Published online Dec 6, 2019. doi: 10.12998/wjcc.v7.i23.3945
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
Diabetic kidney disease (DKD) is one of the common causes of end-stage renal disease. Accurate and timely diagnosis of early DKD are significant for improving prognosis and reducing mortality. Kidney biopsy is the golden standard in DKD diagnosis, but it is an invasive examination method that cannot be used as a screening tool. To date, DKD is often diagnosed by biochemical indicators such as urinary albumin excretion rate (UAER), serum creatinine, and blood urea nitrogen, but these fail to make accurate diagnosis of early DKD because of the strong compensatory capacity of kidney.
Elastography point quantification (ElastPQ) is a new shear wave elastography technology that displays the elasticity of renal tissue and quantifies tissue elasticity through Young's Modulus (YM). Recently, researchers have found that with the progression of DKD, the elasticity of the renal tissue gradually decreases. However, studies about the renal tissue elasticity of early DKD are still lacking, and it is uncertain whether ElastPQ can improve the accuracy of early DKD diagnosis.
In this study, the ElastPQ technique was used to measure the changes of renal elasticity in patients with different stages of DKD. Our study aims to explore the value of ElastPQ in improving the accuracy of early DKD diagnosis.
A total of 69 patients with type 2 diabetes who underwent renal biopsy were recruited and divided into early DKD group and medium DKD group. At the same time, 40 patients with simple diabetes were enrolled as the diabetes group. The basic data, clinical indicators, and ultrasound indicators of each patient were recorded and compared among the three groups. Multivariate logistic regression was used to analyze the influencing factors of the development of simple diabetes into early DKD, and early DKD into medium DKD. Receiver operating characteristic curves were used to test the accuracy of potential indicators in identifying early DKD and medium DKD, as well as early DKD and simple diabetes.
Our study demonstrated that the consistency of YM in renal cortex, medulla, and renal sinus was excellent. Multivariate logistic regression showed that UAER, renal cortical YM, and renal parenchymal thickness were the independent influencing factors of the development of early DKD into medium DKD. Receiver operating characteristic analysis showed that they were accurate in identifying early DKD and medium DKD. As for the development from simple diabetes into early DKD, diabetes duration, UAER, and renal cortical YM were independent factors. However, the accuracy of UAER, diabetes duration, and renocortical YM for the identification of early DKD and simple diabetes were limited. Logistic regression model was used to combine UAER, diabetes course, and renal cortical YM, and it found that the accuracy of the combined indicators was significantly higher than any of the three indicators individually in identifying early DKD and simple diabetes.
ElastPQ is of great value to improve the accuracy of early DKD diagnosis. After combined with diabetes duration and UAER, it is expected to predict accurately early DKD, which is helpful for early clinical diagnosis of DKD.
In order to explore further the clinical application value of the combined model of diabetes duration, UAER, and renocortical YM in early DKD diagnosis, this study plans to verify the accuracy and reliability of the combined model through prospective studies. Based on the results, the protocol should be adjusted reasonably in order to obtain a clinically applicable accurate diagnosis method of early DKD.