Higueras Javier, Olmos Carmen, Palacios-Rubio Julián, Gómez-Polo Juan Carlos, Martínez-Losas Pedro, Ruiz-Pizarro Virginia, Bover Ramón, Pérez-Villacastín Julián
Hospital Clinico San Carlos, Madrid, Spain.
Cardiol J. 2018 Aug 29;27(2):136-41. doi: 10.5603/CJ.a2018.0079.
The aim of the study was to create a straightforward method to rule out abnormalities in electrocardiograms (ECGs) performed in patients with pacemakers.
The TBC method screens the ECG for any of the following findings: Tachycardia with pacing spikes, Bradycardia without spikes and Chaos with spikes unrelated to QRS-T complexes. T was considered to advise for patient assessment and B and C to require referral for urgent pacemaker evaluation. The diagnostic accuracy of the algorithm was validated using a cohort of 151 ECGs with normal and dysfunctional pacemakers. The effect of the algorithm was then evaluated for diagnostic skills and management of patients with pacemakers by non-cardiologists, comparing their diagnostic accuracy before and after teaching the algorithm.
The TBC algorithm had a sensitivity of 86% and a specificity of 94% in diagnosing a malfunctioning pacemaker. The diagnostic skills and patient referral were significantly improved (74.8% vs. 89.5%, p < 0.001; and 57.4% vs. 83%, p < 0.001).
TBC is an easy to remember and apply method to rule out severe abnormalities in ECGs of patients with pacemakers. TBC algorithm has a very good diagnostic capability and is easily applied by non-expert physicians with good results.
本研究的目的是创建一种简单的方法,以排除起搏器患者心电图(ECG)中的异常情况。
TBC方法对心电图进行筛查,以查找以下任何一种情况:伴有起搏尖峰的心动过速、无尖峰的心动过缓以及与QRS-T复合波无关的伴有尖峰的紊乱情况。T被认为建议对患者进行评估,而B和C则需要转诊以进行紧急起搏器评估。使用一组151份正常和功能失调起搏器的心电图验证了该算法的诊断准确性。然后通过非心脏病专家评估该算法对起搏器患者的诊断技能和管理效果,比较他们在学习该算法前后的诊断准确性。
TBC算法在诊断起搏器故障方面的敏感性为86%,特异性为94%。诊断技能和患者转诊情况有显著改善(74.8%对89.5%,p<0.001;57.4%对83%,p<0.001)。
TBC是一种易于记忆和应用的方法,可排除起搏器患者心电图中的严重异常情况。TBC算法具有很好的诊断能力,非专家医生也能轻松应用并取得良好效果。