Prediction of pathological grading of Henoch-Schönlein purpura nephritis in children based on Fisher stepwise discriminant analysis
10.3760/cma.j.issn.2095-428X.2019.14.008
- VernacularTitle: 基于Fisher逐步判别分析法对儿童紫癜性肾炎病理分级的预测模型研究
- Author:
Min HUANG
1
;
Jiacheng LI
2
;
Gaofu ZHANG
2
Author Information
1. Department of Pediatrics, Youyang Hospital, the First Affiliated Hospital of Chongqing Medical University, Youyang 409800, Chongqing, China
2. Department of Nephrology, Children′s Hospital of Chongqing Medical University, Ministry of Education, Key Laboratory of Child Development and Disorders, Chongqing 400014, China
- Publication Type:Journal Article
- Keywords:
Stepwise Fisher discriminant model;
Henoch-Schönlein purpura nephritis;
Pathology;
Child
- From:
Chinese Journal of Applied Clinical Pediatrics
2019;34(14):1072-1076
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish the pathological grades of Henoch-Schönlein purpura nephritis(HSPN) in children with diagnostic prediction models by stepwise Fisher discriminant in children.
Methods:Based on the investigation of 28 clinical indicators from 144 cases with HSPN came from Children′s Hospital of Chongqing Medical University, the sensitive indicators were found and stepwise Fisher discriminant model was established and its accuracy in predicting the pathological classification of HSPN was tested.
Results:There were 5 laboratory indicators and clinical manifestations with different pathological grades of HSPN.In children with pathological grade Ⅱ, Ⅲ and Ⅳ, 5 indicators were screened (P<0.05) and stepwise Fisher discriminant models were established.And the correct rate of comprehensive diagnosis was (61.371±8.740)% in 100 random sampling diagnostic simulations; in children with pathological grade Ⅲa and Ⅲb, 5 indicators were also screened (P<0.05) and stepwise Fisher discriminant models were established.And the correct rate of comprehensive diagnosis was (68.015±5.736)% in 100 random sampling diagnostic simulations.
Conclusions:The stepwise Fisher discriminant models established in this research have a better diagnostic accuracy in forecasting for pathological grade of HSPN, and have a certain guiding value on early treatment and prognosis evaluation of children with newly diagnosed HSPN.
