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A Power Law for Determining Renal Sufficiency Using Volume of Distribution and Weight from Bolus 99mTc-DTPA, Two Blood Sample, Pediatric Data

机译:利用散量99mTc-DTPA,两份血液样本和儿科数据的分布体积和重量确定肾功能充足的幂定律

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Objectives: (1) Explore power laws for estimating the one-compartment glomerular filtration rate (G1), i.e., E(G1), as functions of compartment volume (V), patient mass (W), age (A), height (H) and sex (S). (2) Propose a renal sufficiency index, RSI=G1/E(G1). (3) Present the best estimator, E(G1) = f(V,W) = 10.988 V0.64717W0.20185. (4) Present the first clinical application of RSI, prediction of relative bone age (RBA = E(A)/A). Methods: 130 99mTc-DTPA imaging and G1 studies were screened to find 44 normal studies in children 1.46 to 18.5 years old. Results: E(G1) formulae of the body surface area type, i.e., f(W,H,S) and F(W,H), were found to be statistically unwarranted. Statistically acceptable formulae, in descending adjusted R2, were f(V,W), f(V,A), f(V,H), f(V), f(W,A,H), f(W), f(H) and f(A). Kleiber''s law, E(G1) prop Wfrac34, seems to confirm the previously reported relationship GFRinulin ap 0.87G1. Our best G1 estimator, f(V,W), may be related to a physiological volume. RSI as predicted by f(V,W) had the smallest relative standard deviation, 11.3%, no regression bias and good agreement with clinical classification at 95% specificity. RBA was found to be correlated with RSI, with a peak at 88% E(RSI), with RSI accounting for 25% of its variance. Conclusions: Our best RSI predictor, RSI = 90.927gammaV0.35283W-0.20185, should be capable of detecting mildly reduced (14.1%) renal sufficiency.
机译:目标:(1)探索幂定律,以估计作为隔室容积的函数的单室肾小球滤过率(G 1 )即E(G 1 )( V),患者体重(W),年龄(A),身高(H)和性别(S)。 (2)提出肾功能指数RSI = G 1 / E(G 1 )。 (3)给出最佳估计量E(G 1 )= f(V,W)= 10.988 V 0.64717 W 0.20185 。 (4)提出RSI的第一个临床应用,即预测相对骨龄(RBA = E(A)/ A)。方法:筛选130份 99m Tc-DTPA显像和G 1 研究,以发现44例1.46至18.5岁儿童的正常研究。结果:发现人体表面积类型的E(G 1 )公式,即f(W,H,S)和F(W,H),在统计上是不必要的。在下降的调整后的R 2 中,统计上可接受的公式为f(V,W),f(V,A),f(V,H),f(V),f(W,A, H),f(W),f(H)和f(A)。克莱伯定律E(G 1 )prop W frac34 似乎证实了先前报道的GFR 菊粉 ap 0.87G 1 。我们最好的G 1 估计量f(V,W)可能与生理量有关。由f(V,W)预测的RSI相对标准偏差最小,为11.3%,无回归偏倚,在95%的特异性下与临床分类具有良好的一致性。发现RBA与RSI相关,E(RSI)的峰值为88%,RSI占其方差的25%。结论:我们最好的RSI预测因子RSI = 90.927gammaV 0.35283 W -0.20185 ,应能够检测出轻度降低(14.1%)的肾功能衰竭。

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