐negative bacterial carriage in chronic rhinosinusitis with nasal polyposis is not associated with more severe inflammation
Bibliographic record
Abstract
BACKGROUND: We have previously demonstrated that persistent symptoms following functional endoscopic sinus surgery for chronic rhinosinusitis (CRS) is associated with Gram-negative bacterial carriage. Mechanisms for this remain unknown. We wished to determine whether Gram-negative carriage in patients with CRS with nasal polyposis is associated with a more severe inflammatory phenomenon. METHODS: Three hundred and thirty-seven patients with CRS with nasal polyposis (CRSwNP) previously phenotyped for genetic association studies with questionnaire, serum biomarkers, and endoscopically-obtained swab cultures were studied. These were separated according to the presence (wGN) or absence (sGN) of Gram-negative bacterial carriage; demographic parameters and available serum biomarkers (complete blood count [CBC], total immunoglobulin E [IgE]) were then compared. Subgroup analysis for Pseudomonas aeruginosa (GNwPa) and non-Pseudomonas Gram-negative bacteria (GNsPs) was performed in order to explore potentially differential roles of these bacteria. RESULTS: Gram-negative bacterial carriage was not associated with a difference in demographic parameters or serum biomarkers. However, P. aeruginosa carriage was associated with a higher self-reported incidence of asthma (GNwPa 79%, sGN 57%; p = 0.048). Interestingly, serum IgE was increased in the non-Pseudomonas Gram-negative population (GNsPs: 338 IU/mL, sGN: 195 IU/mL; p = 0.026). CONCLUSION: CRSwNP patients colonized with Gram-negative bacteria have a similar pattern of inflammation as assessed by serum biomarkers to those colonized with Gram-positive ones. Gram-negative bacteria may contribute to development of a T helper 2 (Th2) phenotype via other mechanisms, possibly via Toll-like receptor 4 (TLR4)-mediated interleukin 33 (IL-33) production. Differences in phenotype associated with Pseudomonas species carriage suggest a different behavior than other Gram-negative bacteria, supporting their importance as disease modifiers in CRSwNP.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".