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首页> 外文期刊>Resuscitation. >An algorithm to discriminate supraventricular from ventricular tachycardia in automated external defibrillators valid for adult and paediatric patients.
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An algorithm to discriminate supraventricular from ventricular tachycardia in automated external defibrillators valid for adult and paediatric patients.

机译:一种在成人和儿童患者有效的自动体外除纤颤器中区分室上性和室性心动过速的算法。

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AIM: To adapt adult automated external defibrillator (AED) arrhythmia analysis algorithms for paediatric use through the addition of an algorithm to accurately discriminate supraventricular tachycardia (SVT) from ventricular tachycardia (VT) that is valid for both adult and paediatric patients. MATERIALS AND METHODS: An adult database of 89 SVT and 191 VT records from 280 patients and a paediatric database of 322 SVT and 66 VT records from 260 paediatric and adolescent patients were used. The databases were split into two equal groups with respect to numbers of records and patients for development and testing. The discrimination method consisted of a logistic regression classifier based on two features obtained from the spectral analysis of 3.2s ECG segments of the records. RESULTS: The algorithm had an overall accuracy of 98.2% (656/668, one-sided confidence interval (CI) 97.1%). In terms of SVT/VT discrimination, the SVT specificity was 98.1% (403/411, one-sided CI 96.5%), and the VT sensitivity was 98.4% (253/257, one-sided CI 96.5%). In terms of shocko-shock decisions, the specificity for SVT increased to 99.0% (407/411, one-sided CI 97.8%), 98.8% (318/322, one-sided CI 97.2%) for the paediatric and 100% (89/89, one-sided CI 96.5%) for the adult patients. CONCLUSION: A new algorithm to discriminate SVT/VT was designed that showed high SVT specificity and VT sensitivity in both adults and children. This algorithm could be incorporated into current AEDs with arrhythmia analysis algorithms designed for adult patients to accurately diagnose fast-rate paediatric SVT.
机译:目的:通过添加一种算法,使成人自动体外除颤器(AED)心律失常分析算法适用于儿科,以准确地区分室上性心动过速(SVT)和室性心动过速(VT),该方法对成人和儿科患者均有效。材料与方法:使用了来自280位患者的89条SVT和191条VT记录的成人数据库,以及来自260位儿童和青少年患者的322条SVT和66条VT记录的儿科数据库。根据记录数量和用于开发和测试的患者,将数据库分为两个相等的组。判别方法包括一个逻辑回归分类器,该分类器基于从记录的3.2s ECG段的频谱分析中获得的两个特征。结果:该算法的整体准确率为98.2%(656/668,单侧置信区间(CI)为97.1%)。在SVT / VT鉴别方面,SVT特异性为98.1%(403/411,单侧CI为96.5%),VT敏感性为98.4%(253/257,单侧CI为96.5%)。就休克/无休克决定而言,小儿SVT的特异性增至99.0%(407/411,单侧CI为97.8%),小儿SVT的特异性为98.8%(318/322,单侧CI 97.2%),而儿童为100 %(89/89,一侧CI 96.5%)为成年患者。结论:设计了一种区分SVT / VT的新算法,该算法在成年人和儿童中均显示出较高的SVT特异性和VT敏感性。该算法可以与心律失常分析算法结合到当前的AED中,该算法设计用于成年患者,以准确诊断快速儿科SVT。

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