Branislav Milovanovic’s research while affiliated with University Children's Hospital, Belgrade, Serbia and other places


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Publications (56)


A Lower Level of Post-Vaccinal Antibody Titer against Influenza Virus A H1N1 May Protect Patients with Autoimmune Rheumatic Diseases from Respiratory Viral Infections
  • Article
  • Full-text available

January 2022

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33 Reads

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2 Citations

Medicina

Milomir S. Milanovic

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Background and Objectives: The concentration of antibodies against virus influenza A H1N1 in the titer (≥1:32) positively correlates with resistance to flu in healthy persons. In elderly and immune-compromised patients, an influenza vaccine may be less immunogenic. Hypothesis: A lower post-vaccinal antibody titer (≥1:16) may be sero-protective against respiratory viral infections in patients with autoimmune rheumatic diseases. Materials and Methods: Fifty patients with autoimmune rheumatic diseases (Systemic Lupus Erythematosus—24; Rheumatoid Arthritis—15; and Sjögren’s Syndrome—11), who were at least 65 years old or whose relative disease duration (disease duration/age) was greater than 1/8, were examined. Thirty-four of them were vaccinated with a trivalent inactivated non-adjuvant influenza vaccine. The antibody concentration against influenza virus A H1N1 was measured using the standardized hemagglutination inhibition test and patients who got any respiratory viral infection were registered. To test the hypothesis, a correlative analysis was applied, followed by a binary logistic regression that included potential confounding variables, such as age, disease duration and therapy (personal/health-related conditions). Results: Vaccinated patients were significantly less affected by respiratory viral infections (21% vs. 75%). The lower titer considered (≥1:16) was significantly present more often among vaccinated patients (68% vs. 6%). The correlation between its presence/absence and that of respiratory viral infections was –0.34 (p < 0.05). The binary logistic regression evidenced the relevance of this correlation, confirming the hypothesis. Vaccination was associated with the 87.3% reduction in the likelihood of getting respiratory viral infections, whereas the lower antibody titer (≥1:16) was associated with the 77.6% reduction in the likelihood of getting respiratory viral infections. The vaccine was well tolerated by all patients and after vaccination no exacerbation of the underlying disease was observed. Conclusions: A lower antibody titer (≥1:16) against influenza virus A H1N1 could be protective against respiratory viral infections for certain autoimmune rheumatic diseases patients, which confirms the clinical effectiveness of influenza vaccination.

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Orthostatic hypotension in COVID-19. Results for COVID-19 patients are given in respect to both severe and mild group.
Heart rate and characteristic blood pressure variability in rest and during orthostatic hypotension and head up tilt test by patient with COVID-19 infection and low baroreflex sensitivity (real time beat to beat blood pressure analysis).
Poincare plots and corresponding heart rate signals: (A) Healthy volunteer; (B) COVID-19 patient; (C) COVID-19 patient. Note that the scale is the same in all graphs. The plots are included to illustrate the adverse effects of COVID-19 infection, but the signals were not part of the presented statistics. Patient (b) is male, 71 years old, height 168, weight 66. The patient reported no hereditary diseases, gait instability, and last 2 months the patient was experiencing hard breathing. During hospitalization it was discovered that the patient has heart valve disease, before that the patient was healthy. Patient (c) is female, 87 years old, height 163, weight 81. She reported problems with spine, occasional headaches, dizziness when changing her head position, no hereditary diseases and no other health problems.
Population characteristics of COVID-19 patients and controls.
Beat-to-beat analysis of heart rate variability (Task force monitor) in COVID-19.

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Assessment of Autonomic Nervous System Dysfunction in the Early Phase of Infection With SARS-CoV-2 Virus

June 2021

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245 Reads

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37 Citations

Frontiers in Neuroscience

Background We 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. Aim Assessment of AD in the early phase of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus). Patients and methods We 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. Results AD (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. Conclusion Cardiovascular 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.


List of acronyms.Table 1. List of acronyms.
Entropy Analysis of COVID-19 Cardiovascular Signals

January 2021

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145 Reads

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27 Citations

Entropy

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.


A new theoretical model for hexagonal ice, Ih(d), from first principles investigations

November 2019

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80 Reads

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6 Citations

Zeitschrift fur Naturforschung B

Due to their great importance in science, technology, and the life sciences, water and ice have been extensively investigated over many years. In particular, hexagonal ice Ih has been of great interest since it is the most common form of ice, and several modifications, Ih(a), Ih(b) and Ih(c) are known, whose structural details are still under discussion. In this study, we present an alternative theoretical model, called Ih(d), for the hexagonal ice modification in space group P 6 3 / mmc (no. 194), based on first-principles calculations that have been performed using DFT-LDA, GGA-PBE, and hybrid B3LYP and PBE0 functionals.


Figure 1. Artefact correction. a) RR interval time series; b) SBP time series. Blue line -before the correction, red line -after the correction.
Sequences and antisequences in hypertensive patients under therapy

June 2019

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95 Reads

IJEEC - INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTING

Baroreceptor reflex (baroreflex, BRR) is a domineering physiological regulator considering the systolic blood pressure (SBP) and heart rate (HR). It maintains the negative feedback equilibrium: if the blood pressure increase, heart rate decreases and vice versa. The aim of this study is to compare the number of baroreflex sequences in hypertensive patients before and after the drug administration, and to oppose the assumptions about their origin. Other methods that evaluate the mutual connection between the SBP and HR time series are investigated as well, such as cross-entropy, copula parameter, and probability integral transformed entropy. Surrogate data were used as a control.


SEQUENCES AND ANTISEQUENCES IN HYPERTENSIVE PATIENTS AFTER DRUG ADMINISTRATION

Baroreflex is considered to be the dominant physiologic parameter between systolic blood pressure (SBP) and heart rate. This mechanism maintains physiological equilibrium using negative feedback: if blood pressure tends to rise, heart rate lowers and opposite. The aim of this study was to compare RR intervals and SBP, parallel and antiparallel streams of the different type, before and after taking medicine named verapamil. A method used for estimation of spontaneous baroreflex sensitivity is sequence method. This method is based on the interaction between RR intervals and SBP signal and their ramps.


COMPARATIVE ANALYSIS OF METHODS FOR ESTIMATING THE SPECTRAL DENSITY OF CARDIOVASCULAR TIME SERIES IN THE ASSESSMENT OF THE SYMPATHOVAGAL BALANSE

Power spectral density estimation (psd) of the heart rate signal (HR) indicates the activity of the autonomic nervous system. The lack of standard contributed to the selection of various methods for psd estimation such as classical nonparametric (periodogram, Welch), parametric (Burg method) and the proposed new methods designed especially for psd of HR signals. The paper presents a comparative analysis of the various methods for psd estimation in hypertensive patients before and after the use of Karvileks® medication. It has been shown that the artifacts in the HR time series influence psd estimation, indicating that it is necessary to pre-process HR time series prior the application of the methods. The effects of Karvileks® medication did not cause changes in the sympathovagal balance.


Copula parameters in Poincaré plain for patients under CONCOR treatment

Cardiovascular signals are characterized by spontaneous fluctuations described more than a thousand years ago. Their physiological meaning is largely explained and it represents one of the most important groups of signals used to describe the state of the human organism. This paper analyzes the RR interval and blood pressure signals in patients using the drug therapy. The Poenkare plot and copula density methods were used for the analysis. Considering the nature of the signal, which is characterized by a large number of artifacts, the pre-signal processing was first done with the adaptive filtering procedure.


Procesi, podaci, ljudi i stvari: četiri IoE osnove prikupljanja medicinskih podataka

In this paper we analyze fundamental foundations of Internet of Everything (IoE) and their realizations considering the medical applications. A special attention is devoted to the database creation, where the inputs are signals that volunteers collect during their everyday activities, and then discard due to the memory limitations. The collected data served to discuss the basic requirements of the crowd sensing: parameter transmission vs. complete signal transmission. A comparison between robust and classical parameters is performed.


MACHINE LEARNING TEHNIQUES IMPLEMENTATION FOR CLASSIFICATION OF PATIENTS AFTER MYOCARDIAL INFARCTION

In this paper we analyzed cardiovascular parameters recorded from patients with diagnosis of myocardial infarction and healthy individuals in a control group. The aim was to develop model for solving a problem of binary classification, myocardial infarction risk prediction and parameter’s influence on decision of class affiliation. The paper presents an overview of used models based on 4 different machine learning techniques: Decision tree, Random forest, Support vector machine and Artificial neural network. The comparative analysis of the obtained results resulted in the highest total precision of the prediction of 95.58% for the model based on the Random forest technique of machine learning.


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Citations (31)


... Patients with systemic autoimmune diseases are at increased risk of influenza and severe respiratory complications, particularly if they are on therapy with immunosuppressive drugs belonging to the biological and synthetic last-generation drug classes [1][2][3]. Respiratory tract infections are the most common in this patient setting; among them, seasonal influenza remains one of the most frequent causes of hospitalization and mortality, similar to that observed in the general population [1,[4][5][6]. ...

Reference:

Active vaccination campaign to increase seasonal influenza vaccination coverage: a monocenter experience in a cohort of Italian patients with systemic autoimmune diseases
A Lower Level of Post-Vaccinal Antibody Titer against Influenza Virus A H1N1 May Protect Patients with Autoimmune Rheumatic Diseases from Respiratory Viral Infections

Medicina

... The substantial reduction in vagal heart modulation, as indicated by a decrease in nHF, observed in association with SARS-CoV-2 infection, resonates across various case-control studies that involved Frontiers in Neurology 08 frontiersin.org diverse populations at different infection stages (20,21,(25)(26)(27). ...

Assessment of Autonomic Nervous System Dysfunction in the Early Phase of Infection With SARS-CoV-2 Virus

... The post-pandemic effect of COVID-19, involving cardiac complications in patients who have recovered from the coronavirus, is also a factor [3,4]. Coronary heart disease, heart failure, arrhythmia, heart valve issues, and high blood pressure are among the various types of CVD [5]. Therefore, the medical and scientific community has become more engaged with the study, acquisition, and management of electrocardiogram (ECG) data [6]. ...

Entropy Analysis of COVID-19 Cardiovascular Signals

Entropy

... K-point meshes of 8 × 8 × 8 Monkhorst-Pack scheme have been used. Chosen LCAO/Gaussian basis set type approach and DFT methods have been shown highly efficient and precise in our previous theoretical studies [44][45][46] and in comparison to the experimental data [30,47,48]. A computational strategy implemented in the CRYSTAL17 solid-state, quantum-chemical program has been performed for the accurate ab initio simulation of elastic and mechanical properties of crystalline materials [49]. ...

A new theoretical model for hexagonal ice, Ih(d), from first principles investigations
  • Citing Article
  • November 2019

Zeitschrift fur Naturforschung B

... Since first was proposed, HRV has been rapidly adopted as a non-invasive method to study the cardiac autonomic modulation [3]. Evidences of an association between HRV and CVD, such as myocardial infarction [4,5], stroke [6], angina [7,8], coronary heart disease [9], coronary artery disease [10][11][12] and sudden cardiac death [13], have been reported. Furthermore, studies have put forward that HRV has predictive value for CVD outcomes [14][15][16]. ...

Nonlinear parameters of heart rate variability and detection of high risk patients after myocardial infarction based on artificial intelligence analysis

Journal of Electrocardiology

... It can take advantage of collecting data and support a variety of innovative applications in the Internet of Things (IOTs) [1]. MCS has been widely used in many fields, such as environmental monitoring [2], health care [3], industrial control [4], geological prospecting [5], and transportation planning [6]. Extended author information available on the last page of the article A typical MCS system consists of a task requester, worker, and platform. ...

A Mobile Crowd Sensing Application for Hypertensive Patients

Sensors

... Slika 5 je ilustracija promena pritiska, pulsnog intervala i telesne temperature za istog pacova kao na slikama 3 i 4, a takođe prikazuje i dinamičku zavisnost sa kašnjenjem između pulsnog intervala u odnosu na sistolni pritisak. Ovo dinamičko posmatranje uz farmakološku validaciju detaljno je elaborirano u [10] a neki aspekti su takođe prikazani u [11]. ...

Artifacts in dependency structures of Portapres® signals

IJEEC - INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTING

... It is unclear whether aPL titers and/or certain aPL profiles are associated with the extent and progression of PV-aPL. In a previous study by Djokovic et al. [123], the presence of aB2GPI IgG might be associated with more serious cerebrovascular events. A reduction in aPLs through plasmapheresis or the depletion of B cells or plasma cells might improve long-term prognosis. ...

Relationship between cerebrovascular and valvular manifestations in a Serbian cohort of patients with antiphospholipid syndrome

Clinical and Experimental Rheumatology

... e network is supported by three parts: contracting, bridge, and expanding paths to complete the stain separation of H (hematoxylin), E (eosin), and B (background) channels. e contracting path is used to reduce the spatial dimension of the feature map, while increasing the number of the feature maps layer by layer [37][38][39][40], extracting the input image as a compact feature. e bridge connects the contracting and expanding paths. is U-shaped encoder-decoder model is improved to be a multiple tasks model; besides the output of the U-net, we also use the most compact features to predict the stain color matrixes, which is combined with mean and variance of stain color values of hematoxylin, eosin, and background paths. ...

Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks