School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing 246133, China; Anhui Engineering Research Center of Intelligent Perception and Elderly Care, Chuzhou University, Chuzhou 239000, China.
The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing 246133, China.
Comput Biol Med. 2024 Mar;171:108155. doi: 10.1016/j.compbiomed.2024.108155. Epub 2024 Feb 14.
The current models of estimating vascular age (VA) primarily rely on the regression label expressed with chronological age (CA), which does not account individual differences in vascular aging (IDVA) that are difficult to describe by CA. This may lead to inaccuracies in assessing the risk of cardiovascular disease based on VA. To address this limitation, this work aims to develop a new method for estimating VA by considering IDVA. This method will provide a more accurate assessment of cardiovascular disease risk.
Relative risk difference in vascular aging (RRDVA) is proposed to replace IDVA, which is represented as the numerical difference between individual predicted age (PA) and the corresponding mean PA of healthy population. RRDVA and CA are regard as the influence factors to acquire VA. In order to acquire PA of all samples, this work takes CA as the dependent variable, and mines the two most representative indicators from arteriosclerosis data as the independent variables, to establish a regression model for obtaining PA.
The proposed VA based on RRDVA is significantly correlated with 27 indirect indicators for vascular aging evaluation. Moreover, VA is better than CA by comparing the correlation coefficients between VA, CA and 27 indirect indicators, and RRDVA greater than zero presents a higher risk of disease.
The proposed VA overcomes the limitation of CA in characterizing IDVA, which may help young groups with high disease risk to promote healthy behaviors.
目前估算血管年龄（VA）的模型主要依赖于用年龄（CA）表示的回归标签，而没有考虑到个体血管老化（IDVA）的差异，这些差异很难用 CA 来描述。这可能导致基于 VA 评估心血管疾病风险的不准确。为了解决这一局限性，本研究旨在开发一种新的方法来考虑 IDVA 来估算 VA。这种方法将提供更准确的心血管疾病风险评估。
提出相对血管老化风险差异（RRDVA）来替代 IDVA，它表示个体预测年龄（PA）与健康人群相应平均 PA 之间的数值差异。RRDVA 和 CA 被视为获取 VA 的影响因素。为了获取所有样本的 PA，本研究将 CA 作为因变量，从动脉硬化数据中挖掘出两个最具代表性的指标作为自变量，建立一个回归模型来获取 PA。
基于 RRDVA 的提出的 VA 与 27 个血管老化评估的间接指标显著相关。此外，通过比较 VA、CA 与 27 个间接指标之间的相关系数，VA 优于 CA，并且 RRDVA 大于零表示疾病风险更高。
提出的 VA 克服了 CA 在描述 IDVA 方面的局限性，这可能有助于高疾病风险的年轻群体促进健康行为。
