Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio.
Department of Cardiovascular Medicine, Marshall University, Huntington, West Virginia.
Heart Rhythm. 2018 Oct;15(10):1561-1565. doi: 10.1016/j.hrthm.2018.06.037. Epub 2018 Aug 22.
The Kardia Mobile Cardiac Monitor (KMCM) detects atrial fibrillation (AF) via a handheld cardiac rhythm recorder and AF detection algorithm. The algorithm operates within predefined parameters to provide a "normal" or "possible atrial fibrillation detected" interpretation; outside of these parameters, an "unclassified" rhythm is reported. The system has been increasingly used, but its performance has not been independently tested.
The objective of this study was to evaluate whether the KMCM system can accurately detect AF.
A single-center, adjudicator-blinded case series of 52 consecutive patients with AF admitted for antiarrhythmic drug initiation were enrolled. Serial 12-lead electrocardiograms (ECGs) and nearly simultaneously acquired KMCM recordings were obtained.
There were 225 nearly simultaneously acquired KMCM and ECG recordings across 52 enrolled patients (mean age 68 years; 67% male). After exclusion of unclassified recordings, the KMCM automated algorithm interpretation had 96.6% sensitivity and 94.1% specificity for AF detection as compared with physician-interpreted ECGs, with a κ coefficient of 0.89. Physician-interpreted KMCM recordings had 100% sensitivity and 89.2% specificity for AF detection as compared with physician-interpreted ECGs, with a κ coefficient of 0.85. Sixty-two recordings (27.6%) were unclassified by the KMCM algorithm. In these instances, physician interpretation of KMCM recordings had 100% sensitivity and 79.5% specificity for AF detection as compared with 12-lead ECG interpretation, with a κ coefficient of 0.71.
The KMCM system provides sensitive and specific AF detection relative to 12-lead ECGs when an automated interpretation is provided. Direct physician review of KMCM recordings can enhance diagnostic yield, especially for unclassified recordings.
Kardia 移动心脏监测仪（KMCM）通过手持式心脏节律记录器和房颤检测算法来检测房颤（AF）。该算法在预设参数内运行，提供“正常”或“可能检测到房颤”的解释；超出这些参数范围，则报告“未分类”节律。该系统的使用日益增多，但尚未对其性能进行独立测试。
本研究旨在评估 KMCM 系统是否能准确检测 AF。
这是一项单中心、裁判盲法的连续病例系列研究，纳入了 52 例因心律失常药物治疗而入院的房颤患者。连续获取 12 导联心电图（ECG）和几乎同时获得的 KMCM 记录。
在 52 名入组患者中，共获得了 225 份近乎同时获得的 KMCM 和 ECG 记录（平均年龄 68 岁；67%为男性）。排除未分类记录后，KMCM 自动算法解释与医师解读的 ECG 相比，对 AF 的检测具有 96.6%的敏感性和 94.1%的特异性，κ 值为 0.89。与医师解读的 ECG 相比，医师解读的 KMCM 记录对 AF 的检测具有 100%的敏感性和 89.2%的特异性，κ 值为 0.85。62 份记录（27.6%）未被 KMCM 算法分类。在这些情况下，与 12 导联 ECG 解读相比，医师对 KMCM 记录的解读对 AF 的检测具有 100%的敏感性和 79.5%的特异性，κ 值为 0.71。
当提供自动解读时，KMCM 系统相对于 12 导联 ECG 可提供敏感和特异的 AF 检测。直接对 KMCM 记录进行医师审查可以提高诊断率，尤其是对未分类的记录。
