Evidence map›Paper›PMID 42836257›Full record

ArticleLaryngoscope investigative otolaryngology2026

Airflow Characteristics of Empty Nose Syndrome: Insights From Patient-Specific Computational Modeling of Airflow Distribution Patterns and Nasal Air-Conditioning.

Yang Na, Kyung Won Kwon, Yong Ju Jang

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Article in Laryngoscope investigative otolaryngology, 2026. 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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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yang NaDepartment of Mechanical Engineering Konkuk University Seoul South Korea.
Kyung Won KwonDepartment of Otorhinolaryngology-Head and Neck Surgery Sanggye Paik Hospital, Inje University, College of Medicine Seoul South Korea.ORCID https://orcid.org/0000-0002-0633-8374
Yong Ju JangDepartment of Otolaryngology, Asan Medical Center University of Ulsan, College of Medicine Seoul South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Computational fluid dynamics (CFD) is increasingly used to investigate the complex pathophysiology of empty nose syndrome (ENS). Although previous CFD studies reported middle-meatus-dominant airflow and reduced air-mucosal interaction in ENS, whether airflow distribution alone explains symptoms or impaired nasal physiology remains unclear. Methods: Patient-specific CFD simulations were performed in 14 ENS patients using nasal cavity models reconstructed from computed tomography. Airflow distribution, nasal resistance, air temperature, relative humidity, and surface area-to-volume ratio (SAVR) were analyzed. Ten non-ENS subjects with nasal septal deviation (NSD) without prior nasal surgery and five normal subjects were analyzed for comparison. Results: Airflow distributions in ENS were heterogeneous, consisting of middle-meatus-dominant (9/14), inferior-meatus-dominant (4/14), and mixed (1/14) patterns. ENS6Q scores tended to be higher in the inferior-meatus-dominant group, whereas other variables did not differ between patterns. NSD subjects showed similarly diverse distributions (3/10, 3/10, and 4/10, respectively), indicating that skewed airflow distribution is not unique to ENS, although middle-meatus-dominant airflow was more frequent in ENS. All normal subjects exhibited mixed distributions. ENS subjects showed lower and more variable choanal relative humidity than normal subjects, and relative humidity correlated positively with SAVR in ENS and NSD, suggesting that nasal air-conditioning may be related to residual mucosal surface geometry. No parameter differed significantly between ENS and NSD or correlated with ENS6Q scores. Conclusion: ENS is not characterized by a single airflow pattern but represents a heterogeneous spectrum of airflow characteristics, with similar phenotypes also occurring in non-ENS subjects. Airflow distribution pattern alone was insufficient to explain ENS symptoms, and none of the evaluated global CFD parameters correlated significantly with ENS6Q scores, although the small sample precludes firm exclusion of clinically relevant associations. Preservation of mucosal surface area may nevertheless play an important role in nasal air-conditioning. These findings support a physiology-based and patient-specific understanding of ENS.

Indexed as

computational fluid dynamicsempty nose syndromenasal cavitynasal obstructionrelative humiditysurface area‐to‐volume ratio

Identifiers

PMID42836257
PMCPMC13638262

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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.