Endotypes of chronic rhinitis: A cluster analysis study
Bibliographic record
Abstract
BACKGROUND: Chronic rhinitis (CR) is currently regarded as a syndrome, which presents as several endotypes. The aim of this study was to identify the CR endotype clusters and investigate the inflammatory patterns associated with the different endotypes. METHODS: A total of 259 CR patients and 20 control subjects were enrolled in this prospective study. Twelve clinical variables were analyzed using cluster analysis and five inflammatory variables were measured to investigate the inflammatory patterns associated with the different clusters. RESULTS: Six endotype clusters of CR were defined in the Chinese CR patients. Patients in cluster 1 (38.6%) were diagnosed as allergic rhinitis (AR) without asthma, and in cluster 2 (13.5%) as AR with asthma, with all demonstrating positive results for local eosinophils and high levels of local and serum IgE. Similarly, patients in cluster 3 (18.6%) were diagnosed as nonallergic rhinitis with eosinophilia syndrome (NARES) without asthma and in cluster 5 (5.0%) as NARES with asthma, with all demonstrating positive results for local eosinophils, and negative results for both local and serum IgE. Patients in cluster 4 (4.6%) were diagnosed as local allergic rhinitis and showed positive results for local eosinophils and local IgE, but negative results for serum IgE, whereas patients in cluster 6 (19.7%) were diagnosed as idiopathic rhinitis because of high symptoms scores, but negative findings for local eosinophils, local IgE, and serum IgE. CONCLUSIONS: Chinese CR patients may be clustered into six endotypes with different inflammatory patterns, which may help in delivering individualized treatment.
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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".