Observational Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Dec 6, 2019; 7(23): 3945-3956
Published online Dec 6, 2019. doi: 10.12998/wjcc.v7.i23.3945
Value of elastography point quantification in improving the diagnostic accuracy of early diabetic kidney disease
Qiu-Yun Liu, Qi Duan, Xiao-Hong Fu, Li-Qian Fu, Hong-Wei Xia, Yong-Lin Wan
Qiu-Yun Liu, Xiao-Hong Fu, Hong-Wei Xia, Yong-Lin Wan, Department of Ultrasound, Naval Military Medical University Affiliated Gongli Hospital, Shanghai 200135, China
Qi Duan, Department of Ultrasound, Shanghai Hemujia Hospital, Shanghai 200336, China
Li-Qian Fu, Department of Nephrology, Naval Military Medical University Affiliated Gongli Hospital, Shanghai 200135, China
Author contributions: Liu QY, Duan Q, Fu XH, Fu LQ, and Xia HW designed the research; Liu QY, Duan Q, Fu XH, and Wan YL performed the research; Liu QY, Duan Q, and Xia HW contributed new analytic tools; Liu QY and Xia HW analyzed the data; and Liu QY, Duan Q, Fu XH, Fu LQ, Xia HW, and Wan YL wrote the paper.
Supported by Shanghai Health and Family Planning Commission, No. 201440051; and Shanghai Pudong New Area Health and Family Planning Commission, No. PW2016A-19.
Institutional review board statement: The study was approved by the Ethics Committee of Naval Military Medical University Affiliated Gongli Hospital.
Informed consent statement: All patients gave informed consent.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement, and the manuscript was prepared and revised according to the STROBE Statement.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Qi Duan, MD, Chief Doctor, Department of Ultrasound, Shanghai Hemujia Hospital, No. 1139, Changning District, Shanghai 200336, China. chen_qingan@163.com
Telephone: +86-21-22163999
Received: September 5, 2019
Peer-review started: September 5, 2019
First decision: September 23, 2019
Revised: October 14, 2019
Accepted: October 30, 2019
Article in press: October 30, 2019
Published online: December 6, 2019
Processing time: 92 Days and 9.1 Hours
Abstract
BACKGROUND

Diabetic kidney disease (DKD) is a common complication of diabetes. The patient’s prognosis is poor once DKD progresses to advanced stage. Accurate diagnosis and timely treatment of early DKD are important for improving patient’s prognosis and reducing mortality.

AIM

To explore the value of elastography point quantification (ElastPQ) in improving the accuracy of early DKD diagnosis.

METHODS

A total of 69 patients with type 2 diabetes were recruited from Naval Military Medical University Affiliated Gongli Hospital. Patients were divided into early DKD group and medium DKD group according to pathological results and urinary albumin excretion rate (UAER). Another 40 patients with simple diabetes were included as the diabetes group. The baseline data, laboratory diagnostic indicators, and ultrasound indicators for each patient were recorded. The differences of the indicators in the three groups were compared. Multivariate logistic regression was used to analyze the influencing factors of the development from simple diabetes into early DKD and from early DKD into medium DKD. Receiver operating characteristic analyses of potential indicators in identifying early DKD and medium DKD, and early DKD and simple diabetes were established.

RESULTS

Multivariate logistic regression analysis showed that UAER (P < 0.001), renocortical Young's Modulus (YM) (P < 0.001), and renal parenchymal thickness (P = 0.013) were the independent influencing factors of the development from early DKD into medium DKD. Diabetes duration (P = 0.041), UAER (P = 0.034), and renocortical YM (P = 0.017) were the independent influencing factors of the development from simple diabetes into early DKD. Receiver operating characteristic analysis indicated that UAER, renocortical YM, and renal parenchymal thickness were accurate in identifying early DKD and medium DKD [all area under curve (AUC) > 0.9]. The accuracy of UAER (AUC = 0.744), diabetes duration (AUC = 0.757), and renocortical YM (AUC = 0.782) for the diagnosis of early DKD and simple diabetes were limited. However, the combined diagnosis of UAER, diabetes duration, and renocortical YM was accurate in identifying early DKD and simple diabetes (AUC = 0.906), which was significantly higher than any of the three indicators (all P < 0.05).

CONCLUSION

ElastPQ is of great value in the diagnosis of early DKD. When combined with the diabetes duration and UAER, it is expected to diagnose accurately early DKD.

Keywords: Diabetic kidney disease; Elastography point quantification; Young's Modulus; Urinary albumin excretion rate; Combined diagnosis; Diabetes

Core tips: Early diabetic kidney disease (DKD) can be controlled or even reversed, but kidney function will be severely damaged once it develops into the advanced stage. Currently, staging of DKD relies mainly on urinary albumin excretion rate and clinical symptoms, but it is difficult to determine accurately early DKD patients. This study used elastography point quantification to measure changes in kidney stiffness in patients with different stages of DKD. It revealed that elastography point quantification can make accurate differential diagnosis for early and medium DKD and, when combined with diabetes duration and urinary albumin excretion rate, it can significantly improve the accuracy of early diagnosis of DKD.