The use of urinary biomarkers in the diagnosis of overactive bladder in female patients. A systematic review and meta-analysis

Author(s):  
Sofia Tsiapakidou ◽  
Apostolos Apostolidis ◽  
Konstantinos Pantazis ◽  
Grigoris F Grimbizis ◽  
Themistoklis Mikos
Author(s):  
Stavros Athanasiou ◽  
Eleni Pitsouni ◽  
Themos Grigoriadis ◽  
Dimitris Zacharakis ◽  
Stefano Salvatore ◽  
...  

2021 ◽  
Vol 47 (5) ◽  
pp. 366-374
Author(s):  
Dian Paramita Oktaviani ◽  
◽  
Mohammad Ayodhia Soebadi ◽  
Yudhistira Pradnyan Kloping ◽  
Furqan Hidayatullah ◽  
...  

2015 ◽  
Vol 77 (S3) ◽  
pp. 1369-1377 ◽  
Author(s):  
Wei Huang ◽  
Huantao Zong ◽  
Xin Zhou ◽  
Tao Wang ◽  
Yong Zhang

2020 ◽  
Vol 21 (18) ◽  
pp. 6889 ◽  
Author(s):  
Francesco Guzzi ◽  
Luigi Cirillo ◽  
Elisa Buti ◽  
Francesca Becherucci ◽  
Carmela Errichiello ◽  
...  

Noninvasive tools for diagnosis or prediction of acute kidney allograft rejection have been extensively investigated in recent years. Biochemical and molecular analyses of blood and urine provide a liquid biopsy that could offer new possibilities for rejection prevention, monitoring, and therefore, treatment. Nevertheless, these tools are not yet available for routine use in clinical practice. In this systematic review, MEDLINE was searched for articles assessing urinary biomarkers for diagnosis or prediction of kidney allograft acute rejection published in the last five years (from 1 January 2015 to 31 May 2020). This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Articles providing targeted or unbiased urine sample analysis for the diagnosis or prediction of both acute cellular and antibody-mediated kidney allograft rejection were included, analyzed, and graded for methodological quality with a particular focus on study design and diagnostic test accuracy measures. Urinary C-X-C motif chemokine ligands were the most promising and frequently studied biomarkers. The combination of precise diagnostic reference in training sets with accurate validation in real-life cohorts provided the most relevant results and exciting groundwork for future studies.


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