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Open Access Highly Accessed Database

CDKD: a clinical database of kidney diseases

Sanjay Kr Singh1*, Adeel Malik13, Ahmad Firoz14 and Vivekanand Jha12*

Author Affiliations

1 Biomedical Informatics Centre, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, 160012, India

2 Department of Nephrology, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, 160012, India

3 School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 130-722, South Korea

4 School of Chemistry & Biochemistry, Thapar University, Patiala, Punjab, India

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BMC Nephrology 2012, 13:23  doi:10.1186/1471-2369-13-23

Published: 27 April 2012

Abstract

Background

The main function of the kidneys is to remove waste products and excess water from the blood. Loss of kidney function leads to various health issues, such as anemia, high blood pressure, bone disease, disorders of cholesterol. The main objective of this database system is to store the personal and laboratory investigatory details of patients with kidney disease. The emphasis is on experimental results relevant to quantitative renal physiology, with a particular focus on data relevant for evaluation of parameters in statistical models of renal function.

Description

Clinical database of kidney diseases (CDKD) has been developed with patient confidentiality and data security as a top priority. It can make comparative analysis of one or more parameters of patient’s record and includes the information of about whole range of data including demographics, medical history, laboratory test results, vital signs, personal statistics like age and weight.

Conclusions

The goal of this database is to make kidney-related physiological data easily available to the scientific community and to maintain & retain patient’s record. As a Web based application it permits physician to see, edit and annotate a patient record from anywhere and anytime while maintaining the confidentiality of the personal record. It also allows statistical analysis of all data.