PDF(Pubmed)
Abstract：
Background and Objective: In the landscape of heart failure, non-cardiac comorbidities represent a formidable challenge, imparting adverse prognostic implications. Holter ECG monitoring assumes a supplementary role in delineating myocardial susceptibility and autonomic nervous system dynamics. This study aims to explore the potential correlation between Holter ECG parameters and comorbidities in individuals with ischemic cardiomyopathy experiencing heart failure (HF), with a particular focus on the primary utility of these parameters as prognostic indicators. Materials and Methods: In this prospective inquiry, a cohort of 60 individuals diagnosed with heart failure underwent stratification into subgroups based on the presence of comorbidities, including diabetes, chronic kidney disease, obesity, or hyperuricemia. Upon admission, a thorough evaluation of all participants encompassed echocardiography, laboratory panel analysis, and 24 h Holter monitoring. Results: Significant associations were uncovered between diabetes and unconventional physiological indicators, specifically the Triangular index (p = 0.035) and deceleration capacity (p = 0.002). Pertaining to creatinine clearance, notable correlations surfaced with RMSSD (p = 0.026), PNN50 (p = 0.013), and high-frequency power (p = 0.026). An examination of uric acid levels and distinctive Holter ECG patterns unveiled statistical significance, particularly regarding the deceleration capacity (p = 0.045). Nevertheless, in the evaluation of the Body Mass Index, no statistically significant findings emerged concerning Holter ECG parameters. Conclusions: The identified statistical correlations between non-cardiac comorbidities and patterns elucidated in Holter ECG recordings underscore the heightened diagnostic utility of this investigative modality in the comprehensive evaluation of individuals grappling with HF. Furthermore, we underscore the critical importance of the thorough analysis of Holter ECG recordings, particularly with regard to subtle and emerging parameters that may be overlooked or insufficiently acknowledged.
摘要：
背景和目的：在心力衰竭的景观，非心脏合并症是一个巨大的挑战，赋予不良预后影响。动态心电图监测在描绘心肌敏感性和自主神经系统动力学方面具有辅助作用。本研究旨在探讨动态心电图参数与缺血性心肌病心力衰竭（HF）患者合并症之间的潜在相关性。特别关注这些参数作为预后指标的主要用途。材料与方法：在本前瞻性调查中，根据合并症的存在，对60名诊断为心力衰竭的患者进行了分组分层，包括糖尿病,慢性肾病,肥胖，或高尿酸血症。一被录取,对所有参与者的全面评估包括超声心动图，实验室面板分析，和24hHolter监测。结果：发现糖尿病和非常规生理指标之间存在显著关联，特别是三角指数(p=0.035)和减速能力(p=0.002)。关于肌酐清除率，与RMSSD出现了显著的相关性(p=0.026)，PNN50（p=0.013），和高频电源（p=0.026）。对尿酸水平和独特的动态心电图模式的检查揭示了统计学意义，特别是关于减速能力(p=0.045)。然而，在评估身体质量指数时，关于HolterECG参数没有统计学意义的发现.结论：确定的非心脏合并症与HolterECG记录中阐明的模式之间的统计相关性强调了这种研究方式在全面评估患有HF的个体中的诊断实用性。此外，我们强调了彻底分析Holter心电图记录的重要性，特别是关于可能被忽视或认识不足的微妙和新兴参数。
