This paper is in the following e-collection/theme issue:

Non-Randomized Study Protocols and Methods (Non-eHealth) (571) Diabetes (187)

Published on in Vol 9, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16277, first published .
Identification of Potential Biomarkers of Chronic Kidney Disease in Individuals with Diabetes: Protocol for a Cross-sectional Observational Study

Identification of Potential Biomarkers of Chronic Kidney Disease in Individuals with Diabetes: Protocol for a Cross-sectional Observational Study

Identification of Potential Biomarkers of Chronic Kidney Disease in Individuals with Diabetes: Protocol for a Cross-sectional Observational Study

Authors of this article:

Ashani R Lecamwasam1, 2, 3 Author Orcid Image ;   Mohammadreza Mohebbi4 Author Orcid Image ;   Elif I Ekinci2, 5 Author Orcid Image ;   Karen M Dwyer3 Author Orcid Image ;   Richard Saffery1, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations (5) Metrics

Journals

  1. Lecamwasam A, Mansell T, Ekinci E, Saffery R, Dwyer K. Blood Plasma Metabolites in Diabetes-Associated Chronic Kidney Disease: A Focus on Lipid Profiles and Cardiovascular Risk. Frontiers in Nutrition 2022;9 View
  2. Kang E, Li Y, Kim B, Huh K, Han M, Ahn J, Sung H, Park Y, Lee S, Lee S, Park S, Cho J, Oh K. Identification of Serum Metabolites for Predicting Chronic Kidney Disease Progression according to Chronic Kidney Disease Cause. Metabolites 2022;12(11):1125 View
  3. Jayalath S, Magana-Arachchi D. Dysbiosis of the Human Urinary Microbiome and its Association to Diseases Affecting the Urinary System. Indian Journal of Microbiology 2022;62(2):153 View
  4. Shi L, Xue Y, Yu X, Wang Y, Hong T, Li X, Ma J, Zhu D, Mu Y. Prevalence and Risk Factors of Chronic Kidney Disease in Patients With Type 2 Diabetes in China: Cross-Sectional Study. JMIR Public Health and Surveillance 2024;10:e54429 View