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Published in: BMC Pulmonary Medicine 1/2021

Open Access 01-12-2021 | Laryngoscopy | Research

Clinical analysis of the “small plateau” sign on the flow-volume curve followed by deep learning automated recognition

Authors: Yimin Wang, Wenya Chen, Yicong Li, Changzheng Zhang, Lijuan Liang, Ruibo Huang, Jianling Liang, Yi Gao, Jinping Zheng

Published in: BMC Pulmonary Medicine | Issue 1/2021

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Abstract

Background

Small plateau (SP) on the flow-volume curve was found in parts of patients with suspected asthma or upper airway abnormalities, but it lacks clear scientific proof. Therefore, we aimed to characterize its clinical features.

Methods

We involved patients by reviewing the bronchoprovocation test (BPT) and bronchodilator test (BDT) completed between October 2017 and October 2020 to assess the characteristics of the sign. Patients who underwent laryngoscopy were assigned to perform spirometry to analyze the relationship of the sign and upper airway abnormalities. SP-Network was developed to recognition of the sign using flow-volume curves.

Results

Of 13,661 BPTs and 8,168 BDTs completed, we labeled 2,123 (15.5%) and 219 (2.7%) patients with the sign, respectively. Among them, there were 1,782 (83.9%) with the negative-BPT and 194 (88.6%) with the negative-BDT. Patients with SP sign had higher median FVC and FEV1% predicted (both P < .0001). Of 48 patients (16 with and 32 without the sign) who performed laryngoscopy and spirometry, the rate of laryngoscopy-diagnosis upper airway abnormalities in patients with the sign (63%) was higher than those without the sign (31%) (P = 0.038). SP-Network achieved an accuracy of 95.2% in the task of automatic recognition of the sign.

Conclusions

SP sign is featured on the flow-volume curve and recognized by the SP-Network model. Patients with the sign are less likely to have airway hyperresponsiveness, automatic visualizing of this sign is helpful for primary care centers where BPT cannot available.
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Metadata
Title
Clinical analysis of the “small plateau” sign on the flow-volume curve followed by deep learning automated recognition
Authors
Yimin Wang
Wenya Chen
Yicong Li
Changzheng Zhang
Lijuan Liang
Ruibo Huang
Jianling Liang
Yi Gao
Jinping Zheng
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Pulmonary Medicine / Issue 1/2021
Electronic ISSN: 1471-2466
DOI
https://doi.org/10.1186/s12890-021-01733-x

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