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Development of a Diagnostic Model Focusing on Esophageal Dysmotility in Patients with Systemic Sclerosis

Authors :
Peiling Liu
Jing Chai
Liyi Dai
Beidi Chen
Jinxia Zhao
Ming Lu
Lin Zeng
Zhiwei Xia
Rong Mu
Source :
Diagnostics, Vol 12, Iss 12, p 3142 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Objective. Esophageal dysmotility is a common and neglected complication of systemic sclerosis (SSc) associated with poor prognosis, while the assessment remains a challenge. We aimed to develop a diagnostic model for esophageal dysmotility in SSc patients that provides individualized risk estimates. Methods. Seventy-five SSc patients who underwent high-resolution manometry (HRM) were included in the study. Esophageal widest diameter (WED) was measured on a chest CT scan. Esophageal parameters between patients with and without esophageal dysmotility were compared. Multivariate logistic regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to fit the model. The diagnostic model was evaluated by discrimination and calibration. Internal validation was estimated using the enhanced bootstrap method with 1000 repetitions. Results. Sixty-one systemic sclerosis patients (81.3%) were diagnosed with esophageal dysmotility according to the Chicago Classification v 3.0. The diagnostic model for evaluating the probability of esophageal dysmotility integrated clinical and imaging features, including disease duration, ILD, and WED. The model displayed good discrimination with an area under the curve (AUC) of 0.923 (95% CI: 0.837–1.000), a Brier score of 0.083, and good calibration. A high AUC value of 0.911 could still be achieved in the internal validation. Conclusion. The diagnostic model, which combines the disease duration, ILD, and imaging feature (WED), is an effective and noninvasive method for predicting esophageal dysmotility in SSc patients.

Details

Language :
English
ISSN :
20754418
Volume :
12
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.4ca46c9b1dcb444ba926a999076a3796
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics12123142