Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up

Yi Wang; Yanni Li; Xiaoyi Wang; Ranko Gacesa; Jie Zhang; Lu Zhou; Bangmao Wang

doi:10.1155/2020/8460883

Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up

Yi Wang^*, Yanni Li, Xiaoyi Wang, Ranko Gacesa, Jie Zhang, Lu Zhou, Bangmao Wang

^*Corresponding author for this work

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Abstract

Background. Early detection is crucial for the prognosis of patients with autoimmune liver disease (AILD). Due to the relatively low incidence, developing screening tools for AILD remain a challenge.Aims. To analyze clinical characteristics of AILD patients at initial presentation and identify clinical markers, which could be useful for disease screening and early detection.Methods. We performed observational retrospective study and analyzed 581 AILD patients who were hospitalized in the gastroenterology department and 1000 healthy controls who were collected from health management center. Baseline characteristics at initial presentation were used to build regression models. The model was validated on an independent cohort of 56 patients with AILD and 100 patients with other liver disorders.Results. Asymptomatic AILD individuals identified by the health check-up are increased yearly (from 31.6% to 68.0%,p

Original language	English
Article number	8460883
Number of pages	11
Journal	Disease markers
Volume	2020
DOIs	https://doi.org/10.1155/2020/8460883
Publication status	Published - 31-May-2020

Keywords

AUTOIMMUNE HEPATITIS
OVERLAP SYNDROME
CIRRHOSIS
ULTRASOUND

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Predicting Liver Disease Risk Using a Combination of Common Clinical MarkersFinal publisher's version, 813 KBLicence: CC BY

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title = "Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up",

abstract = "Background. Early detection is crucial for the prognosis of patients with autoimmune liver disease (AILD). Due to the relatively low incidence, developing screening tools for AILD remain a challenge.Aims. To analyze clinical characteristics of AILD patients at initial presentation and identify clinical markers, which could be useful for disease screening and early detection.Methods. We performed observational retrospective study and analyzed 581 AILD patients who were hospitalized in the gastroenterology department and 1000 healthy controls who were collected from health management center. Baseline characteristics at initial presentation were used to build regression models. The model was validated on an independent cohort of 56 patients with AILD and 100 patients with other liver disorders.Results. Asymptomatic AILD individuals identified by the health check-up are increased yearly (from 31.6% to 68.0%,p",

keywords = "AUTOIMMUNE HEPATITIS, OVERLAP SYNDROME, CIRRHOSIS, ULTRASOUND",

author = "Yi Wang and Yanni Li and Xiaoyi Wang and Ranko Gacesa and Jie Zhang and Lu Zhou and Bangmao Wang",

year = "2020",

month = may,

day = "31",

doi = "10.1155/2020/8460883",

language = "English",

volume = "2020",

journal = "Disease markers",

issn = "0278-0240",

publisher = "HINDAWI LTD",

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TY - JOUR

T1 - Predicting Liver Disease Risk Using a Combination of Common Clinical Markers

T2 - A Screening Model from Routine Health Check-Up

AU - Wang, Yi

AU - Li, Yanni

AU - Wang, Xiaoyi

AU - Gacesa, Ranko

AU - Zhang, Jie

AU - Zhou, Lu

AU - Wang, Bangmao

PY - 2020/5/31

Y1 - 2020/5/31

N2 - Background. Early detection is crucial for the prognosis of patients with autoimmune liver disease (AILD). Due to the relatively low incidence, developing screening tools for AILD remain a challenge.Aims. To analyze clinical characteristics of AILD patients at initial presentation and identify clinical markers, which could be useful for disease screening and early detection.Methods. We performed observational retrospective study and analyzed 581 AILD patients who were hospitalized in the gastroenterology department and 1000 healthy controls who were collected from health management center. Baseline characteristics at initial presentation were used to build regression models. The model was validated on an independent cohort of 56 patients with AILD and 100 patients with other liver disorders.Results. Asymptomatic AILD individuals identified by the health check-up are increased yearly (from 31.6% to 68.0%,p

AB - Background. Early detection is crucial for the prognosis of patients with autoimmune liver disease (AILD). Due to the relatively low incidence, developing screening tools for AILD remain a challenge.Aims. To analyze clinical characteristics of AILD patients at initial presentation and identify clinical markers, which could be useful for disease screening and early detection.Methods. We performed observational retrospective study and analyzed 581 AILD patients who were hospitalized in the gastroenterology department and 1000 healthy controls who were collected from health management center. Baseline characteristics at initial presentation were used to build regression models. The model was validated on an independent cohort of 56 patients with AILD and 100 patients with other liver disorders.Results. Asymptomatic AILD individuals identified by the health check-up are increased yearly (from 31.6% to 68.0%,p

KW - AUTOIMMUNE HEPATITIS

KW - OVERLAP SYNDROME

KW - CIRRHOSIS

KW - ULTRASOUND

U2 - 10.1155/2020/8460883

DO - 10.1155/2020/8460883

M3 - Article

SN - 0278-0240

VL - 2020

JO - Disease markers

JF - Disease markers

M1 - 8460883

ER -

Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up

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Keywords

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