Evidence map›Paper›PMID 30097959›Full record

ArticleFrontiers of medicine2019

Comparative analysis of membranous and other nephropathy subtypes and establishment of a diagnostic model.

Hanyu Zhu, Bo Fu, Yong Wang, Jing Gao, Qiuxia Han, Wenjia Geng, Xiaoli Yang, Guangyan Cai, Xiangmei Chen, Dong Zhang

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Frontiers of medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Hanyu ZhuDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Bo FuDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Yong WangDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China. wangyong301@263.net.
Jing GaoDepartment of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, 100853, China.
Qiuxia HanDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Wenjia GengDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Xiaoli YangDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Guangyan CaiDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Xiangmei ChenDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China.
Dong ZhangDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center of Kidney Diseases, Beijing Key Laboratory of Kidney Disease, Beijing, 100853, China. zhangdong301@126.com.
Chinese PLA General Hospital · CNState Key Laboratory of Kidney DiseasesFirst Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare clinical features between membranous nephropathy (MN) and nonmembranous nephropathy (non-MN), to explore the clinically differential diagnosis of these two types, and to establish a diagnostic model of MN. After renal biopsy was obtained, 798 patients were divided into two groups based on their examination results: primary MN group (n = 248) and non-MN group (n = 550). Their data were statistically analyzed. Logistic regression analysis indicated that anti-PLA2R antibodies, IgG, and Cr were independently correlated with MN, and these three parameters were then used to establish the MN diagnostic model. A receiver operating characteristic (ROC) curve confirmed that our diagnostic model could distinguish between patients with and without MN, and their corresponding sensitivity, specificity, and AUC were 79.9%, 89.4%, and 0.917, respectively. The cutoff value for this combination in MN diagnosis was 0.34. The established diagnostic model that combined multiple factors shows a potential for broad clinical applications in differentiating primary MN from other kidney diseases and provides reliable evidence supporting the feasibility of noninvasive diagnosis of kidney diseases.

Indexed as

AdultAutoantibodiesFemaleGlomerulonephritisGlomerulonephritis, MembranousHumansKidneyLogistic ModelsMaleMiddle AgedReceptors, Phospholipase A2Retrospective StudiesROC CurveSensitivity and SpecificityAutoantibodiesReceptors, Phospholipase A2diagnosismembranous nephropathymodelmultiparameter analysis

Identifiers

PMID30097959
OpenAlexW2887619657

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.