不同体表面积标准化方法在老年患者Gate's法测算GFR中的适用性研究

目的:以双血浆法为参考标准,评估不同体表面积（BSA）标准化方法在老年患者Gate's法测算肾小球滤过率（GFR）中的适用性研究。方法:91例在我院行双血浆法以及肾动态显像检查的老年患者纳入本研究,分别计算获得tGFR₀和gGFR₀（未行BSA标准化）。根据不同BSA标准化方法（Du Bois公式,Gehan and George公式,Stevenson公式,胡咏梅公式,胡咏梅提出的性别分开计算公式）,分别计算并记录为gGFR_1-5和tGFR_1-5。以双血浆法为参考标准,进行tGFR_x与gGFR_x的相关性分析。根据体重指数（BMI）将患者分为正常及过轻组（A组,42例）和过重及肥胖组（B组,49例）,将相应gGFR记录为gGFR_x-a和gGFR_x-b,并分别与tGFR_x-a和tGFR_x-a进行相关性分析。结果:tGFR₀与gGFR₀的相关性系数r₀=0.723,tGFR_1-5与不同BSA标准化后的gGFR_1-5相关系数r_1-5分别为0.721,0.719,0.720,0.718,0.751,差异具有统计学意义（P值均=0.000）。亚组分析结果显示:A组tGFR与gGFR相关性普遍较好,tGFR与gGFR相关性良好,相关系数r_0-5a分别为0.817,0.828,0.827,0.828,0.826,0.841,但相关系数最高者为使用第5种BSA标准化公式后获得的gGFR,r_5-a=0.841（P<0.05）。B组tGFR与gGFR相关性均较差,相关系数r_0-5b分别为0.634,0.626,0.620,0.623,0.621,0.678,均具有统计学意义（P<0.05）。结论:在计算GFR方面,Gate's法与99mTc-DTPA双血浆法具有较好相关性,但是过重或肥胖患者GFR的准确评估仍为临床难点问题,需要以患者实际情况为基础,进行综合判断。 

The Application Study of Different BSA Normalization Methods in the Evaluation of GFR by Gate's in Elder Patients

Objective: To compare the application value of different BSA normalization methods in the evaluation of GFR by Gate's in elder patients. Methods: The clinical data of 91 cases of patients who performed double plasma clearance method (tGFR₀) and renography examination (gGFR₀) were selected in our study. According to different formulas (DuBois formula, Gehan and Georgeformula, Stevensonformula, Flu Yongmei formula, Hu Yongmei-gender correction formula), the GFR_1-5 were calculated. The correlation of tGFRx and gGFRx were analyzed. The patients were divided into two subgroups according to BMI (group a and group b), and gGFR were recorded as gGFRx-a and gGFRx-b and its correlation with tGFRx-a or tGFRx-b were analyzed. Results: The correlation of tGFR and gGFR was good in whole study cohort, and r_5-a=0.841, which was highest among all paired groups (P<0.05). The correlation of tGFR and gGFR in group b was worse (P<0.05). Conclusion: The evaluation of GFR by Gate's method is well correlated with tGFR, but it is still a difficult clinical question for the GFR evaluation of fat patients, which needs a large sample size of validation.