Non‐Type 2 and Mixed Inflammation in Chronic Rhinosinusitis and Lower Airway Disease
Bibliographic record
Abstract
OBJECTIVE: The aim was to discuss the role of non-type 2 inflammation in patients diagnosed with chronic rhinosinusitis (CRS) and comorbid lower airway disease. DATA SOURCES: Medline, Embase, National Institute for Health and Care Excellence, TRIP Database, ProQuest, Clinicaltrials.gov, Cochrane Central Registry of Controlled Trials, Web of Science, government and health organizations, and graduate-level theses. REVIEW METHODS: This scoping review followed PRISMA-ScR guidelines. Search strategy was peer-reviewed by medical librarians. Studies were included if they utilized airway sampling, non-type 2 cytokines, and patients with CRS and lower airway disease. RESULTS: Twenty-seven from 7060 articles were included. In patients with CRS and comorbid asthma, aspirin-exacerbated respiratory disease (AERD), and chronic obstructive pulmonary disease (COPD)/bronchiectasis, 60% (n = 12), 33% (n = 2), and 100% (n = 1), respectively, demonstrated mixed or non-type 2 endotypes. Comorbid CRS and asthma produced type 1 (n = 1.5), type 2 (n = 8), type 3 (n = 1), mixed type 1/2 (n = 1), and mixed type 1/2/3 (n = 8.5) endotype shifts. AERD demonstrated type 2 (n = 4), mixed type 2/3 (n = 1), and mixed type 1/2/3 (n = 1) endotype shifts. CRS with COPD or bronchiectasis demonstrated a mixed 1/2 (n = 1) endotype shift. CONCLUSION: Type 2 disease has been extensively reviewed due to advent biologics targeting type 2 inflammation, but outcomes may be suboptimal due to the presence of non-type 2 inflammation. A proportion of patients with CRS and comorbid lower airway disease demonstrated mixed and non-type 2 endotype shifts. This emphasizes that patients with unified airway disease may have forms of inflammation beyond classical type 2 disease which could inform biologic development. Laryngoscope, 134:1005-1013, 2024.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".