2型糖尿病患者患心血管疾病的風(fēng)險是非糖尿病人群的兩到四倍。冠狀動(dòng)脈鈣化（CAC）測試有助醫生預測哪些糖尿病患者心臟疾病的風(fēng)險最大，根據維克森林大學(xué)浸信會(huì )醫療中心的一項研究。

　　目前醫學(xué)界的指南推薦將所有糖尿病患者視為心血管疾病高風(fēng)險人群，但維克森林浸信會(huì )的這項研究發(fā)現，CAC可以識別致命性心血管疾病高風(fēng)險以及低風(fēng)險的糖尿病患者。

　　"我們的研究結果挑戰了公認的醫學(xué)看法，即所有糖尿病患者心血管風(fēng)險相同。CAC是預測不同風(fēng)險水平的關(guān)鍵，"Donald Bowden博士，維克森林大學(xué)浸信會(huì )生物化學(xué)教授和資深作者。研究結果在線(xiàn)發(fā)表于十二月號刊《糖尿病護理》（Diabetes Care）雜志。

　　研究總共納入1123名34-86歲2型糖尿病患者，平均隨訪(fǎng)7.4年。這項研究的受試者來(lái)自北卡羅來(lái)納州西部的診所。

　　"高風(fēng)險人群死于心血管疾病的風(fēng)險是低風(fēng)險人群的11倍。更精確的診斷風(fēng)險水平可幫助醫生提供更有效的治療，并有望改善的結果，"研究人員說(shuō)。

　　Coronary Calcium Score Predicts Cardiovascular Mortality in Diabetes

　　Subhashish Agarwal, Amanda J. Cox, David M. Herringto,et al

　　Abstract

　　OBJECTIVE

　　In type 2 diabetes mellitus (T2DM), it remains unclear whether coronary artery calcium (CAC) provides additional information about cardiovascular disease (CVD) mortality beyond the Framingham Risk Score (FRS) factors.

　　RESEARCH DESIGN AND METHODS

　　A total of 1,123 T2DM participants, ages 34–86 years, in the Diabetes Heart Study followed up for an average of 7.4 years were separated using baseline computed tomography scans of CAC (0–9, 10–99, 100–299, 300–999, and ≥1,000).

　　Logistic regression was performed to examine the association between CAC and CVD mortality adjusting for FRS.

　　Areas under the curve (AUC) with and without CAC were compared. Net reclassification improvement (NRI) compared FRS (model 1) versus FRS+CAC (model 2) using 7.4-year CVD mortality risk categories 0% to <7%, 7% to <20%, and ≥20%.

　　RESULTS

　　Overall, 8% of participants died of cardiovascular causes during follow-up. In multivariate analysis, the odds ratios (95% CI) for CVD mortality using CAC 0–9 as the reference group were, CAC 10–99: 2.93 (0.74–19.55); CAC 100–299: 3.17 (0.70–22.22); CAC 300–999: 4.41(1.15–29.00); and CAC ≥1,000: 11.23 (3.24–71.00). AUC (95% CI) without CAC was 0.70 (0.67–0.73), AUC with CAC was 0.75 (0.72–0.78), and NRI was 0.13 (0.07–0.19).

　　CONCLUSIONS

　　In T2DM, CAC predicts CVD mortality and meaningfully reclassifies participants, suggesting clinical utility as a risk stratification tool in a population already at increased CVD risk.