Monash University, Eastern Health Clinical School, Department of Cardiology, Box Hill Hospital, Melbourne, Victoria, Australia; The University of Melbourne Clinical School, Austin Health Department of Cardiology, Melbourne, Victoria, Australia.
Monash University, Eastern Health Clinical School, Department of Cardiology, Box Hill Hospital, Melbourne, Victoria, Australia.
Am Heart J. 2018 Nov;205:149-153. doi: 10.1016/j.ahj.2018.08.001. Epub 2018 Aug 23.
Despite the appeal of smartphone-based electrocardiograms (ECGs) for arrhythmia screening, a paucity of data exists on the accuracy of primary care physicians' and cardiologists' interpretation of tracings compared with the device's automated diagnosis. Using 408 ECGs in 51 patients, we demonstrate a variable accuracy in clinician interpretation of smartphone-based ECGs, with only cardiologists demonstrating satisfactory agreement when referenced against a 12-lead ECG. Combining the device automated diagnostic algorithm with cardiologist interpretation of only uninterpretable traces yielded excellent results and provides an efficient, cost-effective workflow for the utilization of a smartphone-based ECG in clinical practice.
尽管基于智能手机的心电图 (ECG) 在心律失常筛查方面具有吸引力，但与设备的自动诊断相比，初级保健医生和心脏病专家对心电图的解释准确性的数据却很少。我们使用 51 名患者的 408 份心电图证明了基于智能手机的心电图在临床医生解释中的准确性存在差异，只有心脏病专家与 12 导联心电图对照时才显示出令人满意的一致性。将设备自动诊断算法与仅对不可解释的心电图进行心脏病专家解释相结合，可获得出色的结果，并为在临床实践中使用基于智能手机的心电图提供了高效、具有成本效益的工作流程。
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