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利用体型和心动周期长度进行多元回归分析,以预测犬类的超声心动图变量。

Multiple regression analysis, using body size and cardiac cycle length, in predicting echocardiographic variables in dogs.

作者信息

Jacobs G, Mahjoob K

机构信息

Department of Small Animal Medicine, College of Veterinary Medicine, University of Georgia, Athens 30602.

出版信息

Am J Vet Res. 1988 Aug;49(8):1290-4.

PMID:3178024
Abstract

A significant (P less than 0.0001) positive correlation was demonstrated between left ventricular internal chamber dimension in diastole or systole and body weight, body surface area, cycle length, and the square root of cycle length. On the basis of adjusted coefficients of determination, multiple regression analysis, using body weight or body surface area and cycle length or the square root of cycle length, was superior to separate simple regression with these variables in accounting for variations in left ventricular internal chamber dimensions. Shortening fraction had a significant (P less than 0.0001) negative correlation and left ventricular free wall measurements had a significant (P less than 0.0001) positive correlation to body weight and body surface area. For these echocardiographic variables, correlation to the square root of cycle length was insignificant (P greater than 0.05), and a multiple regression model was not helpful in developing confidence intervals. Septal wall measurements were not correlated with body weight, body surface area, cycle length, or the square root of cycle length.

摘要

舒张期或收缩期左心室内径与体重、体表面积、心动周期长度及心动周期长度的平方根之间呈显著正相关(P<0.0001)。基于调整后的决定系数,使用体重或体表面积以及心动周期长度或心动周期长度的平方根进行的多元回归分析,在解释左心室内径变化方面优于对这些变量进行单独的简单回归分析。缩短分数与体重和体表面积呈显著负相关(P<0.0001),左心室游离壁测量值与体重和体表面积呈显著正相关(P<0.0001)。对于这些超声心动图变量,与心动周期长度的平方根的相关性不显著(P>0.05),多元回归模型无助于构建置信区间。室间隔壁测量值与体重、体表面积、心动周期长度或心动周期长度的平方根均无相关性。

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