基于人工智能的 2 小时 Holter 监测在室性早搏和室上性收缩检测中的诊断效率

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-04-08 DOI:10.1002/clc.24266

Qiong Huang MS, Yuansheng Fan MS, Jialin Wang BS, Zhiyang Xu MS, Linfeng Yang BS, Junhong Wang MD, PhD, Yiyang Zhan MD, PhD, Xiangqing Kong MD, PhD, Ningtian Zhou MD, PhD

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引用次数: 0

摘要

背景心电图（ECG）和 24 小时 Holter 监测（24 h-Holter）为室性早搏和室上性收缩（PVC 和 PSVC）提供了有价值的信息。目前，基于人工智能（AI）的 2 小时单导联 Holter（2 h-Holter）监测可为 PSVC/PVC 诊断提供更好的策略。假设人工智能与单导联 Holter 监测相结合可提高 PSVC/PVC 的检测率。方法在 2022 年 8 月至 2023 年期间，共招募了 170 名患者。所有患者同时佩戴两种设备，然后比较诊断效率，包括 24 h Holter 和 2 h Holter 检测 PSVC/PVC 的灵敏度/特异性/阳性预测值（PPV）和阴性预测值（NPV）。结果与24 h-Holter相比，接受2 h-Holter的患者的PPV和NPV分别为76.00%/87.50%和96.35%/98.55，PSVC/PVC检测的敏感性和特异性分别为79.17%/91.30%和95.65%/97.84%。PSVC 和 PVC 的 ROC 曲线下面积（AUC）分别为 0.885 和 0.741（p < .0001）。结论 2 h-Holter 的潜在优势在于缩短了佩戴时间、提高了便利性和诊断的一致性。

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The diagnostic efficiency of artificial intelligence based 2 hours Holter monitoring in premature ventricular and supraventricular contractions detection

Background

Electrocardiography (ECG) and 24 hours Holter monitoring (24 h-Holter) provided valuable information for premature ventricular and supraventricular contractions (PVC and PSVC). Currently, artificial intelligence (AI) based 2 hours single-lead Holter (2 h-Holter) monitoring may provide an improved strategy for PSVC/PVC diagnosis.

Hypothesis

AI combined with single-lead Holter monitoring improves PSVC/PVC detection.

Methods

In total, 170 patients were enrolled between August 2022 and 2023. All patients wore both devices simultaneously; then, we compared diagnostic efficiency, including the sensitivity/specificity/positive predictive-value (PPV) and negative predictive-value (NPV) in detecting PSVC/PVC by 24 h-Holter and 2 h-Holter.

Results

The PPV and NPV in patients underwent 2 h-Holter were 76.00%/87.50% and 96.35%/98.55, respectively, and the sensitivity and specificity were 79.17%/91.30%, and 95.65%/97.84% in PSVC/PVC detection compared with 24 h-Holter. The areas under the ROC curves (AUCs) for PSVC and PVC were 0.885 and 0.741, respectively (p < .0001).