Edwards A, Deen W M
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge 02139, USA.
Am J Physiol. 1995 Apr;268(4 Pt 2):F736-45. doi: 10.1152/ajprenal.1995.268.4.F736.
The theoretical effects of the glomerular transmural hydraulic pressure difference (delta P) on the sieving coefficients (theta i) of macromolecules of varying size have led to a number of attempts to use sieving curves to estimate delta P noninvasively, with inconsistent results. The objective of this study was to determine the extent to which experimental errors and imperfections in the theoretical models limit the ability to obtain reliable estimates of delta P using this method. Our approach was to generate many sets of synthetic "experimental data" using computer simulations of glomerular sieving and to compute values of delta P by fitting models to those data in the presence of various types and magnitudes of errors. Unbiased experimental errors were simulated by adding random amounts to individual values of theta i, and systematic errors were investigated by using a model based on one type of pore-size distribution to fit "data" generated using a model of a different type. We found that with random errors in theta i only, the estimate of delta P was accurate to within +/- 4 mmHg nearly all of the time, provided that the standard deviation, sigma i, was < or = 5% of theta i. When there were also systematic errors arising from the use of an "incorrect" form of pore-size distribution, a useful predictor of success was the probability P that the residuals, the differences between the measured and predicted sieving coefficients, were randomly distributed. A value of P > 0.2, as calculated from the algebraic signs of the residuals, indicated a high likelihood that the pressure estimate was accurate, provided that the random errors were sufficiently small. When P > 0.2, the fitted value of delta P was within +/- 4 mmHg of the true value in about 90%, 80%, and 70% of the cases examined when sigma i was < or = 2%, 5%, or 10% of theta i, respectively. An analysis of published data from a number of experimental studies indicated, however, that the favorable conditions of small sigma i and large P are extremely difficult to achieve, making it unlikely that an accurate group-mean value of delta P will be estimated from any given set of sieving data. Significant experimental and theoretical advances will be needed to make this a reliable method for estimating glomerular pressure.
肾小球跨壁液压差（δP）对不同大小大分子筛分系数（θi）的理论影响，引发了许多尝试，试图利用筛分曲线无创地估算δP，但结果并不一致。本研究的目的是确定理论模型中的实验误差和缺陷在多大程度上限制了使用该方法获得可靠δP估计值的能力。我们的方法是通过肾小球筛分的计算机模拟生成多组合成“实验数据”，并在存在各种类型和大小误差的情况下，通过将模型拟合到这些数据来计算δP值。通过向θi的各个值添加随机量来模拟无偏实验误差，并使用基于一种孔径分布类型的模型来拟合使用不同类型模型生成的“数据”，以此研究系统误差。我们发现，仅在θi存在随机误差的情况下，只要标准差σi≤θi的5%，δP的估计几乎在所有情况下都精确到±4 mmHg以内。当由于使用“不正确”的孔径分布形式而出现系统误差时，成功的一个有用预测指标是残差（即测量筛分系数与预测筛分系数之间的差异）呈随机分布的概率P。根据残差的代数符号计算得出的P值>0.2，表明压力估计准确的可能性很高，前提是随机误差足够小。当P>0.2时，在σi分别≤θi的2%、5%或10%的情况下，所研究案例中约90%、80%和70%的δP拟合值在真实值的±4 mmHg范围内。然而，对多项实验研究发表数据的分析表明，σi小且P大的有利条件极难实现，因此不太可能从任何给定的一组筛分数据中估计出准确的δP组均值。要使这成为一种可靠的肾小球压力估计方法，还需要重大的实验和理论进展。
