MOLECULAR MARKERS FOR ISCHEMA, DO WE HAVE SOMETHING BETTER THAN CREATININE AND GLOMERULAR FILTRATION RATE?

被引:0
|
作者
Sprenkle, Preston [1 ]
Russo, Paul [1 ]
机构
[1] Mem Sloan Kettering Canc Ctr, Dept Surg, Urol Serv, New York, NY 10065 USA
来源
ARCHIVOS ESPANOLES DE UROLOGIA | 2013年 / 66卷 / 01期
关键词
Biological markers; Acute kidney injury; Ischemia; Creatinine; Glomerular filtration rate; Small renal masses; Renal cancer; ACUTE KIDNEY INJURY; GELATINASE-ASSOCIATED LIPOCALIN; ACUTE-RENAL-FAILURE; ACID-BINDING PROTEIN; SERUM CYSTATIN-C; BETA-D-GLUCOSAMINIDASE; URINARY BIOMARKERS; CARDIAC-SURGERY; LIVER-TYPE; RADICAL NEPHRECTOMY;
D O I
暂无
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Acute kidney injury (AKI) can occur spontaneously or iatrogenically, and rates of AKI continue to rise over the last two decades despite improvements in clinical care and development of preventive strategies. Serum creatinine (sCr) is the current gold standard for measuring changes in kidney function and identifying AKI. Detection of AKI by sCr, however, is delayed and small rises connote significantly increased morbidity and mortality. Diagnosis of AKI by sCr is therefore likely too late to prevent some of the early structural changes that characterize renal injury Several urinary biomarkers including neutrophil gelatinase-associated lipocalin (NGAL), N-acetyl-beta-D-glucosaminidase (NAG), Interleukin-1 8 (IL-18), kidney injury molecule-1 (KIM-7), liver fatly-acid-binding protein (L-FABP), and cystatin-C, have shown an ability to predict AKI days before an elevation in sCr, and a few even seem to predict AKI-related morbidity and mortality better than sCr alone. A review of the current literature regarding these biomarkers reveals that they individually have unique strengths and weaknesses that can provide different types of information about patients. Currently NGAL is the urine biomarker with the most promise as an individual marker. However, combining multiple markers to form a 'biomarker panel' along with sCr is an improvement over current clinical risk prediction models alone, and may be able to provide more individualized detail about the type and location of renal injury.
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页码:99 / 114
页数:16
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