Biomarkers in native and transplant kidneys: opportunities to improve prediction of outcomes in chronic kidney disease
Predicting the outcomes of patients with chronic kidney disease (CKD) is important from both patient and healthcare system perspectives. This review examines the current state of conventional and nonconventional biomarkers as noninvasive tools to improve risk-stratification and outcome prediction in...
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Published in | Current opinion in nephrology and hypertension Vol. 21; no. 6; p. 619 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
01.11.2012
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Subjects | |
Online Access | Get more information |
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Summary: | Predicting the outcomes of patients with chronic kidney disease (CKD) is important from both patient and healthcare system perspectives. This review examines the current state of conventional and nonconventional biomarkers as noninvasive tools to improve risk-stratification and outcome prediction in CKD.
Conventional biomarkers (serum creatinine, urine albumin, and clinical variables such as sex, age, and diabetes) have been the cornerstone of most prediction models for CKD progression to end-stage renal disease (ESRD), and adverse cardiovascular outcomes including death. With better understanding of the pathophysiology of CKD and the evolution of molecular diagnostics, numerous novel or nonconventional markers have emerged. They have been examined individually and in combination to predict specific outcomes. We highlight these markers and studies, conducted primarily in patients with native kidneys. In those with transplant kidneys, markers of both acute and chronic kidney dysfunction have been examined, although to a lesser extent. Similarities and differences in knowledge derived from these two populations are highlighted.
Improving prediction of outcomes in CKD patients with either native or transplant kidneys remains an important goal. Increasingly sophisticated biomarkers may potentially identify targets for clinical research, improve the nature and timing of therapeutic interventions, and guide resource allocation. |
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ISSN: | 1473-6543 |
DOI: | 10.1097/MNH.0b013e32835846e3 |