2023•Journal of Basic and Clinical Physiology and PharmacologyOpen access

Correlation among Poincare plot and traditional heart rate variability indices in adults with different risk levels of metabolic syndrome: a cross-sectional approach from Southern India

Chiranjeevi Kumar Endukuru, Girwar Singh Gaur, Dhanalakshmi Yerrabelli, Jayaprakash Sahoo, Balasubramaniyan Vairappan, Alladi Charanraj Goud

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Abstract

OBJECTIVES: Heart rate variability (HRV) is an important marker of cardiac autonomic modulation. Metabolic syndrome (MetS) can alter cardiac autonomic modulation, raising the risk of cardiovascular disease (CVD). Poincaré plot analysis (PPA) is a robust scatter plot-based depiction of HRV and carries similar information to the traditional HRV measures. However, no prior studies have examined the relationship between PPA and traditional HRV measures among different risk levels of MetS. We evaluated the association between the Poincare plot and traditional heart rate variability indices among adults with different risk levels of MetS. METHODS: We measured anthropometric data and collected fasting blood samples to diagnose MetS. The MetS risk was assessed in 223 participants based on the number of MetS components and was classified as control (n=64), pre-MetS (n=49), MetS (n=56), and severe MetS (n=54). We calculated the Poincaré plot (PP) and traditional HRV measures from a 5 min HRV recording. RESULTS: Besides the traditional HRV measures, we found that various HRV indices of PPA showed significant differences among the groups. The severe MetS group had significantly lower S (total HRV), SD1 (short-term HRV), SD2 (long-term HRV), and higher SD2/SD1. The values of S, SD1, SD2, and SD2/SD1 were significantly correlated with most traditional HRV measures. CONCLUSIONS: We found gradual changes in HRV patterns as lower parasympathetic and higher sympathetic activity alongside the rising number of MetS components. The HRV indices of PPA integrating the benefits of traditional HRV indices distinguish successfully between different risk levels of MetS and control subjects.

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OBJECTIVES: Heart rate variability (HRV) is an important marker of cardiac autonomic modulation. Metabolic syndrome (MetS) can alter cardiac autonomic modulation, raising the risk of cardiovascular disease (CVD). Poincaré plot analysis (PPA) is a robust scatter plot-based depiction of HRV and carries similar information to the traditional HRV measures. However, no prior studies have examined the relationship between PPA and traditional HRV measures among different risk levels of MetS. We evaluated the association between the Poincare plot and traditional heart rate variability indices among adults with different risk levels of MetS. METHODS: We measured anthropometric data and collected fasting blood samples to diagnose MetS. The MetS risk was assessed in 223 participants based on the number of MetS components and was classified as control (n=64), pre-MetS (n=49), MetS (n=56), and severe MetS (n=54). We calculated the Poincaré plot (PP) and traditional HRV measures from a 5 min HRV recording. RESULTS: Besides the traditional HRV measures, we found that various HRV indices of PPA showed significant differences among the groups. The severe MetS group had significantly lower S (total HRV), SD1 (short-term HRV), SD2 (long-term HRV), and higher SD2/SD1. The values of S, SD1, SD2, and SD2/SD1 were significantly correlated with most traditional HRV measures. CONCLUSIONS: We found gradual changes in HRV patterns as lower parasympathetic and higher sympathetic activity alongside the rising number of MetS components. The HRV indices of PPA integrating the benefits of traditional HRV indices distinguish successfully between different risk levels of MetS and control subjects.

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Available abstract

OBJECTIVES: Heart rate variability (HRV) is an important marker of cardiac autonomic modulation. Metabolic syndrome (MetS) can alter cardiac autonomic modulation, raising the risk of cardiovascular disease (CVD). Poincaré plot analysis (PPA) is a robust scatter plot-based depiction of HRV and carries similar information to the traditional HRV measures. However, no prior studies have examined the relationship between PPA and traditional HRV measures among different risk levels of MetS. We evaluated the association between the Poincare plot and traditional heart rate variability indices among adults with different risk levels of MetS. METHODS: We measured anthropometric data and collected fasting blood samples to diagnose MetS. The MetS risk was assessed in 223 participants based on the number of MetS components and was classified as control (n=64), pre-MetS (n=49), MetS (n=56), and severe MetS (n=54). We calculated the Poincaré plot (PP) and traditional HRV measures from a 5 min HRV recording. RESULTS: Besides the traditional HRV measures, we found that various HRV indices of PPA showed significant differences among the groups. The severe MetS group had significantly lower S (total HRV), SD1 (short-term HRV), SD2 (long-term HRV), and higher SD2/SD1. The values of S, SD1, SD2, and SD2/SD1 were significantly correlated with most traditional HRV measures. CONCLUSIONS: We found gradual changes in HRV patterns as lower parasympathetic and higher sympathetic activity alongside the rising number of MetS components. The HRV indices of PPA integrating the benefits of traditional HRV indices distinguish successfully between different risk levels of MetS and control subjects.

Key concepts: Heart rate variability, Poincaré plot, Medicine, Metabolic syndrome, Correlation, Internal medicine, Cardiology, Anthropometry

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