Tóth K, Mezey B, Juricskay I, Jávor T
1st Internal Med. Clinic, Department of Cardiology, University Medical School, Pécs.
Acta Med Hung. 1990;47(1-2):31-42.
The non-invasive differential diagnosis of ischaemic heart disease (IHD) and acute myocarditis or secondary cardiomyopathy following myocarditis can be difficult on the basis of the complaints, resting and exercise ECG and nuclear cardiological tests. 92 patients (mean age: 46 years) in the first step and 100 patients (mean age: 44 years) in the second step all with heart troubles, were examined. Besides determination of the routine parameters, nuclear haemodynamical and haemorheological measurements were carried out. Then each group of the patients was classified into 4 subgroups: 1) myocardial infarction /n:9/, 2) IHD /52/, 3) myocarditis /28/, 4) chronic cor pulmonale (CCP) /3/ subgroups in the first group and 1) normal /n:20/, 2) IHD /50/, 3) myocarditis /16/, 4) chronic cor pulmonale /14/ subgroups in the second group. The patients were reclassified by our multivariate pattern recognition algorithm (PRIMA). The average effectiveness of our method was over 80%, the recognition abilities for the subgroups (classes) ranged between 71 and 100%. An analysis of the discrimination power of the properties has made it evident that the haemorheological features were more characteristic than the haemodynamic ones in distinguishing the two differential-diagnostically critical groups. Our results show that our multivariate statistical method can be useful for the computer-aided decision in cardiological diagnostics.
基于患者主诉、静息及运动心电图以及核心脏学检查，对缺血性心脏病（IHD）与急性心肌炎或心肌炎后继发性心肌病进行无创鉴别诊断可能存在困难。第一步检查了92例患者（平均年龄：46岁），第二步检查了100例患者（平均年龄：44岁），所有患者均有心脏问题。除了测定常规参数外，还进行了核血液动力学和血液流变学测量。然后将每组患者分为4个亚组：第一组中的1）心肌梗死/n:9/，2）IHD/52/，3）心肌炎/28/，4）慢性肺心病（CCP）/3/亚组；第二组中的1）正常/n:20/，2）IHD/50/，3）心肌炎/16/，4）慢性肺心病/14/亚组。通过我们的多变量模式识别算法（PRIMA）对患者进行重新分类。我们方法的平均有效性超过80%，对亚组（类别）的识别能力在71%至100%之间。对各属性判别力的分析表明，在区分两个鉴别诊断关键组时，血液流变学特征比血液动力学特征更具特征性。我们的结果表明，我们的多变量统计方法可用于心脏病诊断中的计算机辅助决策。
