O'Malley Bridget R, Raja Nayem, Blue Gillian M, Winlaw David S, Sholler Gary F
The Heart Centre for Children, Sydney Children's Hospital Network, Sydney, Australia.
Sydney Medical School, The University of Sydney, Sydney, Australia.
Cardiol Young. 2024 Oct;34(10):2213-2218. doi: 10.1017/S1047951124025721. Epub 2024 Oct 18.
Complexity stratification for CHD is an integral part of clinical research due to its heterogenous clinical presentation and outcomes. To support our ongoing research efforts into CHD requiring disease severity stratifications, a simplified CHD severity classification system was developed and verified, with potential utility for clinical researchers without specialist CHD knowledge or access to clinical/medical records.
A two-tiered analysis approach was undertaken. First-tier analysis included the audit of a comprehensive system based on: i) timing of intervention, ii) cardiac morphology, and iii) cardiovascular physiology using real patient data (n = 30), across 10 common CHD lesions. Second-tier analysis allowed for a simplified version of the classification system using morphology as a stand-alone predictor. Twelve clinicians of varying specialities involved in CHD care ranked 10 common lesions from least to most severe based on typical presentation and clinical course.
First-tier analysis identified that cardiac morphology was the principal driver of complexity. Second-tier analysis largely confirmed the ranking and classification of the lesions into the broad CHD severity groups, although some variation was noted, specifically among non-cardiac specialists. This simplified version of the classicisation system, with morphology as a stand-alone predictor of severity, allowed for effective stratification for the purposes of analysis.
The findings presented here support this comprehensive and simple CHD severity classification system with broad utility in CHD research, particularly among clinicians and researchers with limited knowledge of CHD. The model may be applied to produce locally relevant research tools.
由于冠心病（CHD）临床表现和预后的异质性，其复杂性分层是临床研究的一个重要组成部分。为了支持我们正在进行的针对需要疾病严重程度分层的冠心病研究工作，我们开发并验证了一种简化的冠心病严重程度分类系统，该系统对没有冠心病专业知识或无法获取临床/医疗记录的临床研究人员具有潜在用途。
采用了两级分析方法。一级分析包括基于以下方面对一个综合系统进行审核：i）干预时机，ii）心脏形态，以及iii）使用真实患者数据（n = 30）的心血管生理学，涉及10种常见的冠心病病变。二级分析允许使用形态学作为独立预测因子的简化版分类系统。12名参与冠心病护理的不同专业的临床医生根据典型表现和临床病程将10种常见病变从最轻到最严重进行了排序。
一级分析确定心脏形态是复杂性的主要驱动因素。二级分析在很大程度上证实了病变在广泛的冠心病严重程度组中的排序和分类，尽管存在一些差异，特别是在非心脏专科医生中。这种以形态学作为严重程度独立预测因子的简化版分类系统，为分析目的提供了有效的分层。
此处呈现的研究结果支持了这种全面且简单的冠心病严重程度分类系统，该系统在冠心病研究中具有广泛用途，特别是在对冠心病知识有限的临床医生和研究人员中。该模型可用于生成与当地相关的研究工具。
