摘要
目的比较汇集队列风险方程(pooled cohort risk equation,PCE)和改良Framingham卒中风险评估量表(revised Framingham stroke risk profile,R-FSP)在健康体检人群卒中风险评估中的应用。方法随机抽取2017年1-12月于宜宾市第二人民医院健康管理中心体检的40~70岁健康体检者1277例,采用R-FSP和PCE评估其10年卒中风险,并比较R-FSP和PCE在卒中风险评估应用中的一致性。结果用R-FSP和PCE评估1277例健康体检者的10年卒中风险概率分别为5.8%和6.1%,男性高于女性[R-FSP(6.0%vs 5.5%,t=3.184,P=0.002),PCE(6.5%vs 5.7%,t=4.700,P=0.000)],BMI≥24 kg/m~2者高于BMI<24 kg/m~2者[R-FSP(5.5%vs6.5%),PCE(5.9%vs6.8%)],3个年龄段(40~49岁、50~59岁和60~70岁)体检者卒中风险差异也有统计学意义[R-FSP(3.6%vs 5.9%vs 9.2%,F=7.213,P=0.003),PCE(4.0%vs 6.0%vs 9.9%,F=11.628,P=0.000)]。R-FSP和PCE评估卒中风险结果有高度一致性,其Pearson相关系数和组内相关系数(intraclass correlation coefficient,ICC)分别为0.719和0.757(P<0.05)。结论 R-FSP和PCE预测卒中风险结果一致,研究者可以根据实际情况选择合适的预测工具。
Objective To compare the application of pooled cohort risk equations(PCE) and revised Framingham stroke risk profile(R-FSP) in assessing stroke risk in healthy people through physical examination, to provide a reference for preventing stroke more effectively.Methods A total of 1277 healthy people(40~70 years) through physical examination were selected randomly from No.2 Peoples' s Hospital from January to December 2017. The 10-year stroke risk of all subjects were evaluated using R-FSP and PCE, and the consistency of R-FSP and PCE in predicting stroke risk were compared.Results The stroke risk assessed by R-FSP and PCE in 1277 subjects were 5.8% and 6.1% respectively. Male had a higher stroke risk than female(R-FSP: 6.0% vs 5.5%, t=3.184, P=0.002; PCE: 6.5% vs 5.7%, t=4.700, P=0.000), people with a BMI ≥24 kg/m~2 had a higher risk than those with BMI <24 kg/m~2(R-FSP: 5.5% vs 6.5%; PCE: 5.9% vs 6.8%), and different ages(40~49 years, 50~59 years and 60~70 years) had different risks(R-FSP: 3.6% vs 5.9% vs 9.2%, F=7.213, P=0.003; PCE: 4.0% vs 6.0% vs 9.9%, F=11.628, P=0.000). R-FSP and PCE had high consistency in assessing the stroke risk, with Pearson correlation coefficient and intraclass correlation coefficient being 0.719 and 0.757 respectively(P<0.05). Conclusions The R-FSP and PCE are similar in assessing the stroke risk. The users can choose any appropriate tool to predict stroke risk according to the conditions.
引文
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