健康成人超声心动图正常值生理变异校正的方法学研究及其软件实现

Echocardiography is the most commonly used technique for the non-invasive assessment of cardiac structures, systolic and diastolic functions and cardiovascular hemodynamics in routine clinical practice. The echocardiographic measurements are not only impacted by pathological conditions, but also vary significantly with demographic and anthropometric factors such as ethnicity, body size, gender and age. A widely representative echocardiographic normal reference values from Chinese population is so far not available. It is of important theoretical significance and clinical value to establish the population-based echocardiographic normal reference values in healthy adults and to eliminate, or at least substantially decrease, the overlap between normal and abnormal ranges that could be influenced by body size variables using appropriate scaling approaches. Generally, the relationship between the cardiac variables and body size variables are nonlinear rather than linear. The clinically exclusive use of isometric model (linear) to scale the cardiac variable for body surface area (BSA) is theoretically, mathematically and empirically flawed. Therefore, the purpose of this project is: (1) to establish formulas for calculating BSA, body volume, density and fat-free mass (FFM), and their normal reference ranges in healthy adults; (2) to build-up the most appropriate and optimized multiple regression model between each of 34 M-mode/two-dimensional echocardiographic parameters and physical variables using the allometric model (nonlinear); (3) to establish the normal reference ranges of measured and normalized echocardiographic parameters; and (4) to establish a software system for the online judgement whether the measured and normalized echocardiographic values in a individual are normal or not.

超声心动图是临床无创性评价心脏结构、功能和血流动力学的最常用技术，其正常值不仅受疾病的影响，而且受包括种族、体型、性别和年龄等生理性因素的影响，中国尚无具有广泛代表性的正常值标准。因此，建立中国健康人群超声心动图正常值并对其生理变异进行科学合理的校正，具有十分重要的理论意义和临床实用价值。心脏变量与体格变量之间多呈非线性相关，临床上普遍采用的体表面积（BSA）和等距模型对心脏变量进行线性校正的方法，无论从理论上还是经验上均存在明显缺陷。本研究旨在：（1）建立我国健康成年人群BSA、体积、比重和非脂肪体重（FFM）的计算公式及其正常值范围；（2）采用非等距模型筛选并建立34个M型/二维超声心动图参数对多个体格变量进行校正的最优多元回归模型；（3）建立34个M型/二维超声心动图参数正常值及其校正值的参考值范围；（4）建立在线判定受检者超声心动图参数测量值及其校正值正常与否的软件分析系统。

多数二维与多普勒超声心动图参数测值受包括年龄、性别、体型大小和静息心率等生物学特征变量的显著影响，有必要对超声心动图参数的生理性变异进行校正，以便于不同个体间以及正常与异常的鉴别。本项目旨在提出并验证不同超声心动图参数与不同的生物学特征变量呈现不同的非线性相关关系，并在健康成人中建立多元非线性校正方程及校正值的参考值范围。方法：在1224例BMI <25.0 kg/m2的健康成人中对34个二维参数和23个左室多普勒参数建立并验证优化的多元非线性校正模型（OMAM）及其校正方程。采用BSA校正的单因素线性校正模型（SVIM）作为对比。成功校正的标准设定为：校正值与生物学特征变量间无生物学及统计学意义的显著相关（r>0.20 or r<-0.20, P<0.05），并且校正值与非校正值间保持显著相关关系（P<0.05）。研究结果显示：（1）校正前，所有超声心动图参数与一个或多个生物学特征变量显著相关，85.3%的二维参数和47.8%的多普勒参数存在男女性别间的显著差异；（2）OMAM模型对34个二维参数的校正成功率达100%，可消除96.6%参数的性别间差异，而SVIM模型的校正成功率仅为11%；（3）OMAM模型对23个左室多普勒参数的校正成功率达100%，可消除81.8%参数的性别间差异，而SVIM模型的校正成功率为0%；（4）建立了二维与多普勒参数OMAM校正值的参考值范围；（5）在210例成人中建立并验证了BSA计算公式，其准确性优于国际上通用的Du Bois公式。由此得出结论：不同的二维和多普勒超声心动图参数与一个或多个生物学特征变量间呈非线性相关，本项目建立的OMAM校正方程可成功校正生物学变量所产生的生理性差异，明显优于SVIM模型，所建立的BSA计算公式的准确性优于国际上通用的Bu Bois公式，应在临床中推广应用。