Lei Meng-Huan, Hsu Yu-Chen, Chung Sheng-Liang, Chen Chao-Chin, Chen Wei-Cheng, Chen Wan-Ming, Jao An-Tzu, Hsiao Ju-Feng, Hsu Jen-Te, Wu Szu-Yuan
Division of Cardiology, Department of Internal Medicine, Lo-Hsu Medical Foundation, Lotung Poh-Ai Hospital, No. 83, Nanchang St., Luodong Township, Yilan County, 265, Taiwan.
Graduate Institute of Business Administration, College of Management, Fu Jen Catholic University, New Taipei City, Taiwan.
Diabetol Metab Syndr. 2024 May 19;16(1):104. doi: 10.1186/s13098-024-01341-9.
To enhance the predictive risk model for all-cause mortality in individuals with Type 2 Diabetes (T2DM) and prolonged Atherosclerotic Cardiovascular Disease (ASCVD) risk factors. Despite the utility of the Coronary Artery Calcium (CAC) score in assessing cardiovascular risk, its capacity to predict all-cause mortality remains limited.
A retrospective cohort study included 1929 asymptomatic T2DM patients with ASCVD risk factors, aged 40-80. Variables encompassed demographic attributes, clinical parameters, CAC scores, comorbidities, and medication usage. Factors predicting all-cause mortality were selected to create a predictive scoring system. By using stepwise selection in a multivariate Cox proportional hazards model, we divided the patients into three risk groups.
In our analysis of all-cause mortality in T2DM patients with extended ASCVD risk factors over 5 years, we identified significant risk factors, their adjusted hazard ratios (aHR), and scores: e.g., CAC score > 1000 (aHR: 1.57, score: 2), CAC score 401-1000 (aHR: 2.05, score: 2), and more. These factors strongly predict all-cause mortality, with varying risk groups (e.g., very low-risk: 2.0%, very high-risk: 24.0%). Significant differences in 5-year overall survival rates were observed among these groups (log-rank test < 0.001).
The Poh-Ai Predictive Scoring System excels in forecasting mortality and cardiovascular events in individuals with Type 2 Diabetes Mellitus and extended ASCVD risk factors.
增强2型糖尿病(T2DM)患者及具有长期动脉粥样硬化性心血管疾病(ASCVD)危险因素个体的全因死亡率预测风险模型。尽管冠状动脉钙化(CAC)评分在评估心血管风险方面具有实用性,但其预测全因死亡率的能力仍然有限。
一项回顾性队列研究纳入了1929名年龄在40 - 80岁、有ASCVD危险因素的无症状T2DM患者。变量包括人口统计学特征、临床参数、CAC评分、合并症和用药情况。选择预测全因死亡率的因素以创建一个预测评分系统。通过在多变量Cox比例风险模型中采用逐步选择法,我们将患者分为三个风险组。
在我们对具有延长的ASCVD危险因素的T2DM患者5年全因死亡率的分析中,我们确定了显著的危险因素、其调整后的风险比(aHR)和评分:例如,CAC评分>1000(aHR:1.57,评分:2),CAC评分401 - 1000(aHR:2.05,评分:2)等等。这些因素能有力地预测全因死亡率,不同风险组(例如,极低风险:2.0%,极高风险:24.0%)情况各异。这些组之间观察到5年总生存率存在显著差异(对数秩检验<0.001)。
Poh - Ai预测评分系统在预测2型糖尿病和具有延长的ASCVD危险因素个体的死亡率和心血管事件方面表现出色。