Objectives This study aimed to derive age-specific multivariate reference regions (MVRs) able to classify subjects into those having normal or abnormal filling patterns and to evaluate the prognostic impact of this classification.

Background The integration of several parameters is necessary to diagnose disorders of left ventricular (LV) filling because no single measurement accurately describes the complexity of diastolic function. However, no generally accepted validated multiparametric algorithm currently exists.

Methods A cohort of 1,240 apparently healthy subjects from HUNT (Nord-Trøndelag Health Study) with measured early (E) and late (A) mitral inflow velocity and early mitral annular diastolic tissue velocity (e′) were used to derive univariate 95% reference bands and age-specific MVRs. Subsequently, the prognostic impact of this MVR-based classification was evaluated by Cox regression in a community-based cohort (n = 726) and in a cohort of subjects with recent acute myocardial infarction (n = 551). Both evaluation cohorts were derived from VaMIS (the Västmanland Myocardial Infarction Study).

Results Univariate reference bands and MVRs are presented graphically and as regression equations. After adjustment for sex, age, hypertension, body mass index, diabetes, prior ischemic heart disease, LV mass, LV ejection fraction, and left atrial size, the hazard ratio associated with abnormal filling patterns in the community-based cohort was 3.5 (95% confidence interval: 1.7 to 7.0; p < 0.001) and that in the acute myocardial infarction cohort was 1.8 (95% confidence interval: 1.1 to 2.8; p = 0.011).

Conclusions This study derived age-specific MVRs for identification of abnormal LV filling patterns and showed, in a community-based cohort and in a cohort of patients with recent acute myocardial infarction, that these MVRs conveyed important prognostic information. An MVR-based classification of LV filling patterns could lead to more consistent diagnostic algorithms for identification of different filling disorders.

目的本研究旨在得出特定年龄的多元参考区域（MVR），该区域可将受试者分类为具有正常或异常充盈模式的受试者，并评估该分类的预后影响。

背景技术由于没有单一的测量能够准确地描述舒张功能的复杂性，因此必须综合几个参数来诊断左心室（LV）充盈障碍。但是，目前不存在公认的经过验证的多参数算法。

方法采用来自HUNT（Nord-Trøndelag健康研究）的1,240名明显健康的受试者队列，测量其早期（E）和晚期（A）的二尖瓣流入速度和早期二尖瓣环舒张组织速度（e'），得出95％的单变量参考值乐队和特定年龄段的MVR。随后，通过基于Cox回归的基于社区的队列（n = 726）和最近患有急性心肌梗死的受试者（n = 551）对这种基于MVR的分类的预后影响进行了评估。两个评估队列均来自VaMIS（Västmanland心肌梗塞研究）。

结果单变量参考带和MVR以图形方式显示为回归方程。在对性别，年龄，高血压，体重指数，糖尿病，先前缺血性心脏病，左室重量，左室射血分数和左心房大小进行调整后，社区队列中与异常充盈模式相关的危险比为3.5（95 ％置信区间：1.7至7.0； p <0.001），急性心肌梗死队列的置信区间为1.8（95％置信区间：1.1至2.8； p = 0.011）。

结论这项研究得出了特定年龄的MVRs，用于识别异常的LV充盈模式，并在以社区为基础的队列研究和近期患有急性心肌梗死的患者队列中显示，这些MVRs可传达重要的预后信息。基于MVR的LV充盈模式分类可以导致更一致的诊断算法，用于识别不同的充盈障碍。