Association of Heart Rate Variability and Acceleration Plethysmography with Systemic Comorbidity Burden in Patients with Glaucoma

<b>Background</b>: Autonomic nervous system (ANS) and vascular factors are associated with glaucoma. However, the association between systemic comorbidity burden and ANS and hemodynamic function in patients with glaucoma remains unclear. This study aimed to examine the association between heart rate variability (HRV) and acceleration plethysmography (APG) parameters and the age-adjusted Charlson Comorbidity Index (ACCI) in patients with glaucoma. <b>Methods</b>: A total of 260 subjects (260 eyes), including 186 with primary open-angle glaucoma (PG) and 74 with exfoliation glaucoma (EG), were enrolled at Shimane University Hospital from June 2023 to July 2024. HRV and APG were assessed using a sphygmograph (TAS9 Pulse Analyzer Plus View). HRV parameters included time-domain measures (SDNN, RMSSD, CVRR) and frequency-domain measures (TP, VLF, LF, HF, LF/HF). APG parameters included the a, b, c, d, and e components of the accelerated pulse wave, and the following vascular types: Type A, Type B, and Type C. The association between ACCI and HRV and APG parameters was evaluated using Spearman's rank correlation and multivariate regression adjusted for sex, body mass index, pulse rate, systolic and diastolic blood pressure, intraocular pressure, medication score, mean deviation, and glaucoma type. <b>Results</b>: By univariate analysis, against ACCI, significant inverse correlations were observed for several parameters: LnLF (R = -0.17, <i>p</i> = 0.0062); LnLF/LnHF (R = -0.24, <i>p</i> = 0.00012); b peak (R = -0.14, <i>p</i> = 0.031); d peak (R = -0.17, <i>p</i> = 0.0072); and e peak (R = -0.15, <i>p</i> = 0.015). Regarding HRV parameters, multivariate linear regression models showed that ACCI was significantly positively associated with RMSSD (coefficient: 2.861; 95% CI: 0.447 to 5.274) and significantly negatively associated with the frequency-domain parameters LnLF (coefficient: -0.127; 95% CI: -0.245 to -0.009) and LnLF/LnHF (coefficient: -0.038; 95% CI: -0.062 to -0.014). In APG parameters, the c peak was significant associated with ACCI (coefficient: -12.6; 95% CI: -22.5 to -2.69). ACCI was significantly associated with Type B (coefficient: 0.305; 95% CI: 0.057 to 0.552). <b>Conclusions</b>: Greater systemic comorbidity burden may be related to impaired ANS regulation and increased vascular stiffness in glaucoma patients.

Authors

Institutions

Publication Details

Journal
Biomedicines
Published
2025-09-04
DOI
https://doi.org/10.3390/biomedicines13092155
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association of Heart Rate Variability and Acceleration Plethysmography with Systemic Comorbidity Burden in Patients with Glaucoma

Hinako Takei, Masaki Tanito, Yuto Yoshida, Keigo Takagi et al.
Biomedicines
Heart Rate Variability and Autonomic Control
article

Association of Heart Rate Variability and Acceleration Plethysmography with Systemic Comorbidity Burden in Patients with Glaucoma

Hinako Takei, Masaki Tanito, Yuto Yoshida, Keigo Takagi, Misaki Ukisu
article en

Abstract

<b>Background</b>: Autonomic nervous system (ANS) and vascular factors are associated with glaucoma. However, the association between systemic comorbidity burden and ANS and hemodynamic function in patients with glaucoma remains unclear. This study aimed to examine the association between heart rate variability (HRV) and acceleration plethysmography (APG) parameters and the age-adjusted Charlson Comorbidity Index (ACCI) in patients with glaucoma. <b>Methods</b>: A total of 260 subjects (260 eyes), including 186 with primary open-angle glaucoma (PG) and 74 with exfoliation glaucoma (EG), were enrolled at Shimane University Hospital from June 2023 to July 2024. HRV and APG were assessed using a sphygmograph (TAS9 Pulse Analyzer Plus View). HRV parameters included time-domain measures (SDNN, RMSSD, CVRR) and frequency-domain measures (TP, VLF, LF, HF, LF/HF). APG parameters included the a, b, c, d, and e components of the accelerated pulse wave, and the following vascular types: Type A, Type B, and Type C. The association between ACCI and HRV and APG parameters was evaluated using Spearman's rank correlation and multivariate regression adjusted for sex, body mass index, pulse rate, systolic and diastolic blood pressure, intraocular pressure, medication score, mean deviation, and glaucoma type. <b>Results</b>: By univariate analysis, against ACCI, significant inverse correlations were observed for several parameters: LnLF (R = -0.17, <i>p</i> = 0.0062); LnLF/LnHF (R = -0.24, <i>p</i> = 0.00012); b peak (R = -0.14, <i>p</i> = 0.031); d peak (R = -0.17, <i>p</i> = 0.0072); and e peak (R = -0.15, <i>p</i> = 0.015). Regarding HRV parameters, multivariate linear regression models showed that ACCI was significantly positively associated with RMSSD (coefficient: 2.861; 95% CI: 0.447 to 5.274) and significantly negatively associated with the frequency-domain parameters LnLF (coefficient: -0.127; 95% CI: -0.245 to -0.009) and LnLF/LnHF (coefficient: -0.038; 95% CI: -0.062 to -0.014). In APG parameters, the c peak was significant associated with ACCI (coefficient: -12.6; 95% CI: -22.5 to -2.69). ACCI was significantly associated with Type B (coefficient: 0.305; 95% CI: 0.057 to 0.552). <b>Conclusions</b>: Greater systemic comorbidity burden may be related to impaired ANS regulation and increased vascular stiffness in glaucoma patients.

BiomedicinesVol. 13(9)
Shimane University (JP)
Openalex Percentile: Top 63%
Heart Rate Variability and Autonomic Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.