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A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis

To establish a noninvasive model based on two-dimensional shear wave elasticity (2D-SWE) technology, ultrasound feature and serological indicators to predict cirrhosis in autoimmune hepatitis (AIH) and verified. Patients with AIH confirmed by liver biopsy with liver ultrasound and serological examin...

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Autores principales: Feng, Siyi, Tu, Haibin, Chen, Lihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519531/
https://www.ncbi.nlm.nih.gov/pubmed/37747028
http://dx.doi.org/10.1097/MD.0000000000035295
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author Feng, Siyi
Tu, Haibin
Chen, Lihong
author_facet Feng, Siyi
Tu, Haibin
Chen, Lihong
author_sort Feng, Siyi
collection PubMed
description To establish a noninvasive model based on two-dimensional shear wave elasticity (2D-SWE) technology, ultrasound feature and serological indicators to predict cirrhosis in autoimmune hepatitis (AIH) and verified. Patients with AIH confirmed by liver biopsy with liver ultrasound and serological examination were collected from January 2019 to May 2022. Patients were divided into cirrhosis and non-cirrhosis groups. Basic indexes, ultrasound indexes and serological indexes were collected. Multivariable logistic regression used for screening independent risk factors predicting cirrhosis, construct the AIH cirrhosis prediction model, named autoimmune hepatitis cirrhosis (AIHC). Determine best cutoff score according to the Youden index, verified the model’s predictive efficacy. One hundred forty-six patients were collected. The following indicators were independent risk factors for predicting cirrhosis: LS (OR: 1.416, P = .015), splenomegaly (OR: 10.446, P = .006), complement C4 (OR: 0.020, P = .009). The best cutoff score was 65, with a sensitivity 88.9% and specificity 75.6%; the area under curve was 0.901, AIHC possessed a higher net reclassification index (NRI) and integrated discrimination improvement compared with other indexes, and AIHC had the best clinical decision curve. The AIHC constructed in this study has better predictive efficacy than other noninvasive indexes, and we visualized the model for easy application, which was worth further promotion in clinical practice.
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spelling pubmed-105195312023-09-26 A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis Feng, Siyi Tu, Haibin Chen, Lihong Medicine (Baltimore) 3600 To establish a noninvasive model based on two-dimensional shear wave elasticity (2D-SWE) technology, ultrasound feature and serological indicators to predict cirrhosis in autoimmune hepatitis (AIH) and verified. Patients with AIH confirmed by liver biopsy with liver ultrasound and serological examination were collected from January 2019 to May 2022. Patients were divided into cirrhosis and non-cirrhosis groups. Basic indexes, ultrasound indexes and serological indexes were collected. Multivariable logistic regression used for screening independent risk factors predicting cirrhosis, construct the AIH cirrhosis prediction model, named autoimmune hepatitis cirrhosis (AIHC). Determine best cutoff score according to the Youden index, verified the model’s predictive efficacy. One hundred forty-six patients were collected. The following indicators were independent risk factors for predicting cirrhosis: LS (OR: 1.416, P = .015), splenomegaly (OR: 10.446, P = .006), complement C4 (OR: 0.020, P = .009). The best cutoff score was 65, with a sensitivity 88.9% and specificity 75.6%; the area under curve was 0.901, AIHC possessed a higher net reclassification index (NRI) and integrated discrimination improvement compared with other indexes, and AIHC had the best clinical decision curve. The AIHC constructed in this study has better predictive efficacy than other noninvasive indexes, and we visualized the model for easy application, which was worth further promotion in clinical practice. Lippincott Williams & Wilkins 2023-09-22 /pmc/articles/PMC10519531/ /pubmed/37747028 http://dx.doi.org/10.1097/MD.0000000000035295 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 3600
Feng, Siyi
Tu, Haibin
Chen, Lihong
A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title_full A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title_fullStr A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title_full_unstemmed A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title_short A novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
title_sort novel model predicted liver cirrhosis constructed by ultrasound and serological in autoimmune liver hepatitis
topic 3600
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519531/
https://www.ncbi.nlm.nih.gov/pubmed/37747028
http://dx.doi.org/10.1097/MD.0000000000035295
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