Continuous AI-assisted ECG monitoring over 72 hours in 60 patients with acute pulmonary embolism revealed progressive recovery of cardiac electrophysiological and autonomic function.
Cohort (n=60)
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Does AI-enhanced continuous ECG monitoring detect dynamic changes in right ventricular function and autonomic recovery in patients with intermediate-/high-risk acute pulmonary embolism?
AI-assisted continuous ECG monitoring can detect progressive recovery of cardiac electrophysiological and autonomic function within 72 hours following acute pulmonary embolism, offering a non-invasive tool for real-time assessment.
Abstract Background Right ventricular dysfunction (RVD) is the major risk of short-term mortality and long-term sequelae in acute pulmonary embolism (PE). About 30% of PE patients exhibit persistent RVD one year after the acute event, yet the trajectory of right ventricular recovery remains unclear. The electrocardiogram (ECG), as a routine and widely accessible clinical tool, provides indirect insights into right ventricular alterations but lacks specificity. Integrating artificial intelligence (AI) algorithms with continuous ECG monitoring offers a novel approach to detect subtle, dynamic changes in right ventricular structure and function. This study aims to characterize dynamic changes in right ventricular function in intermediate-/high-risk PE using continuous ECG monitoring with artificial intelligence (AI)-based analysis. Methods In this prospective, multicenter cohort study, patients with confirmed intermediate-/high-risk PE were enrolled across four tertiary hospitals in China. Exclusion criteria included symptom onset more than 14 days before diagnosis, chronic PE without recurrence, contraindications to ECG patch, and having atrial fibrillation. Echocardiography was performed at admission and prior to discharge. Continuous three-lead ECG recordings were obtained using patch-type monitors for 72 hours within the first three days after admission. Raw ECG signals were processed using convolutional neural networks to extract electrophysiological features, and temporal modeling was applied to evaluate dynamic changes. Heart rate variability (HRV) parameters were derived from both frequency-domain (TP, LF, HF, LF/HF) and time-domain (SDNN, SDANN, SDNN index, rMSSD, pNN50, pNN20) analyses. Results 60 patients were included in final analysis. 4 patients received systemic thrombolysis, 6 patients underwent catheter-directed interventions. Over the 72-hour monitoring period, heart rate, P-wave amplitude, QRS amplitude, QT interval, and T-wave amplitude increased, while P-wave width, QRS duration, ST-segment amplitude, and T-wave width decreased. RR interval declined after 48 h; PR interval remained stable. Time-domain HRV indices showed overall improvement, indicating recovery of autonomic and cardiovascular regulatory function. Frequency-domain analysis revealed a shift toward parasympathetic predominance, reflecting attenuation of stress response. Patients receiving reperfusion therapy demonstrated faster normalization of both time- and frequency-domain HRV parameters, suggesting earlier stabilization of autonomic function following rapid relief of pulmonary obstruction. Conclusion Dynamic ECG analyses reveal progressive recovery of cardiac electrophysiological and autonomic function within 72 hours following acute PE, with parasympathetic activation serving as a key indicator of clinical improvement. AI-assisted ECG offers a practical, non-invasive approach for continuous assessment of right ventricular function, offering valuable complementary information to echocardiography and supporting real-time clinical decision-making. This abstract is funded by: The National High Level Hospital Clinical Research Funding (No.2024-NHLHCRF-JBGS-WZ-09)
Xu et al. (2026) conducted a cohort in Acute pulmonary embolism (n=60). Continuous ECG monitoring with AI-based analysis was evaluated on Dynamic changes in right ventricular function. Continuous AI-assisted ECG monitoring over 72 hours in 60 patients with acute pulmonary embolism revealed progressive recovery of cardiac electrophysiological and autonomic function.