PubMed · 13493218
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A BRUSCA, P L BRUZZONE, V LEVI, F SOLERIO. 1957-10-31. [Left intracavitary electrogram in man].. https://pubmed.ncbi.nlm.nih.gov/13493218/
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Systemic lupus erythematosus (SLE), a connective tissue disease characterized by the production of auto-antibodies and immune complexes, can affect all organs including the heart. The involvement of the conduction system in SLE has been less commonly described. We report a case of an asymptomatic 45-year-old woman with SLE referred to the emergency department (ED) for thrombocytopenia, and was found to have alternating first- and second-degree atrioventricular block (AVB) during routine electrocardiographic screening for hospital admission. Serial electrocardiograms (ECG) done in the ED when compared to those recorded 24 h prior revealed progression from mild first-degree AVB (PR interval = 216 ms) to significant first-degree AVB (PR interval = 510 ms), followed by second-degree AVB (Mobitz type I-Wenckebach phenomenon). The conduction abnormalities recorded over a 28-h period resolved with corticosteroid treatment. Review of the literature on the disruption of the cardiac conduction system in SLE is discussed.
BACKGROUND: Analysis of heart rate variation (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially non-stationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. METHODS: This paper presents the spatial filling index and time-frequency analysis of heart rate variability signal for disease identification. Renyi's entropy is evaluated for the signal in the Wigner-Ville and Continuous Wavelet Transformation (CWT) domain. RESULTS: This Renyi's entropy gives lower 'p' value for scalogram than Wigner-Ville distribution and also, the contours of scalogram visually show the features of the diseases. And in the time-frequency analysis, the Renyi's entropy gives better result for scalogram than the Wigner-Ville distribution. CONCLUSION: Spatial filling index and Renyi's entropy has distinct regions for various diseases with an accuracy of more than 95%.