Association of cardiac autonomic modulation with physical and clinical features of young people with type 1 diabetes

Does length of time since diagnosis in Parkinson's disease influence heart rate variability? A cross-sectional study

BACKGROUND

Intrinsic changes in Parkinson's disease (PD) affect the autonomic nervous system, and the disease course can aggravate the initial condition. Although the impact of time since disease onset on autonomic modulation has already been studied in other populations, this has not yet been investigated in PD.

OBJECTIVE

To investigate the impact of the length of time since diagnosis on the cardiac autonomic modulation of individuals with PD and compare with healthy individuals.

METHODS

Fifty participants were divided into three groups: a control group (CG; n = 24) and two groups with PD, divided according to the median length of time since diagnosis (median = 5.5 years): below the median (PG1; n = 13) and above the median (PG2; n = 13). To evaluate cardiac autonomic modulation, heart rate was obtained beat-to-beat in the supine position over a 30-min period, and heart rate variability (HRV) indices were calculated using linear methods in the time and frequency domains.

RESULTS

There were no significant differences in HRV indices between the PG groups, or between the three groups regarding Mean RR, LFun, HFun and LF/HF ratio. Significant reductions in the RMSSD, SDNN, pNN50, LFms2 and HFms2 indices were observed in PG1 and PG2, compared with CG.

CONCLUSIONS

The cardiac autonomic modulation of individuals with PD was not influenced by the time since diagnosis. However, reduced parasympathetic and global modulation were observed in these individuals, compared with controls. These results emphasize the importance of aerobic exercise for improving autonomic modulation among individuals with PD.

The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey

Background

Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters.

Objective

The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management.

Methods

A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts.

Results

On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices.

Conclusions

Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.

Autonomic modulation at rest and in response to postural change in adolescents with Duchenne muscular dystrophy: a cross-sectional study

BACKGROUND

Analysis of autonomic modulation after postural change may inform the prognosis and guide treatment in different populations. However, this has been insufficiently explored among adolescents with Duchenne muscular dystrophy (DMD).

OBJECTIVE

To investigate autonomic modulation at rest and in response to an active sitting test (AST) among adolescents with DMD.

METHODS

Fifty-nine adolescents were included in the study and divided into two groups: 1) DMD group: adolescents diagnosed with DMD; 2) control group (CG): healthy adolescents. Participants' weight and height were assessed. Lower limb function, motor limitations and functional abilities of the participants in the DMD group were classified using the Vignos scale, Egen classification and motor function measurement, respectively. The following variables were assessed before, during and after AST: systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory rate (f), oxygen saturation and heart rate (HR). To analyze the autonomic modulation, the HR was recorded beat-by-beat. Heart rate variability (HRV) indices were calculated in the time and frequency domains.

RESULTS

Differences in relation to groups were observed for all HRV indices, except LF/HF, oxygen saturation, HR and f (p < 0.05). Differences in relation to time and the interaction effect between group and time were observed for RMSSD, SD1, SD2, SD1/SD2, LFms2 and LFnu, HFun, SBP and DBP (p < 0.05). Differences in relation to time were also observed for the indice SDNN, FC and f (p < 0.05).

CONCLUSIONS

Performing the AST promoted reduced autonomic modulation and increased SBP, DBP and HR in adolescents with DMD.

Relationship of the Aggregation of Cardiovascular Risk Factors in the Parasympathetic Modulation of Young People with Type 1 Diabetes

Background and objectives: In healthy individuals, autonomic alterations are associated with the aggregation of cardiovascular risk factors. However, in individuals with type 1 diabetes, who are known to present autonomic alterations, mainly characterized by a reduction in parasympathetic modulation, these associations have not yet been investigated. We assess whether the aggregation of cardiovascular risk factors influences parasympathetic indices of heart rate variability in young people with type 1 diabetes. Materials and methods: This cross-sectional study included 39 individuals with type 1 diabetes (22.54 ± 4.31), evaluated in relation to the risk factors: blood pressure, fat percentage, and resting heart rate. For heart rate variability analysis, heart rate was recorded beat-to-beat using a cardio frequency meter (PolarS810i) for 30 min with the volunteers in dorsal decubitus. The parasympathetic heart rate variability indices were calculated: rMSSD, pNN50, high frequency (HF) n.u (normalized units), SD1, 2LV, and 2ULV. Data collection was carried out in 2014 and analyzed in 2017. Results: Individuals with two aggregate risk factors present a reduction in the values of the indices that reflect parasympathetic autonomic modulation compared to individuals without the risk factors analyzed, regardless of sex and age. Conclusion: In young people with type 1 diabetes, the aggregation of cardiovascular risk factors is associated with parasympathetic autonomic impairment.

Can coefficient of variation of time-domain analysis be valuable for detecting cardiovascular autonomic neuropathy in young patients with type 1 diabetes: a case control study

Background

Cardiovascular autonomic neuropathy (CAN) increases morbidity and mortality in diabetes through association with a high risk of cardiac arrhythmias and sudden death, possibly related to silent myocardial ischemia. During the sub-clinical stage, CAN can be detected through reduction in heart rate variability (HRV). The aim of our study was to estimate if the time and frequency-domain analysis can be valuable for detecting CAN in young patients with type 1 diabetes mellitus (T1DM).

Methods

For this case control study of evaluation of cardiovascular autonomic function the 15–25 years age group of patients with duration of T1DM more than 9 years (n = 208, 89 males and 119 females) were selected. 67 patients with confirmed CAN were assigned to the “case group” and 141 patients without CAN served as a control group, the duration of T1DM was similar (15.07 ± 4.89 years vs.13.66 ± 4.02 years; p = 0.06) in both groups. Cardiovascular autonomic reflex tests and time and frequency domains analysis of HRV were performed for all subjects.

Results

Time domain measures were significantly lower in CAN group compared with control (p < 0.05). R-R max / R-R min ratio and coefficient of variation (CV) were the lowest during deep breathing among T1DM patients with CAN. Receivers operating characteristic (ROC) curves were constructed to compare the accuracies of the parameters of time-domain analysis for diagnosing CAN. We estimated a more reliable cut-off value of parameters of time-domain. The CV values in supine position <1.65, reflected sensitivity 94.3%, specificity 91.5%. The CV values during deep breathing <1.45 reflected sensitivity 97.3%, specificity 96.2%. The CV values in standing position <1.50 reflected sensitivity 96.2%, specificity 93.0%. The most valuable CV was during deep breathing (AUC 0.899). The results of frequency-domain (spectral analysis) analysis showed significant decrease in LF power and LFPA, HF Power and HFPA, total power among subjects with CAN than compared with subjects without CAN (p < 0.05).

Conclusions

Time and frequency domain analysis of HRV permits a more accurate evaluation of cardiovascular autonomic function, providing more information about sympathetic and parasympathetic activity. The coefficient of variation (time-domain analysis) especially during deep breathing could be valuable for detecting CAN.