Cross-Regional Comparison of Type 2 Inflammatory Markers in Chronic Rhinosinusitis With Nasal Polyposis: Insights From the Gulf Region and Canada
Bibliographic record
Abstract
Objective Chronic rhinosinusitis with nasal polyposis (CRSwNP) is prevalent worldwide, but regional variations in disease endotypes have been described. The Gulf region is unique in genetic background and environmental conditions, potentially influencing disease characteristics. This study aimed to compare phenotypic traits and serum biomarkers associated with type 2 disease between CRSwNP patients in the Gulf and Canada. Study design A retrospective observational study was conducted in a tertiary center in Dubai, comparing newly diagnosed CRSwNP patients from the United Arab Emirates (UAE), representative of the UAE, with two Canadian cohorts: severe chronic rhinosinusitis (CRS) patients, (Genetics of Chronic Rhinosinusitis 1 (GCRS1)) and CRSwNP patients (Genetics of Chronic Rhinosinusitis 2 (GCRS2)). Methods Serum eosinophilia, white blood cell (WBC), and immunoglobulin E (IgE) levels were analyzed to identify potential differences or similarities between the populations. Results Serum eosinophil counts and the percentage of subjects with high serum eosinophilia values (≥300 cells/µL) were similar across the UAE and Canadian groups. However, total serum IgE levels were higher in the UAE cohort, while reported allergy rates were significantly lower compared to the Canadian groups. Type 2 comorbidities were more frequently reported in the Canadian cohorts, potentially reflecting differences in diagnostic practices or patient reporting. Conclusion Despite environmental and population differences, the immunological profile of CRSwNP disease in the Gulf region closely mirrors that in North America, suggesting that management strategies developed and used in Western countries are applicable in the Gulf. Eosinophil screening in CRSwNP patients remains valuable to detect elevated levels, potentially indicative of vasculitis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".