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QRS fragmentation index as a new discriminator for early diagnosis of heart diseases

机译:QRS碎片指数可作为心脏病早期诊断的新指标

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In the past few years, the presence of fragmentation in the QRS complex has been demonstrated to be related to diseases such as myocardial fibrosis, cardiac sarcoidosis, arrythmogenic cardiopathies, acute coronary syndrome, and Brugada syndrome, among others. The detection of fragmentation in the QRS is usually carried out manually, which represents a subjective pattern recognition task that demands an effort by the clinician, increasing with the number of patients. These problems have made the process of fragmentation detection a good candidate to its automatization. In this work, we used a database with over six-thousand 12-lead ECG from Hospital Virgen de la Arrixaca de Murcia (Spain), which where digitally recorded with GE MAC5000. Affected and non-affected patients records were extracted for computerized analysis. Clinical supervision was performed for gold-standard development and for signal classification. Fragmentation detection algorithms were developed using first and second derivatives calculation in the pre-qualified segments of the signal, after fiducial point detection. The obtained results were 96.88% sensitivity, 72.92% specificity, and 82.50% accuracy. These results confirm that it is possible to automatically detect fragmentation, constituting a relevant tool to pre-qualify patients for further diagnostic-tests, and it also opens new opportunities for computerized diagnosis.
机译:在过去的几年中,QRS复合体的碎片化已被证明与诸如心肌纤维化,心脏结节病,心律失常性心律失常,急性冠状动脉综合征和Brugada综合征等疾病有关。 QRS中碎片的检测通常是手动进行的,这代表了一种主观的模式识别任务,需要临床医生的努力,并且随着患者数量的增加而增加。这些问题使碎片检测过程成为其自动化的良好候选者。在这项工作中,我们使用了来自西班牙Virgen de la Arrixaca de Murcia医院的超过六千条12导联心电图的数据库,并通过GE MAC5000进行了数字记录。提取受影响和未受影响的患者记录以进行计算机分析。对金标准制定和信号分类进行了临床监督。在基准点检测之后,使用信号的预限定段中的一阶和二阶导数计算来开发碎片检测算法。获得的结果为96.88%的灵敏度,72.92%的特异性和82.50%的准确性。这些结果证实,有可能自动检测碎片,构成使患者具备资格进行进一步诊断测试的相关工具,并且还为计算机化诊断打开了新的机会。

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