Evidence map›Paper›PMID 42587833›Full record

ReviewCells2026

Clinical-Cytological Grading in Chronic Rhinosinusitis with Nasal Polyps: An Integrated Framework for Precision Medicine.

Matteo Gelardi

Abstract readReview
In one paragraph

Review in Cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Matteo GelardiUnit of Otolaryngology, Department of Clinical and Experimental Medicine, University of Foggia, Viale Luigi Pinto 1, 71122 Foggia, Italy.ORCID 0000-0003-4406-0008

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous inflammatory disease in which type 2 inflammation, epithelial dysfunction, and tissue remodeling determine severity, recurrence, and treatment response. Although molecular biomarkers have clarified disease endotypes, their routine use remains limited by cost, availability, and invasiveness. Nasal cytology offers a simple, repeatable, and minimally invasive method to assess-at the mucosal surface-both epithelial morphology and the dominant inflammatory infiltrate, whether neutrophilic, eosinophilic, mast cell, or mixed. Clinical-Cytological Grading (CCG) integrates the dominant cytological pattern with selected comorbidities, including asthma, allergy, and NSAID-exacerbated respiratory disease (N-ERD), into a weighted clinical-cytological framework. In the founding cohort, the highest relapse association was observed when mixed eosinophil-mast cell inflammation coexisted with asthma and N-ERD. This review discusses the rationale, clinical relevance, and translational applications of CCG in CRSwNP, addressing eosinophilic and mixed mast cell-eosinophilic inflammation, epithelial morphology, disease recurrence, difficult-to-treat phenotypes, biologic monitoring, and the operative dialogue between nasal cytology and histopathology. By linking cytological findings with selected clinical comorbidities, CCG may support biologically informed patient characterization and may prompt targeted mast cell assessment in tissue. However, its prognostic accuracy, incremental clinical value, and role in therapeutic decision-making require independent external validation.

Indexed as

Nasal PolypsPrecision MedicineRhinosinusitisSinusitisChronic DiseaseEosinophilsHumansMast Cellsallergyasthmabiologic therapychronic rhinosinusitis with nasal polypsClinical-Cytological Gradingeosinophilsmast cellsnasal cytologyNSAID-exacerbated respiratory diseaserecurrence

Identifiers

PMID42587833
PMCPMC13464912

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.