Division of Thoracic and Cardiovascular Surgery, Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA.
J Thorac Cardiovasc Surg. 2012 Apr;143(4):873-8. doi: 10.1016/j.jtcvs.2011.09.070. Epub 2012 Feb 4.
Clinical models incompletely predict the outcomes after coronary artery bypass grafting. Novel molecular technologies can identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting.
The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected before surgery. Principal components analysis and Cox proportional hazards regression modeling were used to assess the relation between the metabolite factor levels and a composite outcome of postcoronary artery bypass grafting myocardial infarction, the need for percutaneous coronary intervention, repeat coronary artery bypass grafting, and death.
During a mean follow-up period of 4.3 ± 2.4 years, 126 subjects (26.4%) experienced an adverse event. Three principal components analysis-derived factors were significantly associated with an adverse outcome on univariate analysis: short-chain dicarboxylacylcarnitines (factor 2, P = .001); ketone-related metabolites (factor 5, P = .02); and short-chain acylcarnitines (factor 6, P = .004). These 3 factors remained independently predictive of an adverse outcome after multivariate adjustment: factor 2 (adjusted hazard ratio, 1.23; 95% confidence interval, 1.10-1.38; P < .001), factor 5 (odds ratio, 1.17; 95% confidence interval, 1.01-1.37; P = .04), and factor 6 (odds ratio, 1.14; 95% confidence interval, 1.02-1.27; P = .03).
Metabolic profiles are independently associated with adverse outcomes after coronary artery bypass grafting. These profiles might represent novel biomarkers of risk that can augment existing tools for risk stratification of coronary artery bypass grafting patients and might elucidate novel biochemical pathways that mediate risk.
临床模型不能完全预测冠状动脉旁路移植术后的结果。新型分子技术可以识别生物标志物，以改善风险分层。我们研究了代谢谱是否可以预测接受冠状动脉旁路移植术的患者的不良事件。
该研究人群包括来自 CATHGEN 生物库的 478 名患者，这些患者在登记后因心脏导管插入术而接受冠状动脉旁路移植术。在手术前采集的空腹冷冻血浆样本中进行基于靶向质谱的 69 种代谢物的分析。主成分分析和 Cox 比例风险回归模型用于评估代谢物因子水平与冠状动脉旁路移植术后心肌梗死、经皮冠状动脉介入治疗、再次冠状动脉旁路移植术和死亡的复合结局之间的关系。
在平均 4.3 ± 2.4 年的随访期间，126 名患者（26.4%）经历了不良事件。单变量分析显示，3 个主成分分析衍生因子与不良预后显著相关：短链二羧酸酰基辅酶 A（因子 2，P =.001）；酮相关代谢物（因子 5，P =.02）；和短链酰基辅酶 A（因子 6，P =.004）。多变量调整后，这 3 个因素仍然是不良预后的独立预测因素：因子 2（调整后的危险比，1.23；95%置信区间，1.10-1.38；P <.001），因子 5（比值比，1.17；95%置信区间，1.01-1.37；P =.04），和因子 6（比值比，1.14；95%置信区间，1.02-1.27；P =.03）。
代谢谱与冠状动脉旁路移植术后的不良结局独立相关。这些谱可能代表风险的新型生物标志物，可以增强用于冠状动脉旁路移植术患者风险分层的现有工具，并可能阐明介导风险的新的生化途径。
