Non Invasive Cardiac Output Evaluation with CO₂ Rebreathing Method for CRT Patients
Pages 175-181
Eraldo Occhetta, Chiara Devecchi, Paolo Devecchi, Emanuela Facchini, Virginia Di Ruocco, Laura Plebani and Paolo Nicola Marino
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.03.3
Published: 16 July 2016

Abstract: Background: Cardiac resynchronization therapy with ICD (CRT-D) or pacemaker (CRT-P) is useful to reverse the deleterious effects of ventricular dyssynchronia in heart failure (HF) patients. To determinate the responders patients, hemodynamic parameters are difficult to evaluate during follow-up, due to the invasivity of the procedures. We compare hemodynamic response to CRT with cardiac output, not invasively detected (CO2 rebreathing method, Innocor system), with conventional clinical, functional and echocardiographic parameters.

Methods: We enrolled 29 patients affected by end-stage dilated cardiomyopathy treated with CRT-P/CRT-D according to the latest guidelines (NYHA class II-IV, left ventricular ejection fraction [LVEF] ≤ 35%, QRS ≥ 120 ms, sinus rhythm, optimal medical therapy). Patients were evaluated before and after CRT (3 months), considering: NYHA class, Quality of Life score (Minnesota Living with Heart Failure questionnaire), QRS width, echocardiographic parameters (diastolic and systolic left ventricular volumes and related LVEF), six minutes walking test (6MWT) and cardiac output (detected with Innocor system).

Results: Our data showed a significant improvement in Innocor cardiac output 3 months after CRT implant compared to baseline (4.01±0.72 vs 4.48±0.59 l/min, p=0.001). The percentage improvement in cardiac output correlates with the percentage increase in LVEF (25±6% vs 30±7%; r=0.541). The correlation is not statistically significant with NYHA class (from 2.52±0.73 to 1.78±0.60; r=0.098), QoL (from 22.57±15.37 to 9.91±9.14 score; r=0.231) and exercise tolerance (from 390±50 to 437±54 meters; r=0.144).

Conclusions: The Innocor system is a promising non-invasive method to assess the cardiac output at baseline and during follow up in HF patients treated with CRT.

Statistical Performance Effect of Feature Selection Techniques on Eye State Prediction Using EEG
Pages 224-230
Jean de Dieu Uwisengeyimana, Nusaibah Khalid Al_Salihy and Turgay Ibrikci
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.03.9
Published: 16 July 2016

Abstract: Several recent studies have demonstrated that electrical waves recorded by electroencephalogram (EEG) can be used to Predict eye state (Open or Closed) and all the studies in the literatures used 14 electrodes for data recording. To reduce the number of electrodes without affecting the statistical performance of an EEG device, it is not an easy task. Hence, the focus of this paper is on reducing the number of EEG electrodes by means of feature selection techniques without any consequences on the statistical performance measures of the earlier EEG devices. In this study, we compared different attribute evaluators and classifiers. The results of the experiments have shown that ReliefF attribute evaluator was the best to identify the two least important features (P7, P8) with 96.3% accuracy. The overall results show that two data-recording electrodes could be removed from the EEG devices and still perform well for eye state prediction. The accuracy achieved was equal to 96.3% with KStar (K*) classifier which was also the best classifier among the 21 tested classifiers in this study.

Study on Temporal Effects of Urban Malaria Incidences
Pages 120-132
Krishnendra S. Ganguly, Soumita Modak, Krishna S. Ganguly and Asis K. Chattopadhyay
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.02.6
Published: 08 June 2016

Abstract: In Africa and Asia Malaria is considered to be the most widespread vector-borne disease taking lives of many people and specially affecting children. Many parts of India are significantly affected by malaria over a long period of time. Kolkata is one of the Metropolitan cities in India where the seasonal effect of malaria is very common. In the present work attempts have been made to study temporal variation of urban malaria incidences using time series model on the basis of a large survey conducted by the Kolkata Municipal Corporation. It is found that the proposed time series model can be used successfully for prediction purpose.

Intention-to-Treat Analysis but for Treatment Intention:How should Consumer Product Randomized Controlled Trials be Analyzed?
Pages 90-98
Rolf Weitkunat, Gizelle Baker and Frank Lüdicke
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.02.3
Published: 02 June 2016

Abstract: Background: Experimental study design, randomization, blinding, control, and the analysis of such data according to the intention-to-treat (ITT) principle are de-facto “gold standards” in pharmacotherapy research. While external treatment allocation under conditions of medical practice is conceptually reflected by in-study randomization in randomized controlled trials (RCTs) of therapeutic drugs, actual product use is based on self-selection in a consumer product setting.

Discussion: With in-market product allocation being consumer-internal, there is no standard against which protocol adherence can be attuned, and the question arises, as to whether compliance-based analysis concepts reflect the real-world effects of consumer products.

Summary: The lack of correspondence between RCTs and consumer market conditions becomes evident by the fact that even if, theoretically, all data would be available from all members of the real-world target population, it would be impossible to calculate either an ITT or a per-protocol effect. This renders the calculation of such estimates meaningless in consumer product research contexts.

Confidence Intervals for the Population Correlation Coefficient ρ
Pages 99-111
Shipra Banik and B.M. Golam Kibria
DOI: http://dx.doi.org/10.6000/1929-6029.2016.05.02.4
Published: 02 June 2016

Abstract: Computing a confidence interval for a population correlation coefficient is very important for researchers as it gives an estimated range of values which is likely to include an unknown population correlation coefficient. This paper studied some confidence intervals for estimating the population correlation coefficient ρ by means of a Monte Carlo simulation study. Data are randomly generated from several bivariate distributions with a various values of sample sizes. Assessment measures such as coverage probability, mean width and standard deviation of the width are selected for performances evaluation. Two real life data are analyzed to demonstrate the application of the proposed confidence intervals. Based on our findings, some good confidence intervals for a population correlation coefficient are suggested for practitioners and applied researchers.