Heart rate variability is associated with cerebral small vessel disease in patients with diabetes

Robust QRS detection based on simulated degenerate optical parametric oscillator-assisted neural network

Accurately detecting the depolarization QRS complex in the ventricles is a fundamental requirement for cardiovascular disease detection using electrocardiography (ECG). In contrast to traditional signal enhancement algorithms, emerging neural network approaches have shown promise for QRS detection because of their generalizability on complex data. However, the inevitable noise present during ECG recording leads to a decrease in the performance of neural networks. To enhance the robustness and performance of neural network-based QRS detectors, we propose a simulated degeneration unit (SDU)-assisted convolutional neural network (CNN). An SDU simulates the physical degeneration process of interfering optical pulses, which can effectively suppress in-band noise. Through comprehensive performance evaluations on three open-source databases, the SDU-enhanced CNN-based approach demonstrated better performance in detecting QRS complexes than other recently reported QRS detectors. Furthermore, real-world noise injection tests indicate that the optimal noise robustness boundary for the CNN equipped with SDU is 167-300% higher than that for the CNN without SDU.

Real-time heart rate variability according to ambulatory glucose profile in patients with diabetes mellitus

Background

Autonomic neuropathy commonly occurs as a long-term complication of diabetes mellitus (DM) and can be diagnosed based on heart rate variability (HRV), calculated from electrocardiogram (ECG) recordings. There are limited data on HRV using real-time ECG and ambulatory glucose monitoring in patients with DM. The aim of this study was to investigate real-time HRV according to ambulatory glucose levels in patients with DM.

Methods

A total of 43 patients (66.3 ± 7.5 years) with DM underwent continuous real-time ECG monitoring (225.7 ± 107.3 h) for HRV and ambulatory glucose monitoring using a remote monitoring system. We compared the HRV according to the ambulatory glucose profile. Data were analyzed according to the target in glucose range (TIR).

Results

There were no significant differences in the baseline characteristics of the patients according to the TIR. During monitoring, we checked ECG and ambulatory glucose levels (a total of 15,090 times) simultaneously for all patients. Both time- and frequency-domain HRVs were lower when the patients had poorly controlled glucose levels (TIR < 70%) compared with well controlled glucose levels (TIR > 70%). In addition, heart and respiratory rates increased with real-time glucose levels (P < 0.001).

Conclusions

Poorly controlled glucose levels were independently associated with lower HRV in patients with DM. This was further substantiated by the independent continuous association between real-time measurements of hyperglycemia and lower HRV. These data strongly suggest that cardiac autonomic dysfunction is caused by elevated blood sugar levels.

Heart rate variability analysis in toxic leukoencephalopathy-induced malignant catatonia: A case report

RATIONALE

Toxic leukoencephalopathy, a condition resulting from exposure to toxic substances, can lead to malignant catatonia, a severe motor dysfunction with symptoms such as muscle rigidity and high-spiking fever, hypertensive urgency, and tachycardia. This case study investigates the relationship between toxic leukoencephalopathy-induced malignant catatonia and heart rate variability (HRV), a marker of autonomic nervous system function.

PATIENT CONCERNS

A 51-year-old male presented to the emergency department with acute onset of progressively worsening mental status.

DIAGNOSES

The patient was diagnosed with cocaine-induced toxic leukoencephalopathy causing malignant catatonia.

INTERVENTIONS

A 5-day escalating treatment regimen was instituted for the management of malignant catatonia until resolution. Daily HRV parameters in the temporal and frequency domain, geometric data, and cardiac entropy were recorded using HRVAnalysis v.1.2 (ANS Lab Tools). The HRV analysis was correlated with pharmacologic management, the Bush-Francis catatonia rating scale, and hemodynamic parameters, including blood pressure, heart rate, and temperature.

OUTCOMES

The results showed a correlation between the severity and frequency of malignant catatonic episodes and the patient autonomic dysfunction. Improvement in malignant catatonia with pharmacological management was associated with an improved HRV, including elevated rMSSD, SDNN, cardiac entropy, and pNN50%.

LESSONS

Malignant catatonia is associated with decreased HRV, and its management is associated with an increase. This suggests a link between malignant catatonia and autonomic dysfunction, highlighting the potential benefits of treating malignant catatonia to improve autonomic function and reduce cardiovascular risk.