Gemini Lab, Pl. Badalocchio 3/A, 43126 Parma, Italy.
University Hospital Maggiore, Cardiology Unit, Viale Gramsci 14, 43126 Parma, Italy.
Biomed Res Int. 2019 Jul 2;2019:4861951. doi: 10.1155/2019/4861951. eCollection 2019.
The RITMIA™ app (Heart Sentinel™, Parma, Italy) is a novel application that combined with a wearable consumer-grade chest-strap Bluetooth heart rate monitor, provides automated detection of atrial fibrillation (AF), and may be promising for sustainable AF screening programs, since it is known that prolonged monitoring leads to increased AF diagnosis.
The purpose of this study was to examine whether RITMIA™ could accurately differentiate sinus rhythm (SR) from AF compared with gold-standard physician-interpreted 12-lead electrocardiogram (ECG).
In this observational prospective study consecutive patients presenting for elective cardioversion (ECV) of AF, from November 2017 to November 2018, were enrolled. Patients underwent paired 12-lead ECG and RITMIA™ recording, both before and after ECV procedure. The RITMIA™ automated interpretation was compared with 12-lead ECG interpreted by the agreement of two cardiologists. The latter were blinded to the results of the App automated diagnosis. Feasibility, sensitivity, specificity, and K coefficient for RITMIA™ automated diagnosis were calculated.
A total of 100 consecutive patients were screened and enrolled. Five patients did not undergo ECV due to spontaneous restoration of SR. 95 patients who actually underwent ECV were included in the final analysis. Mean age was 66.2±10.7 years; female patients were 20 (21.1%). There were 190 paired ECGs and RITMIA™ recordings. The RITMIA™ app correctly detected AF with 97% sensitivity, 95.6% specificity, and a K coefficient of 0.93.
The automated RITMIA™ algorithm very accurately differentiated AF from SR before and after elective ECV. The only hardware required by this method is a cheap consumer-grade Bluetooth heart rate monitor of the chest-strap type. This robust and affordable RITMIA™ technology could be used to conduct population-wide screening in patients at risk for silent AF, thanks to the long-term monitoring applicability.
RITMIA™ 应用程序（Heart Sentinel™，意大利帕尔马）是一种新颖的应用程序，它与可穿戴的消费级蓝牙心率监测器相结合，可实现心房颤动（AF）的自动检测，并且可能是可持续的 AF 筛查计划的有前途的选择，因为众所周知，延长监测可提高 AF 的诊断率。
本研究旨在检查 RITMIA™ 是否能与金标准医生解读的 12 导联心电图（ECG）相比，准确地区分窦性节律（SR）和 AF。
在这项观察性前瞻性研究中，连续纳入了 2017 年 11 月至 2018 年 11 月期间因 AF 行择期电复律（ECV）的患者。患者在 ECV 前后均接受了 12 导联 ECG 和 RITMIA™ 记录。将 RITMIA™ 的自动解读与两位心脏病专家一致解读的 12 导联 ECG 进行比较。后者对应用程序自动诊断的结果不知情。计算了 RITMIA™ 自动诊断的可行性、敏感性、特异性和 K 系数。
共筛选并纳入了 100 例连续患者。由于 SR 自发恢复，有 5 例患者未行 ECV。实际接受 ECV 的 95 例患者纳入最终分析。平均年龄为 66.2±10.7 岁；女性患者 20 例（21.1%）。共有 190 对 ECG 和 RITMIA™ 记录。RITMIA™ 应用程序正确检测到 AF 的敏感性为 97%，特异性为 95.6%，K 系数为 0.93。
在择期 ECV 前后，自动 RITMIA™ 算法非常准确地将 AF 与 SR 区分开来。这种方法所需的唯一硬件是一种廉价的消费级蓝牙心率监测器，为胸带式。这种强大且经济实惠的 RITMIA™ 技术可以通过长期监测的适用性，用于对有发生无症状 AF 风险的人群进行广泛筛查。
