Department of Internal Medicine, Division of Cardiology, Wake Forest University, Winston-Salem, North Carolina, USA.
Diabetes Care. 2011 May;34(5):1219-24. doi: 10.2337/dc11-0008. Epub 2011 Mar 11.
In diabetes, it remains unclear whether the coronary artery calcium (CAC) score provides additional information about total mortality risk beyond traditional risk factors.
A total of 1,051 participants, aged 34-86 years, in the Diabetes Heart Study (DHS) were followed for 7.4 years. Subjects were separated into five groups using baseline computed tomography scans and CAC scores (0-9, 10-99, 100-299, 300-999, and ≥1,000). Logistic regression was performed adjusting for age, sex, race, smoking, and LDL cholesterol to examine the association between CAC and all-cause mortality. Areas under the curve with and without CAC were compared. Natural splines using continuous measures of CAC were fitted to estimate the relationship between observed CAC and mortality risk.
A total of 17% (178 of 1,051) of participants died during the follow-up. In multivariate analysis, the odds ratios (95% CIs) for all-cause mortality, using CAC 0-9 as the reference group, were CAC 10-99: 1.40 (0.57-3.74); CAC 100-299: 2.87 (1.17-7.77); CAC 300-999: 3.04 (1.32-7.90); and CAC ≥ 1,000: 6.71 (3.09-16.87). The area under the curve without CAC was 0.68 (95% CI 0.66-0.70), and the area under the curve with CAC was 0.72 (0.70-0.74) (P = 0.0001). Using splines, the estimated risk (95% CI) of mortality for a CAC of 0 was 6.7% (4.6-9.7), and the risk increased nearly linearly, plateauing at CAC ≥ 1,000 (20.0% [15.7-25.2]).
In diabetes, CAC was shown to be an independent predictor of mortality. Participants with CAC (0-9) were at lower risk (0.9% annual mortality). The risk of mortality increased with increasing levels of CAC, plateauing at approximately CAC ≥ 1,000 (2.7% annual mortality). More research is warranted to determine the potential utility of CAC scans in diabetes.
在糖尿病患者中，冠状动脉钙（CAC）评分是否能提供比传统危险因素更多的关于全因死亡率的信息仍不清楚。
共有 1051 名年龄在 34-86 岁的糖尿病心脏研究（DHS）参与者接受了 7.4 年的随访。受试者根据基线计算机断层扫描和 CAC 评分（0-9、10-99、100-299、300-999 和≥1000）分为五组。使用逻辑回归调整年龄、性别、种族、吸烟和 LDL 胆固醇，以检查 CAC 与全因死亡率之间的关联。比较有无 CAC 的曲线下面积。使用 CAC 的连续测量值拟合自然样条，以估计观察到的 CAC 与死亡率风险之间的关系。
在随访期间，共有 17%（178/1051）的参与者死亡。在多变量分析中，使用 CAC 0-9 作为参考组，全因死亡率的比值比（95%CI）分别为 CAC 10-99：1.40（0.57-3.74）；CAC 100-299：2.87（1.17-7.77）；CAC 300-999：3.04（1.32-7.90）；和 CAC≥1000：6.71（3.09-16.87）。无 CAC 的曲线下面积为 0.68（95%CI 0.66-0.70），有 CAC 的曲线下面积为 0.72（0.70-0.74）（P=0.0001）。使用样条，CAC 为 0 的死亡率估计风险（95%CI）为 6.7%（4.6-9.7），风险呈近线性增加，在 CAC≥1000 时趋于平稳（20.0%[15.7-25.2]）。
在糖尿病患者中，CAC 被证明是死亡率的独立预测因子。CAC（0-9）的参与者风险较低（年死亡率 0.9%）。死亡率随 CAC 水平的增加而增加，在 CAC 约≥1000 时趋于平稳（年死亡率 2.7%）。需要进一步研究以确定 CAC 扫描在糖尿病中的潜在应用价值。
