Independent component analysis algorithms for non-invasive fetal electrocardiography

The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms. However, there are many variants of the ICA methods and it is not clear which one is the most suitable for this task. The goal of this study is to test and objectively evaluate 11 variants of ICA methods combined with an adaptive fast transversal filter (FTF) for the purpose of extracting the NI-fECG. The methods were tested on two datasets, Labour dataset and Pregnancy dataset, which contained real records obtained during clinical practice. The efficiency of the methods was evaluated from the perspective of determining the accuracy of detection of QRS complexes through the parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). The best results were achieved with a combination of FastICA and FTF, which yielded mean values of ACC = 83.72%, SE = 92.13%, PPV = 90.16%, and F1 = 91.14%. Time of calculation was also taken into consideration in the methods. Although FastICA was ranked to be the sixth fastest with its mean computation time of 0.452 s, it had the best ratio of performance and speed. The combination of FastICA and adaptive FTF filter turned out to be very promising. In addition, such device would require signals acquired from the abdominal area only; no need to acquire reference signal from the mother's chest

Independent component analysis algorithms for non-invasive fetal electrocardiography

The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms. However, there are many variants of the ICA methods and it is not clear which one is the most suitable for this task. The goal of this study is to test and objectively evaluate 11 variants of ICA methods combined with an adaptive fast transversal filter (FTF) for the purpose of extracting the NI-fECG. The methods were tested on two datasets, Labour dataset and Pregnancy dataset, which contained real records obtained during clinical practice. The efficiency of the methods was evaluated from the perspective of determining the accuracy of detection of QRS complexes through the parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). The best results were achieved with a combination of FastICA and FTF, which yielded mean values of ACC = 83.72%, SE = 92.13%, PPV = 90.16%, and F1 = 91.14%. Time of calculation was also taken into consideration in the methods. Although FastICA was ranked to be the sixth fastest with its mean computation time of 0.452 s, it had the best ratio of performance and speed. The combination of FastICA and adaptive FTF filter turned out to be very promising. In addition, such device would require signals acquired from the abdominal area only; no need to acquire reference signal from the mother’s chest

Activated CD8+CD38+ Cells Are Associated With Worse Clinical Outcome in Hospitalized COVID-19 Patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that spread around the world during the past 2 years, has infected more than 260 million people worldwide and has imposed an important burden on the healthcare system. Several risk factors associated with unfavorable outcome were identified, including elderly age, selected comorbidities, immune suppression as well as laboratory markers. The role of immune system in the pathophysiology of SARS-CoV-2 infection is indisputable: while an appropriate function of the immune system is important for a rapid clearance of the virus, progression to the severe and critical phases of the disease is related to an exaggerated immune response associated with a cytokine storm. We analyzed differences and longitudinal changes in selected immune parameters in 823 adult COVID-19 patients hospitalized in the Martin University Hospital, Martin, Slovakia. Examined parameters included the differential blood cell counts, various parameters of cellular and humoral immunity (serum concentration of immunoglobulins, C4 and C3), lymphocyte subsets (CD3+, CD4+, CD8+, CD19+, NK cells, CD4+CD45RO+), expression of activation (HLA-DR, CD38) and inhibition markers (CD159/NKG2A). Besides already known changes in the differential blood cell counts and basic lymphocyte subsets, we found significantly higher proportion of CD8+CD38+ cells and significantly lower proportion of CD8+NKG2A+ and NK NKG2A+ cells on admission in non-survivors, compared to survivors; recovery in survivors was associated with a significant increase in the expression of HLA-DR and with a significant decrease of the proportion of CD8+CD38+cells. Furthermore, patients with fatal outcome had significantly lower concentrations of C3 and IgM on admission. However, none of the examined parameters had sufficient sensitivity or specificity to be considered a biomarker of fatal outcome. Understanding the dynamic changes in immune profile of COVID-19 patients may help us to better understand the pathophysiology of the disease, potentially improve management of hospitalized patients and enable proper timing and selection of immunomodulator drugs

Immune Profile in Patients With COVID-19 : Lymphocytes Exhaustion Markers in Relationship to Clinical Outcome

The velocity of the COVID-19 pandemic spread and the variable severity of the disease course has forced scientists to search for potential predictors of the disease outcome. We examined various immune parameters including the markers of immune cells exhaustion and activation in 21 patients with COVID-19 disease hospitalised in our hospital during the first wave of the COVID-19 pandemic in Slovakia. The results showed significant progressive lymphopenia and depletion of lymphocyte subsets (CD3+, CD4+, CD8+ and CD19+) in correlation to the disease severity. Clinical recovery was associated with significant increase in CD3+ and CD3+CD4+ T-cells. Most of our patients had eosinopenia on admission, although no significant differences were seen among groups with different disease severity. Non-survivors, when compared to survivors, had significantly increased expression of PD-1 on CD4+ and CD8+ cells, but no significant difference in Tim-3 expression was observed, what suggests possible reversibility of immune paralysis in the most severe group of patients. During recovery, the expression of Tim-3 on both CD3+CD4+ and CD3+CD8+ cells significantly decreased. Moreover, patients with fatal outcome had significantly higher proportion of CD38+CD8+ cells and lower proportion of CD38+HLA-DR+CD8+ cells on admission. Clinical recovery was associated with significant decrease of proportion of CD38+CD8+ cells. The highest AUC values within univariate and multivariate logistic regression were achieved for expression of CD38 on CD8+ cells and expression of PD1 on CD4+ cells alone or combined, what suggests, that these parameters could be used as potential biomarkers of poor outcome. The assessment of immune markers could help in predicting outcome and disease severity in COVID-19 patients. Our observations suggest, that apart from the degree of depletion of total lymphocytes and lymphocytes subsets, increased expression of CD38 on CD3+CD8+ cells alone or combined with increased expression of PD-1 on CD3+CD4+ cells, should be regarded as a risk factor of an unfavourable outcome in COVID-19 patients. Increased expression of PD-1 in the absence of an increased expression of Tim-3 on CD3+CD4+ and CD3+CD8+ cells suggests potential reversibility of ongoing immune paralysis in patients with the most severe course of COVID-19