Evidence map›Paper›PMID 42500106›Full record

ArticleWorld journal of otorhinolaryngology - head and neck surgery2025

Distinct Nasal Microbiome Profiles and Prediction Model for Allergic Rhinitis, Nonallergic Rhinitis, and Healthy Children.

Kantima Kanchanapoomi, Iyarit Thaipisuttikul, Perapon Nitayanon, Witchaya Srisuwatchari, Punchama Pacharn, Nualanong Visitsunthorn, Orathai Jirapongsananuruk

Abstract read
In one paragraph

Article in World journal of otorhinolaryngology - head and neck surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

7 authors.

Kantima KanchanapoomiDivision of Allergy and Clinical Immunology, Department of Pediatrics, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Iyarit ThaipisuttikulDepartment of Microbiology, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Perapon NitayanonDepartment of Microbiology, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Witchaya SrisuwatchariDivision of Allergy and Clinical Immunology, Department of Pediatrics, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Punchama PacharnDivision of Allergy and Clinical Immunology, Department of Pediatrics, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Nualanong VisitsunthornDivision of Allergy and Clinical Immunology, Department of Pediatrics, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.
Orathai JirapongsananurukDivision of Allergy and Clinical Immunology, Department of Pediatrics, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand.ORCID https://orcid.org/0000-0002-1603-1106

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Adult studies reported differences in nasal microbiota composition among patients with allergic rhinitis (AR), nonallergic rhinitis (NAR), and healthy controls (HCs), whereas pediatric data remain limited. This study compared the nasal microbiomes of children with AR, NAR, and HC, investigated factors influencing these microbiomes, and developed a predictive model to differentiate these conditions based on microbiome data. Methods: Nasal swab samples were collected from children with AR, NAR, and HC. Microbial characterization was performed using 16S rDNA sequencing to analyze bacterial composition. Relevant demographic data and influencing factors were collected. Results: Sixty participants (median age 6.3 [4.3-8.4] years, 51.6% males) were categorized into AR ( Conclusion: This pilot study identified preliminary differences in nasal microbiome diversity and composition among children with AR, NAR, and HC. Differential microbial abundances may reflect distinct rhinitis phenotypes. However, these findings are hypothesis-generating and require validation in larger, independent cohorts.

Indexed as

allergic rhinitischildrenmachine learningmicrobial diversitymicrobiomenonallergic rhinitis

Identifiers

PMID42500106
PMCPMC13398806

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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 OpenQuestion graph.