Diercks Deborah B, Owen Kelly P, Tolstikov Vladimir, Sutter Mark E, Kline Jeffrey A
University of California Davis, Department of Emergency Medicine, Sacramento, California.
Carolinas Medical Center, Department of Emergency Medicine, Charlotte, North Carolina.
West J Emerg Med. 2014 Mar;15(2):152-7. doi: 10.5811/westjem.2013.11.15343.
Contrast-induced nephropathy is a result of injury to the proximal tubules caused by oxidative stress and ischemia. Metabolomics is a novel technique that has been used to identify renal damage from drug toxicities. The objective of this study is to analyze the metabolic changes in the urine after dosing with intravenous (IV) contrast for computed tomograph (CT) of the chest.
A convenience sample of patients undergoing a chest ct with iv contrast who had at least one of the following: age ≥50 years, diabetes, heart failure, chronic kidney disease, coronary artery disease, or diastolic blood pressure >90 mmHg -- were eligible for enrollment. Urine samples were collected prior to imaging and 4-6 hours post imaging. Samples underwent gas chromography/mass spectrometry profiling. We measured peak metabolite values and log transformed data. Paired T tests were calculated. We used significance analysis of microarrays (SAM) to determine the most significant metabolites.
The cohort comprised 14 patients with matched samples; 9/14 (64.3) were males, and the median age was 61 years (IQR 50-68). A total of 158 metabolites were identified. Using SAM we identified 9 metabolites that were identified as significant using a delta of 1.6.
Changes in urinary metabolites are present soon after contrast administration. This change in urinary metabolites may be potential early identifiers of contrast-induced nephropathy and could identify patients at high-risk for developing this condition.
对比剂肾病是由氧化应激和缺血导致近端肾小管损伤的结果。代谢组学是一种已被用于识别药物毒性所致肾损伤的新技术。本研究的目的是分析静脉注射对比剂用于胸部计算机断层扫描(CT)后尿液中的代谢变化。
选取接受静脉注射对比剂进行胸部CT检查且符合以下至少一项标准的患者作为便利样本:年龄≥50岁、糖尿病、心力衰竭、慢性肾脏病、冠状动脉疾病或舒张压>90 mmHg。在成像前及成像后4 - 6小时收集尿液样本。样本进行气相色谱/质谱分析。我们测量了代谢物峰值并对数据进行对数转换。计算配对t检验。我们使用微阵列显著性分析(SAM)来确定最显著的代谢物。
该队列包括14例有匹配样本的患者;9/14(64.3%)为男性,中位年龄为61岁(四分位间距50 - 68)。共鉴定出158种代谢物。使用SAM,我们鉴定出9种代谢物,其差异值为1.6时被确定为显著。
对比剂给药后不久尿液代谢物就会出现变化。尿液代谢物的这种变化可能是对比剂肾病的潜在早期标志物,并且可以识别出发生这种情况的高危患者。