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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.
Sec. Coronary Artery Disease
Volume 11 - 2024 | doi: 10.3389/fcvm.2024.1401343
This article is part of the Research Topic Silicon Revolution in Healthcare View all articles

The Application Value of 24-Hour Holter Monitoring Indices in Predicting MACEs Outside the Hospital Within Three Years After PCI in Patients with STEMI

Provisionally accepted
Bingxin Chen Bingxin Chen 1Li Men Li Men 1Hongli Wang Hongli Wang 1Long Yang Long Yang 1Mingxi Li Mingxi Li 2Jingcheng Hu Jingcheng Hu 2Ping Fan Ping Fan 1*
  • 1 First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uyghur Region, China
  • 2 Xinjiang Medical University, Ürümqi, Xinjiang Uyghur Region, China

The final, formatted version of the article will be published soon.

    Evaluating cardiovascular risk in patients experiencing acute ST-elevation myocardial infarction (STEMI) and undergoing percutaneous coronary intervention (PCI) is crucial for early intervention and improving long-term outcomes. 24-hour Holter monitoring provides continuous cardiac electrophysiological data, enabling the detection of arrhythmias and autonomic dysfunction that are not captured during routine examinations. This study aimed to examine the relationship between Holter monitoring metrics and the occurrence of out-ofhospital major adverse cardiovascular events (MACEs) following PCI in patients with STEMI, offering insights into cardiovascular risk evaluation.This prospective cohort study included STEMI patients undergoing PCI. 24-hour Holter monitoring data were recorded, including heart rate, heart rate variability (HRV) metrics such as SDNN and SDANN index, heart rate deceleration capacity (DC) at different time scales (DC2, DC4, DC8), and the frequency of premature ventricular contractions (PVCs). Independent correlations between these indices and MACEs, as well as cardiovascular deaths, were investigated using multifactorial logistic regression. Predictive capacities were assessed through receiver operating characteristic (ROC) curves.A total of 172 participants were enrolled in this study. Over the 3-year follow-up period, MACEs were observed in 57 patients, including 20 cases of cardiac death. In logistic regression models adjusted for confounding variables, SDNN (OR: 0.980; 95% CI: [0.967, 0.994]; p=0.005) and SDANN index (OR: 0.982; 95% CI: [0.969, 0.996]; p=0.009) were negatively associated with the incidence of MACEs. Conversely, the slowest heart rate (OR: 1.075; 95% CI: [1.022, 1.131]; p=0.005) and frequent PVCs (OR: 2.685; 95% CI: [1.204, 5.987]; p=0.016) demonstrated a positive association with MACEs. Furthermore, SDNN (OR: 0.957; 95% CI: [0.933, 0.981]; p=0.001), DC (OR: 0. 702; 95% CI: [0.526, 0.938]; p=0.017)) and DC4 (OR: 0.020; 95% CI: [0.001, 0.664]; p=0.029) were negatively associated with cardiac death. The ROC analysis results indicated that SDNN was an effective predictor of both MACEs (AUC: 0.688 [95% CI: 0.601 -0.776]) and cardiac death (AUC: 0.752 [95% CI: 0.625 -0.879]).HRV, DC metrics, and frequent PVCs obtained by 24-hour Holter monitoring were associated with the risk of MACEs in STEMI patients. These metrics can help clinicians identify at-risk patients early so that timely interventions.

    Keywords: STEMI, MACEs, Holter, Heart rate variability, Deceleration capacity

    Received: 15 Mar 2024; Accepted: 11 Jul 2024.

    Copyright: © 2024 Chen, Men, Wang, Yang, Li, Hu and Fan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ping Fan, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uyghur Region, China

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