Evaluation of thoracic surface motion during the free breathing and deep inspiration breath hold methods.

The aim of this study was to evaluate thoracic surface motion from chest wall expansion during free breathing (FB) and deep inspiration breath hold (DIBH) methods, measured with and without 4-dimensional computed tomography (4D-CT) simulation, using equipment developed in-house. The respiratory amplitude and chest wall expansion were evaluated at 5 levels of the thorax, (the sterno-clavicular joint (SCJ), the second level, the intermammary line (IML), the fourth level and the caudal end of the xiphoid process (XP)) using radiopaque wires and potentiometers, with a CT scan simultaneously. This study included 25 examinees (10 volunteers performed FB, 10 volunteers performed DIBH and 5 patients performed FB). For low and irregular respiration, coaching was used, and its impact was evaluated for both breathing methods, FB and DIBH. The breathing amplitude performed with FB between volunteers and patients was not detectable at the SCJ; increasing to the abdomen, 3 mm vs 2 mm (p = 0.326) at the second level; 6 mm vs 4 mm (p = 0.042) at the IML; 10 mm vs 8 mm (p < 0.01) at the fourth level; and 23 mm vs 19 mm (p < 0.001) at the XP. Contrary to the DIBH, where breathing amplitude was greater at 2 first levels 18 mm (SCJ) and 20 mm (second level), decreasing to the abdomen, 14 mm (IML); 11 mm (fourth level); and 10 mm (XP). Chest wall expansion was not detected at the SCJ, while at other levels measured from 1 to 7 mm. Coaching was improve breathing amplitude, for both methods, FB (3 mm) and DIBH (5 mm). The location of amplification is different depending on the breathing method and the in-house phantom was useful to check the amplification level.

DATA MINING APPROACH FOR IN-HOSPITAL TREATMENT OUTCOME IN PATIENTS WITH ACUTE CORONARY SYNDROME.

INTRODUCTION: Risk stratification is nowadays crucial when estimating the patient's prognosis in terms of treatment outcome and it also helps in clinical decision making. Several risk assessment models have been developed to predict short-term outcomes in patients with acute coronary syndrome. This study was aimed at developing an outcome prediction model for patients with acute coronary syndrome submitted to percutaneus coronary intervention using data mining approach. MATERIAL AND METHODS: A total of 2030 patients hospitalized for acute coronary syndrome and treated with percutaneous coronary intervention from December 2008 to December 2011 were assigned to a derivation cohort. Demographic and anamnestic data, clinical characteristics on admission, biochemical analysis of blood parameters on admission, and left ventricular ejection fraction formed the basis ofthe study. A number of machine learning algorithms available within Waikato Environment for Knowledge Discovery had been evaluated and the most successful was chosen. The predictive model was subsequently validated in a different population of 931 patients (validation cohort), hospitalized during 2012. RESULTS: The best prediction results were achieved using Alternating Decision Tree classifier, which was able to predict in-hospital mortality with 89% accuracy, and preserved good performance on validation cohort with 87% accuracy. Alternating Decision Tree classifier identified a subset of 6 attributes most relevant to mortality prediction: systolic and diastolic blood pressure, heart rate, left ventricular ejection fraction, age, and troponin value. CONCLUSION: Data mining approach enabled the authors to develop a model capable of predicting the in-hospital outcome following percutaneous coronary intervention. The model showed excellent sensitivity and specificity during internal validation.

THE LEVEL OF GRAMMAR SCHOOL STUDENTS' KNOWLEDGE ON CARDIOVASCULAR DISEASE RISK FACTORS.

INTRODUCTION: Cardiovascular diseases are one of the leading causes of mortality and morbidity worldwide. The atherosclerotic process in the aorta starts in childhood, while atheroclerotic changes of coronary heart vessels start in adolescence. The aim of the study was to evaluate the knowledge of the students attending all four grades of grammar school about the risk factors for cardiovascular disease, with special attention to the risk factors that can be influenced by modification of life-style. MATERIAL AND METHODS: Data from the entrance and exit tests were collected from 197 students attending a grammar school in Novi Sad. Chi-square test and Student T-test or Mann-Whitney U test were used to examine the statistical difference between categorized variables and the continuous variables, respectively. RESULTS: The difference between the number of correct answers for all the students on the entrance test and exit test was statistically significant (p<0.0005) and the overall knowledge level after lectures was increased by 29.4%. The lowest level of knowledge on the entrance tests was noted among the students of the third grade of grammar school and after the lectures, the student's knowledge level was increased by 82.3% (p<0.0005). CONCLUSION: Children and adolescents from Vojvodina and Serbia should be well informed about the cardiovascular disease risk factors and their prevention with special attention paid to the risk factors that can be influenced by changing lifestyle habits.

Clinical performance of the EuroSCORE II compared with the previous EuroSCORE iterations.

BACKGROUND: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) II has been recently introduced as an update to the previous versions. We sought to evaluate the predictive performance of the EuroSCORE II model against the original additive and logistic EuroSCORE models. PATIENTS AND METHODS: The study included 1,247 consecutive patients who underwent cardiac surgery procedures during a 14-month period starting from the beginning of 2012. The original additive and logistic EuroSCORE models were compared with the EuroSCORE II focusing on the accuracy of predicting hospital mortality. RESULTS: The overall hospital mortality rate was 3.45%. The discriminative power of the EuroSCORE II was modest and similar to other algorithms (C-statistics 0.754 for additive EuroSCORE; 0.759 for logistic EuroSCORE; and 0.743 for EuroSCORE II). The EuroSCORE II significantly underestimated the all-patient hospital mortality (3.45% observed vs. 2.12% predicted), as well as in the valvular (3.74% observed vs. 2% predicted), and combined surgery cohorts (6.87% observed vs. 3.64% predicted). The predicted EuroSCORE mortality significantly differed from the observed mortality in the third and the fourth quartile of patients stratified according to the EuroSCORE II mortality risk (p < 0.05). The calibration of the EuroSCORE II was generally good for the entire patient population (Hosmer-Lemeshow [HL] p = 0.139), for the valvular surgery subset (HL p = 0.485), and for the combined surgery subset (HL p = 0.639). CONCLUSION: The EuroSCORE II might be considered a solid predictive tool for hospital mortality. Although, the EuroSCORE II employs more sophisticated calculation methods regarding the number and definition of risk factors included, it does not seem to significantly improve the performance of previous iterations.

Locally derived system for cardiac operative risk evaluation.

INTRODUCTION: During the last two decades, many authors have found that European Systems for Cardiac Operative Risk Evaluation (additive and logistic models) overestimate the risk in cardiac surgery. The new European model has recently been introduced as an update to previous versions. The aim of the study was to investigate the significance of locally derived system for cardiac operative risk evaluation and to compare its predictive power with the existing European systems. MATERIAL AND METHODS: For developing a local risk prediction model, data from 2681 patients submitted to cardiac surgery at the Institute of Cardiovascular Diseases Vojvodina have thoroughly been collected. Logistic regression analysis was used to construct a local model for prediction of outcome. The evaluation of the local model and three European systems was performed by comparing the observed and expected hospital mortality. RESULTS: The difference between the predicted and observed mortality regardless of the type of surgery was statistically insignificant for the additive European system (p=0.073) and the local model (p=0.134). The logistic European system overestimated the operative risk, while the new European model underestimated mortality. In coronary surgery, all models, except the logistic European system, performed well. In valvular surgery, the new European model and the local model underestimated mortality significantly, while the additive and logistic European models performed well. In combined surgery, the new European system significantly underestimated mortality (p=0.029), while the local model performed well (p=0.252). CONCLUSION: The locally derived model shows satisfactory results, with good calibration and discriminative power. The local model specifically outperforms all other European systems in terms of discriminatory power in combined surgery subset.

Vojvodinascore--local system for cardiac operative risk evaluation.

INTRODUCTION: The aim of the study was to investigate the prognostic value, sensitivity and specificity of both the logistic and additive European System for Cardiac Operative Risk Evaluation (as well as the European System for Cardiac Operative Risk Evaluation II and to assess the necessity for developing a local outcome prediction model in cardiac surgery. MATERIAL AND METHODS: The research included 406 consecutive patients who had undergone cardiac surgical procedures at Institute of Cardiovascular Diseases of Vojvodina from January 2012 to July 2012. The authors compared the predicted mortality according to the additive and logistic European Systems for Cardiac Operative Risk Evaluation, the new European System for Cardiac Operative Risk Evaluation II and the observed mortality (30 days after surgery). RESULTS: The difference between the predicted and observed mortality regarding the whole group of 406 operated cardiac patients was not statistically significant for the additive European System for Cardiac Operative Risk Evaluation (p = 0.081) and the European System for Cardiac Operative Risk Evaluation II (p = 0.164), but it was statistically significant for the logistic European System for Cardiac Operative Risk Evaluation (p = 0.031). The areas under the receiver operating characteristic curves are statistically different from 0.5 for both models (additive and logistic European System for Cardiac Operative Risk Evaluation), as well as for the European System for Cardiac Operative Risk Evaluation II. However, the proper classification of the patients has not been observed since their sensitivity and specificity are not satisfactory. CONCLUSION: The additive and logistic European Systems for Cardiac Operative Risk Evaluation overestimate while the European System for Cardiac Operative Risk Evaluation II underestimates the risk in cardiac surgery. We believe that a locally derived model would be of great use in the everyday clinical practice since it would faithfully illustrate the actual state of patient population of the region where it was developed. At the same time it would provide the accurate prediction of surgical outcome.

[Body composition analysis in ballet dancers]. / Analiza telesne kompozicije balerina.

INTRODUCTION: The aim of this study was to evaluate and compare the nutritional status and body composition in female ballet dancers and a group of non-athletic female controls. MATERIALS AND METHODS: The study group consisted of 30 female ballet dancers, aged 17.4 +/- 2.01, whereas the control group included 30 non-athletic female examinees, aged 18.00 years on average. Height and weight were measured and body mass index (BMI) was calculated in all subjects. Body composition was estimated using the bioelectrical impedance method. RESULTS: Body composition analysis of ballet dancers revealed significantly lower values of body fat mass compared to the control group (18.85 +/- 4.50% vs. 23.41 +/- 4.34). Most examinees in both groups were of normal weight. 50% of ballet dancers and 23.33% of examinees in the control group were underweight, while overweight subjects were registered only in the control group. Most underweight ballet dancers had lower body fat mass, whereas majority of underweight examinees in the control group presented with normal body fat mass. Normal-weight obesity was established in 40.91% candidates in the control and 6.67% in the study group. CONCLUSION: Ballet dancers had significantly lower values of body mass and BMI, compared to the study group. In order to prevent very serious complications caused by changes in size and proportion of some body compartments, it is necessary to carry out assessment of body composition more often in high-risk groups, such as the study group of ballet dancers.