Aug 2026· Journal of Bangladesh Society of Physiologists· Vol 21, pp. 60-65· 0 citations
TL;DR
Impaired autonomic function characterized by reduced parasympathetic modulation may occur in Parkinson’s disease according to time domain analysis of HRV.
Abstract
Background: Cardiac autonomic dysfunction is an important non-motor feature of Parkinson’s disease and increase morbidity. Heart rate variability (HRV) is a noninvasive technique for assessment of cadiac sympathetic and parasympathetic tonic activity. Objective: To assess cardiac autonomic nerve function (CANF) in Parkinson’s disease by time domain analysis of HRV. Method: This analytical cross-sectional study was conducted in2023. For this, 30 newly diagnosed patients with Parkinson’s disease (age 45-70 years, male and female) and 30 apparently , matched healthy control were enrolled. To assess CANF, HRV was recorded from ECG based data acquisition device, Power lab 8/35, AD instruments, Australia. Time domain parameters were auto generated by Lab chart software. For statistical analysis unpaired “t” test was used by SPSS for windows version 16. Results: Resting pulse rate was significantly higher in the Parkinson’s disease group than in controls ( p˂0.001). In this study, mean heart rate was significantly higher(p<0.01) , standard deviation of the RR intervals (SDRR) (p˂0.001), standard deviation of the difference between successive RR intervals(SDSD), square root of mean squared difference of successive RR intervals (RMSSD), proportion of RR interval with duration ˃50 ms (pRR50% ) were significantly (p<0.001) lower in Parkinsons disease patients compared to healthy subjects. Conclusion: The present study concluded that impaired autonomic function characterized by reduced parasympathetic modulation may occur in Parkinson’s disease.
J Bangladesh Soc Physiol 2026;21(1): 60-65
Compared with young healthy controls, the older and diabetic groups showed lower mean values for SDNN, RMSSD, NN50, pNN50, TINN, total power, SD1, and SD2.
Tarak Das, H. Chatterjee, Buddhadev Pradhan· Asian Journal of Advanced Re...· 0 citations
Background: Phase-Rectified Signal Averaging (PRSA) methods, Deceleration (DC), and Acceleration Capacity (AC), provide a comprehensive assessment of cardiac autonomic function (CAN). There are no published studies comparing PRSA methods with conventional methods such as Time Domain Heart Rate Variability (TD-HRV) or Cardiac Autonomic Reflex Tests (CARTs), nor have they described a cut-off value for AC and DC to distinguish patients with CAN (+ve) from those without CAN (-ve). Our study compares PRSA methods with conventional methods and defines cut-off values for AC and DC to diagnose CAN. Methodology: We studied two cohorts: 126 individuals with normal ventricular function (derivation cohort) and 143 individuals with Left Ventricular Dysfunction (validation cohort). These patients underwent CARTs and supine, resting ECG recordings for 2 to 3 minutes. The patients were categorized as CAN +Ve and CAN -Ve based on TD-HRV parameters and the CARTs. Two different CART criteria were studied: the All-India Institute of Medical Sciences (AIIMS-AFT) criteria and the 2011 Toronto Consensus recommendations. Patients with and without CAN were segregated by AC and DC values, and the methods were compared. The cutoff values for DC and AC were calculated using the ROC curve method from the derivation cohort and verified in the validation cohort. Results: A reduction in DC values and an increase in AC values indicate a higher chance of CAN. The cut-off values of -7 for AC and 7 for DC provide the highest accuracy in detecting CAN prevalence. Both values have an AUC of nearly 0.9. Reclassifying both Cohorts as CAN +Ve based on the derived cut-offs and comparing with the prevalence determined by conventional methods results in kappa values ranging from 0.5 to 0.7. Conclusions: A decrease in DC value and an increase in AC value are associated with a higher probability of CAN. An AC value ≥ -7 and a DC value ≤ 7 indicate good accuracy in identifying CAN.
Stigi Joseph, A. Sudhakar, JK Mukkadan· Nigerian Medical Journal· 0 citations
Findings support the value of routine HRV and Ewing's battery assessment in Morvan syndrome for early detection of cardiovascular autonomic involvement and improved clinical monitoring.
Chandregowda Nandan, Ganagarajan Inbaraj, K. Arjun et al.· Revue neurologique (Paris)· 0 citations
Objective To determine whether cardiovascular autonomic neuropathy (CAN) and reduced heart rate variability (HRV) predict the development of distal symmetrical polyneuropathy (DSPN) in individuals with diabetes mellitus (DM). Methods A total of 288 individuals with DM (mean age 58.1 ± 13.4 years, 41.3% women, 78.5% with type 2 diabetes) underwent baseline assessment of CAN using cardiovascular autonomic reflex tests and HRV indices (CVRR, rMSSD, high- and low-frequency power). DSPN was characterized using three definitions: (i) clinical criteria based on symptoms and signs, (ii) the sensory-loss phenotype derived from quantitative sensory testing, and (iii) the Toronto consensus definition requiring abnormal nerve conduction plus symptoms or signs. A total of 194 participants without DSPN at baseline were followed for 3.0 ± 1.3 years to assess incident DSPN. Results At baseline, CAN prevalence was 16.3%, and low HRV indices were present in 18.6–40.2% of participants. DSPN prevalence was 27.7%, 17.6%, and 20.8% for definitions (i), (ii), and (iii), respectively. Cross-sectionally, CAN and reduced HRV were associated with DSPN (unadjusted ORs 1.8–4.0), with associations largely persisting after adjustment. Incident DSPN occurred at 8.4, 5.7, and 3.3 per 100 person-years. Baseline CAN independently predicted incident DSPN (adjusted HRs 6.20, 3.30, and 7.33 across definitions). Lower rMSSD, HF power, and LF power predicted incident DSPN according to definitions (i) and (iii), whereas reduced CVRR predicted DSPN defined by criteria (ii). Conclusions Established CAN is a strong predictor of future DSPN. Reduced HRV provides a practical, accessible alternative marker for identifying individuals at elevated neuropathy risk.
Dimitrios Tsilingiris, D. Schmalzridt, O. Eldesouky et al.· Frontiers in Endocrinology· 0 citations
Fatigue is a debilitating symptom in multiple sclerosis (MS) associated with autonomic nervous system (ANS) dysfunction. Heart rate variability (HRV) provides a non-invasive measure of ANS function; yet the relative sensitivity of linear and nonlinear HRV parameters in capturing specific ANS (dys)function remains unclear. This study investigated the factorial structure of HRV parameters, their response to biopsychological interventions, and their relationship with MS-related fatigue. Data from two clinical trials (N = 78) were pooled. Exploratory factor analysis (EFA) was applied to time-domain, frequency-domain, and nonlinear HRV parameters. Repeated-measures ANOVAs examined the effects of self-alert training (SAT; activating), deep breathing (DB; relaxing), and progressive muscle relaxation (PMR; intermediate) on HRV, controlling for age, depression, and disability. Subsequent regression analyses investigated whether HRV changes during a vigilance task predicted MS-related fatigue. EFA revealed two factors, likely reflecting parasympathetic (PNS) or sympathetic (SNS) activity. SAT decreased HRV parameters loaded onto both factors, DB increased parameters related to the factor interpreted as mainly reflecting SNS activity, and PMR affected both factors. Reduced SDNN change during the vigilance task predicted higher trait fatigue, whereas state fatigue was not associated with HRV. HRV offers the potential to monitor PNS-SNS-related activity during psychological interventions and to measure reduced autonomic adaptability in MS-related trait fatigue.
G. Garis, Carina Sander-Sandersfeld, Andrea Hildebrandt et al.· Multiple Sclerosis and Relat...· 1 citation
Background Heart rate variability (HRV) is a critical biomarker for assessing autonomic dysfunction, particularly in elderly and type 2 diabetes mellitus (T2DM) populations. However, traditional HRV indices, derived from R-R intervals (RRIs), often fail to detect subtle autonomic dysfunction in complex clinical scenarios. This study proposes a novel Direct TRI Correction (DTRC) sequence to optimize HRV assessment by directly extracting TR intervals (DTRI) and applying a single-step correction. The aim is to enhance accuracy in evaluating HRV, particularly in elderly and T2DM cohorts, where early detection is critical for preventing cardiovascular complications. Methods The study enrolled 124 participants (60 T2DM patients and 64 healthy controls) stratified into three groups based on glycemic control. HRV indices were derived from traditional RRI sequences, two-step corrected TRC sequences, and the novel single-step corrected DTRC sequences, respectively. Statistical analyses were performed on the HRV indices of three sequences to evaluate the comparative performance of DTRC sequences. Results DTRC-based HRV indices demonstrated superior sensitivity and discriminative capability compared to both RRI-based and TRC-based HRV indices. Significant improvements were observed in RMSSD (p = 0.007), pNN50 (p = 0.043), SDSD (p = 0.007), LHR (p = 0.016), SSR (p = 0.010), BEI (p = 0.002), and MSELS (p = 0.009). Visualization analysis and ROC curves confirmed clearer inter-group separation, particularly for T2DM patients with poor glycemic control. Conclusions The DTRC sequence significantly enhances HRV assessment accuracy, offering a reliable tool for early detection of autonomic dysfunction in high-risk populations. Its simplified correction process and improved sensitivity hold promise for clinical diagnostics and wearable health monitoring applications.
Shanglin Yang, Hongbin Zhou, Xuwei Liao et al.· Frontiers in Cardiovascular...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
