目的：心血管疾病一直為國人十大死因的前三名，而目前佛萊明漢心血管危險預估評 分表(Framingham risk score)為最常被使用預測心血管疾病風險的工具，但臨床上使用需花 費不少時間。目前已有多篇研究提出腎絲球過濾率估計值和心血管疾病的相關性，故本研 究的目的為以醫院工作人員為研究對象，探討腎絲球過濾率估計值是否可作為佛萊明漢心 血管危險預估評分表的替代工具。 方法：本研究為橫斷性研究，以北台灣某醫院員工族群為收錄對象，以佛萊明漢心血 管危險預估分數分為風險低、中、高三組比較其組內差異。其次將腎絲球過濾率及佛萊明 漢心血管危險預估分數做相關性分析。最後以不同的多變項線性回歸模式分析腎絲球過濾 率估計值對心血管風險的預測能力。 結果：931位的醫院員工，在心血管疾病風險低的組別中，腎絲球過濾率值及其他血液 生化指標都和風險中及高組者有顯著差異。線性回歸則顯示未校正(Model 1)的標準回歸係 數B值為-0.074，及校正(Model 2-5，校正年紀、體重、低密度脂蛋白、三酸甘油脂、血糖 等)，B值分別為-0.036、-0.042、-0.027、-0.033。分析後的p值皆<0.05且95%信賴區間皆未 通過0。 結論：腎絲球過濾率估計值較低者，佛萊明漢心血管危險預估分數相對較高。因此對 於腎功能較差或比之前退步者應提早介入，預防之後心血管疾病發生。

Background and purpose: Cardiovascular disease is the second leading cause of death in Taiwan. Framingham risk score is the most popular tool used to estimate the 10-year cardiovascular risk of an individual; but it is a time consuming tool. On the other hand, there are several studies proved that estimated glomerular filtration rate(eGFR) is significantly associated with cardiovascular risk. Therefore, the aim of this study is to clarify the association between eGFR and Framingham risk score in the population of hospital workers. Methods: This is a prospective, cross-sectional study; the participants were the workers from one hospital in northern Taiwan. The enrolled participants were divided into three groups including low, middle and high cardiovascular risk by Framingham risk score; then we compared the difference of the three groups. Correlation analysis between eGFR and Framingham risk score was also conducted. Finally, multiple variable regression models were built to investigate the ability of eGFR to predict Framingham risk score. Results: 931 hospital workers were analyzed. The difference of eGFR and other biochemistry data were all significantly between low cardiovascular risk group and middle to high cardiovascular risk group. Multiple linear regression showed the B value of unadjusted model(molde 1) was -0.074; the B value of the adjusted models(Model2-5, adjusted by age, body weight, low density lipoprotein, triglycerides, sugar) were -0.036, -0.042, -0.027, -0.033. The p values were all <0.05 and the 95% confidence interval were not including 0. Conclusion: Our findings showed that the lower eGFR might associated with higher Framingham risk score. Thus, aggressive preventive strategies are indicated for the lower eGFR individuals.