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Background and Objective. The objective of our study was to evaluate the predictive power of a combined assessment of heart rate variability (HRV) and impedance cardiography (ICG) measures in order to better identify the patients at risk of serious adverse events after ST-segment elevation myocardial infarction (STEMI): all-cause or cardiac mortality (primary outcomes) and in-hospital recurrent ischemia, recurrent nonfatal MI, and need for revascularization (secondary outcomes). Material and Methods. A total of 213 study patients underwent 24-hour electrocardiogram (used for HRV analysis) and thoracic bioimpedance monitoring (used for calculation of hemodynamic measures) immediately after admission. The patients were examined on discharge and contacted after 1 and 5 years. Cox regression analysis was used to determine the predictors of selected outcomes. Results. The standard deviation of all normal-to-normal intervals (SDNN) and cardiac power output (CPO) were found to be the significant determinants of 5-year all-cause mortality (SDNN ≤100.42 ms and CPO ≤1.43 W vs. others: hazard ratio [HR], 11.1; 95% CI, 4.48–27.51; P<0.001). The standard deviation of the averages of NN intervals (SDANN) and CPO were the significant predictors of 5-year cardiac mortality (SDANN ≤85.41 ms and CPO ≤1.43 W vs. others: HR, 11.05; 95% CI, 3.75–32.56; P<0.001). None of the ICG measures was significant in predicting any secondary outcome. Conclusions. The patients with both impaired autonomic heart regulation and systolic function demonstrated by decreased heart rate variability and impedance hemodynamic measures were found to be at greater risk of all-cause and cardiac death within a 5-year period after STEMI. An integrated analysis of electrocardiogram and impedance cardiogram helps estimate patient’s risk of adverse outcomes after STEMI.

Background Sepsis is a life-threatening condition with high morbidity and mortality rate. Identifying early prediction factors of critical situations in intra-abdominal sepsis patients can help reduce mortality rates. This prospective study was carried out to evaluate the association of technically available factors with 30-day in-hospital mortality. Material/Methods There were 67 intra-abdominal sepsis patients included in the study; patients were observed for 30 days postoperatively. The data was processed using SPSS24.0 statistical analysis package. All tests that had a significance level of 0.05 were selected. Results Septic shock in association with increase in age per year showed increase the odds of mortality and prognosed 30-days in hospital mortality correctly in 79% of cases. The observed OR was 12.24 ( P <0.001). Multiple logistic regression model 2 for the 30-day mortality identified a combination of septic shock, age (≥70 years), time from peritonitis symptoms to surgery prognose mortality with accuracy of 82%. The most accurate model to prognose 30-day in-hospital mortality included the presents of septic shock, age, time from peritonitis symptoms to surgery, drop of MAP <65 mmHg) post-induction, the odds of mortality 8.86 ( P =0.001). Severe hypotension post-induction was more frequent in patients who were not diagnosed with sepsis ( P =0.035). Conclusions The present study revealed a simple indicator for the risk for death under diffuse peritonitis patients complicated with sepsis. Septic shock, increase in age per year, peritonitis symptoms lasting more than 30 hours, and severe hypotension post-induction had a negative prognostic value for mortality in patients with intra-abdominal sepsis, and might be a high risk for 30-day mortality.

Reflection of fetal heart electrical activity is present in registered abdominal ECG signals. However this signal component has noticeably less energy than concurrent signals, especially maternal ECG. Therefore traditionally recommended independent component analysis, fails to separate these two ECG signals. Multistage principal component analysis (PCA) is proposed for step-by-step extraction of abdominal ECG signal components. Truncated representation and subsequent subtraction of cardio cycles of maternal ECG are the first steps. The energy of fetal ECG component then becomes comparable or even exceeds energy of other components in the remaining signal. Second stage PCA concentrates energy of the sought signal in one principal component assuring its maximal amplitude regardless to the orientation of the fetus in multilead recordings. Third stage PCA is performed on signal excerpts representing detected fetal heart beats in aim to perform their truncated representation reconstructing their shape for further analysis. The algorithm was tested with PhysioNet Challenge 2013 signals and signals recorded in the Department of Obstetrics and Gynecology, Lithuanian University of Health Sciences. Results of our method in PhysioNet Challenge 2013 on open data set were: average score: 341.503 bpm(2) and 32.81 ms.