BackgroundWe are facing the outburst of coronavirus disease 2019 (COVID-19) defined as a serious, multisystem, disorder, including various neurological manifestations in its presentation. So far, autonomic dysfunction (AD) has not been reported in patients with COVID-19 infection.AimAssessment of AD in the early phase of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus).Patients and methodsWe analyzed 116 PCR positive COVID-19 patients. After the exclusion of 41 patients with associate diseases (CADG), partitioned to patients with diabetes mellitus, hypertension, and syncope, the remaining patients were included into a severe group (45 patients with confirmed interstitial pneumonia) and mild group (30 patients). Basic cardiovascular autonomic reflex tests (CART) were performed, followed by beat-to-beat heart rate variability (HRV) and systolic and diastolic blood pressure variability (BPV) analysis, along with baroreceptor sensitivity (BRS). Non-linear analysis of HRV was provided by Poincare Plot. Results were compared to 77 sex and age-matched controls.ResultsAD (sympathetic, parasympathetic, or both) in our study has been revealed in 51.5% of severe, 78.0% of mild COVID-19 patients, and the difference compared to healthy controls was significant (p = 0.018). Orthostatic hypotension has been established in 33.0% COVID-19 patients compared to 2.6% controls (p = 0.001). Most of the spectral parameters of HRV and BPV confirmed AD, most prominent in the severe COVID-19 group. BRS was significantly lower in all patients (severe, mild, CADG), indicating significant sudden cardiac death risk.ConclusionCardiovascular autonomic neuropathy should be taken into account in COVID-19 patients’ assessment. It can be an explanation for a variety of registered manifestations, enabling a comprehensive diagnostic approach and further treatment.

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Future smart healthcare systems—often referred to as Internet of Medical Things (IoMT) – will combine a plethora of wireless devices and applications that use wireless communication technologies to enable the exchange of healthcare data. Smart healthcare requires sufficient bandwidth, reliable and secure communication links, energy-efficient operations, and Quality of Service (QoS) support. The integration of Internet of Things (IoT) solutions into healthcare systems can significantly increase intelligence, flexibility, and interoperability. This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications. A particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems. Major challenges in privacy and security are also discussed. A particular attention is devoted to crowdsourcing/crowdsensing, envisaged as tools for the rapid collection of massive quantities of medical data. Finally, open research challenges and future perspectives of IoMT are presented.

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The clinical use of doxorubicin, an effective chemotherapeutic is hampered by the development of irreversible cardiotoxicity. Here we test time-frequency analysis of heart rate (HR) variability (HRV) for early detection of doxorubicin-induced cardiotoxicity. Experiments were conducted in adult male Wistar rats treated for 15 days with doxorubicin (DOXO, total dose 15 mg kg(-1), i.p.) or saline (CONT). DOXO rats exhibited cardiotoxicity confirmed by histological examination without developing heart failure as estimated by echocardiography. However, HR variability increase reflected subtle microscopic changes of cardiac toxicity in DOXO rats. The results recommend time-frequency analysis of HRV for early detection of doxorubicin-induced cardiomyopathy.

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This study investigates blood pressure (BP) and heart rate (HR) short-term variability and spontaneous baroreflex functioning in adult borderline hypertensive rats and normotensive control animals kept on normal-salt diet. Arterial pulse pressure was recorded by radio telemetry. Systolic BP, diastolic BP and HR variabilities and baroreflex were assessed by spectral analysis and the sequence method, respectively. In all experimental conditions (baseline and stress), borderline hypertensive rats exhibited higher BP, increased baroreflex sensitivity and resetting, relative to control animals. Acute shaker stress (single exposure to 200 cycles min-1 shaking platform) increased BP in both strains, while chronic shaker stress (3-day exposure to shaking platform) increased systolic BP in borderline hypertensive rats alone. Low- and high-frequency HR variability increased only in control animals in response to acute and chronic shaker (single exposure to restrainer) stress. Acute restraint stress increased BP, HR, low- and high-frequency variability of BP and HR in both strains to a greater extent than acute shaker stress. Only normotensive rats exhibited a reduced ratio of low- to high-frequency HR variability, pointing to domination of vagal cardiac control. In borderline hypertensive rats, but not in control animals, chronic restraint stress (9-day exposure to restrainer) increased low- and high-frequency BP and HR variability and their ratio, indicating a shift towards sympathetic cardiovascular control. It is concluded that maintenance of BP in borderline hypertensive rats in basal conditions and during stress is associated with enhanced baroreflex sensitivity and resetting. Imbalance in sympathovagal control was evident only during exposure of borderline hypertensive rats to stressors.

The world has faced a coronavirus outbreak, which, in addition to lung complications, has caused other serious problems, including cardiovascular. There is still no explanation for the mechanisms of coronavirus that trigger dysfunction of the cardiac autonomic nervous system (ANS). We believe that the complex mechanisms that change the status of ANS could only be solved by advanced multidimensional analysis of many variables, obtained both from the original cardiovascular signals and from laboratory analysis and detailed patient history. The aim of this paper is to analyze different measures of entropy as potential dimensions of the multidimensional space of cardiovascular data. The measures were applied to heart rate and systolic blood pressure signals collected from 116 patients with COVID-19 and 77 healthy controls. Methods that indicate a statistically significant difference between patients with different levels of infection and healthy controls will be used for further multivariate research. As a result, it was shown that a statistically significant difference between healthy controls and patients with COVID-19 was shown by sample entropy applied to integrated transformed probability signals, common symbolic dynamics entropy, and copula parameters. Statistical significance between serious and mild patients with COVID-19 can only be achieved by cross-entropies of heart rate signals and systolic pressure. This result contributes to the hypothesis that the severity of COVID-19 disease is associated with ANS disorder and encourages further research.