Volume 43 (2015): Issue 1 (December 2015)

Many factors play an important role in prediction of infertility treatment outcome (for example, female age and quality of oocytes or embryos are the most important prognostic factors concerning positive IVF outcome). The purpose of this study was to identify a set of variables that could fulfill criteria for prediction of pregnancy in IVF patients through the application of data mining – using the discriminant analysis method. The principle of this method is to establish a set of rules that allows one to place multi-dimensional objects into one of two analyzed groups (pregnant or not pregnant). Six hundred and ten IVF cycles were included in the analysis and the following variables were taken into consideration: female age, number and quality of retrieved oocytes, number and quality of embryos, number of transferred embryos, and outcome of treatment. Discriminant analysis allowed for the creation of a model with a 51.22% correctness of prediction to achieve pregnancy during IVF treatment and with 74.07% correctly predicted failure of pregnancy. Therefore, the created model is more suitable for the prediction of a negative outcome (lack of pregnancy) during IVF treatment and offers an option for adjustments to be made during infertility treatment.

Biomedical signals are frequently noisy and incomplete. They produce complex and high-dimensional data sets. In these mentioned cases, the results of traditional methods of signal processing can be skewed by noise or interference present in the signal. Information entropy, as a measure of disorder or uncertainty in the data, was introduced by Shannon. To date, many different types of entropy methods have appeared with many different application areas. The purpose of this paper is to present a short overview of some methods of entropy analysis and to discuss their suitability for use in the analysis of biomedical signals.

The aim of this study was to evaluate the possibility of incorrect assessment of mortality risk factors in a group of patients affected by acute coronary syndrome, due to the lack of hazard proportionality in the Cox regression model. One hundred and fifty consecutive patients with acute coronary syndrome (ACS) and no age limit were enrolled. Univariable and multivariable Cox proportional hazard analyses were performed. The proportional hazard assumptions were verified using Schoenfeld residuals, χ² test and rank correlation coefficient t between residuals and time. In the total group of 150 patients, 33 (22.0%) deaths from any cause were registered in the follow-up time period of 64 months. The non-survivors were significantly older and had increased prevalence of diabetes and erythrocyturia, longer history of coronary artery disease, higher concentrations of serum creatinine, cystatin C, uric acid, glucose, C-reactive protein (CRP), homocysteine and B-type natriuretic peptide (NT-proBNP), and lower concentrations of serum sodium. No significant differences in echocardiography parameters were observed between groups. The following factors were risk of death factors and fulfilled the proportional hazard assumption in the univariable model: smoking, occurrence of diabetes and anaemia, duration of coronary artery disease, and abnormal serum concentrations of uric acid, sodium, homocysteine, cystatin C and NT-proBNP, while in the multivariable model, the risk of death factors were: smoking and elevated concentrations of homocysteine and NT-proBNP. The study has demonstrated that violation of the proportional hazard assumption in the Cox regression model may lead to creating a false model that does not include only time-independent predictive factors.

One of the most effective methods of infertility treatment is in vitro fertilization (IVF). Effectiveness of the treatment, as well as classification of the data obtained from it, is still an ongoing issue. Classifiers obtained so far are powerful, but even the best ones do not exhibit equal quality concerning possible treatment outcome predictions. Usually, lack of pregnancy is predicted far too often. This creates a constant need for further exploration of this issue. Careful use of different classification methods can, however, help to achieve that goal.

Prevention and early diagnosis of forthcoming preterm labor is of vital importance in preventing child mortality. To date, our understanding of the coordination of uterine contractions is incomplete. Among the many methods of recording uterine contractility, electrohysterography (EHG) – the recording of changes in electrical potential associated with contraction of the uterine muscle, seems to be the most important from a diagnostic point of view. There is some controversy regarding whether EHG may identify patients with a high risk of preterm delivery. There is a need to check various digital signal processing techniques to describe the recorded signals. The study of synchronization of multivariate signals is important from both a theoretical and a practical point of view. Application of the Hilbert transformation seems very promising.

A gene expression data set, containing 3051 genes and 38 tumor mRNA training samples, from a leukemia microarray study, was used for differentiation between ALL and AML groups of leukemia. In this paper, single and combined discriminant methods were applied on the basis of the selected few most discriminative variables according to Wilks’ lambda or the leave-one-out error of first nearest neighbor classifier. For the linear, quadratic, regularized, uncorrelated discrimination, kernel, nearest neighbor and naive Bayesian classifiers, two-dimensional graphs of the boundaries and discriminant functions for diagnostics are presented. Cross-validation and leave-one-out errors were used as measures of classifier performance to support diagnosis coming from this genomic data set. A small number of best discriminating genes, from two to ten, was sufficient to build discriminant methods of good performance. Especially useful were nearest neighbor methods. The results presented herein were comparable with outcomes obtained by other authors for larger numbers of applied genes. The linear, quadratic, uncorrelated Bayesian and regularized discrimination methods were subjected to bagging or boosting in order to assess the accuracy of the fusion. A conclusion drawn from the analysis was that resampling ensembles were not beneficial for two-dimensional discrimination.

The purpose of the study was a comparative analysis of the burden of lung cancer in urban and rural areas in the Świętokrzyskie Province in the years 1999–2010. The material for the study accounted for information about the number of new cases of lung cancer obtained from the Świętokrzyskie Cancer Registration Office in Kielce and data from the Central Statistical Office concerning the number of deaths due to lung cancer in the years 1999–2010. Crude and age-standardized incidence, mortality, and potential years of life lost rates were calculated separately for groups of men and women in urban and rural areas. A comparative analysis of coefficients in urban and rural areas based on Rate Ratio (RR) and Rate Difference (RD) was performed by using the Health Disparities Calculator. The average annual incidence of lung cancer among men was 18% lower in the urban population than in the rural, while the mortality rate was 16% lower. For women, the incidence and mortality rates were higher in urban areas as opposed to rural areas – by 48% and 54% respectively. The comparative analysis of the burden of lung cancer showed great diversity between urban and rural populations in the Świętokrzyskie Province.

Physical activity, along with proper nutrition, is a very important element in child development. Lack of everyday, regular physical activity among young people is a public health problem. The aim of the study was to use cluster analysis to assess the relationship between nutrition and physical activity levels of primary school children. The study included 682 students from randomly selected elementary schools and was performed using a proprietary questionnaire during the 2013/2014 school year. The questionnaire contained questions about eating habits and physical activity, as well as the socio-economic conditions of families. Clusters of students of similar dietary habits were identified using cluster analysis and subsequently compared in terms of physical activity level. We identified four clusters, characterized by relative internal homogeneity and at the same time variability between one another in terms of number of meals throughout the day and time of their consumption. The most important characteristic of Cluster 1 was eating four meals a day including breakfast, which is the most important meal of the day. The diets of children in Cluster 2 abounded with raw vegetables and fruits. Students in Cluster 3 were characterized by a regular and varied diet. The least appropriate behaviour in the field of nutrition was observed among students belonging to Cluster 4. Cluster analysis in the studied population allowed relationships between dietary habits and physical activity to be described. By using the UIAF indicator (Moderate to Intense Physical Activity), a statistically significant association between the eating habits of the children and their physical activity levels was observed. A sufficient level of physical activity was observed in most students belonging to Cluster 3, and high levels of physical activity were observed in a small percentage of children belonging Cluster 4. An average level of physical activity was observed in a high percentage of children belonging to Cluster 4. Low levels of physical activity were most frequently observed in Clusters 4 and 1 and least frequently observed in Cluster 3. All of the identified active forms of free-time activity were most commonly acknowledged in Cluster 3. The study supports a beneficial relationship between students’ eating behaviours and physical activity.

The development and widespread use of ICT in society are reflected by the way research is designed and conducted. The Computer Assisted Web Interview method is becoming more attractive and is a frequently used method in health sciences. The National Study of ICT Use in Primary Healthcare in Poland was conducted using this method. The aim of this paper is to present the major advantages and disadvantages of web surveys. Technical aspects of methodology and important stages of the aforementioned study, as well as key elements for its procedure, are mentioned. The authors also provide reflections based on their analysis of this national study, conducted between January and April 2014.

Computer games have accompanied the development of computer technologies since the very beginning. Despite their basic, purely entertainment-targeted appliance, games can also be used for many other purposes. Medical applications are especially interesting, as games (especially different kinds of simulations) are widely used for training personnel, e.g. to perform certain procedures or in learning to use equipment. This allows the trainees to gain knowledge and proper habits, as well as test themselves in different situations without any risk. Computer games can also be used as a diagnostic tool, although this topic is still insufficiently researched. This paper discusses the possibility of using serious games for diagnosing color vision disorders, focusing especially on two problems: differences in diagnosing colorblindness using 2D and 3D environments, and the influence of individual features, such as reflex or agility, on the diagnostic process.

Reporting systems, based on mobile technologies and feedback from regular citizens, are constantly gaining popularity, especially when it comes to environmental and cultural heritage protection. Reporting life-threatening situations, such as sudden natural disasters or traffic accidents, constitutes the same class of problems and could be aided by IT systems of similar architecture. Emergency services also could benefit from such kinds of solutions, e.g., by getting an accurate location of the place where help is needed as well as fast exchange of information. Designing and developing systems for reporting life-threatening situations is not a trivial task, requiring tight cooperation among software developers and experts of different domains, who most likely would have trouble with industrially recognized languages and notations. Thus, the question is whether using simplified graphical domain-specific languages (SGDSLs) could help in creating a common communication platform. In order to answer that question, short workshops were conducted at the University of Economics in Prague, Czech Republic and in Lublin, Poland. They involved people trained during their studies to work in administration and emergency services, among others, as policy makers, medicine specialists, environmentalists, or managers. All participants received brief training in graphical modeling languages in the context of modeling mobile applications and were asked to voluntarily fill in an anonymous survey in order to check their knowledge about and attitude toward the presented technologies. Most respondents claimed that SGDSLs oriented on defining a flow of actions might be valuable as tools for creating a common communication platform.

The necessary prerequisites for efficiently pursuing distance learning include carefully planned organization of work and resource management tools, typically found in an internet application – a distance learning portal. The portal application must meet a number of capacity and functionality requirements. Learning goals are pursued through implementation of appropriate tools available in the portal. In the article that follows, the authors attempt to analyze this aspect of medical education as utilized by blended learning and e-learning classes. The article presents a proposal for a set of tools to organize classes in an e-learning portal at a medical school. In addition, the article presents the opinions of students of the Poznan University of Medical Sciences and the Medical University of Bialystok who took part in distance education classes.

The popularity of telemedical applications has been increasing noticeably in recent years. Easy access to a variety of software products makes contemporary users concentrate not only on functionalities but also on the design of the Graphical User Interface (GUI) – its usefulness, ease of use, and intuitiveness. The objective of this study was to evaluate the GUI quality of selected telemedical applications dedicated to depressed patients and doctors providing medical care for this group of patients. Another aim of the paper was to propose and check assessment criteria applied to the evaluation experiment. To achieve this objective, the case study was based on two methods: expert analysis and cognitive walkthrough. The expert analysis study was conducted on three groups of users: user experience specialists, patients, and clinicians. Although the expert analysis method is usually dedicated to GUI design specialists, in this study, we also applied it to patient and physician groups. The results showed that there were no statistical differences between assessments carried out by those three groups of users. Applied testing criteria were revised with Nielsen’s heuristics. The proposed criteria helped to uncover many usability problems in several different areas during user tests. Further studies might be performed in order to strengthen accuracy and for completion of the proposed expert analysis evaluation criteria. However, our results show that the criteria we used seem to be robust enough to apply to both expert and end-user evaluations. Furthermore, multiple evaluation based on two different methods presented with better results, allowing not only problem identification but also verification.

Enhancement of teaching using digital materials is rapidly entering the world of medical studies. Creation of a self-learning environment supported with self-tests is received well, or even enthusiastically, among students. On the other hand, there is a relatively large group of opponents among university teachers, who do not see the need for changes in teaching and testing methodology to be made. This attitude may be surfacing as a result of anxiety connected with implementing new technologies in teaching medical subjects, as well as the belief that implementing new technologies does not have an immediate effect on learning quality. The authors of this article attempt to demonstrate that a thoughtful choice of e-learning platform facilitates the process of implementing online learning and testing aids in medical faculties. The second part of the article presents initial results of studies concerning the efficiency of learning enhanced with self-tests. Our analysis details the results of exams in pathophysiology taken by students of the medical faculty at the Poznan University of Medical Sciences. After the course, an evaluation survey was completed by 195 students concerning the quality of teaching with the use of the OLAT (Online Learning and Training) e-learning portal. It showed that students had positive attitudes toward learning with the use of online materials, particularly with regard to the use of self-tests, which allowed students to check their knowledge independently in exam-like conditions. The article that follows is targeted at those teachers who are interested in implementing a self-study and electronic knowledge evaluation environment for their courses, not necessarily in medical subjects.

With the aim of verifying the suitability of the CES-D scale for use in long-term care institutions for older adults, the CES-D questionnaire was used to collect patient-reported assessments, and two well-known psychometric instruments – the Hospital Anxiety and Depression Scale (HADS) and the Barthel Index of Abilities of Daily Living – were used to collect nurse-reported assessments, based on observations of patients’ behaviours. With regard to possible frequent cases of cognitive impairment and/or insufficient motivation to give sensible responses to CES-D questions, the patient-reported responses were collected from patients during one-on-one sessions with a nurse. The reliability, concurrent validity, and the trustworthiness of the obtained data were supported with proper values of the Cronbach’s alpha coefficient, 0.70 < alpha < 0.85, with significant correlation between CES-D and HADS-Depression, R = 0.50, p < 0.001, and with significant correlation between scores of particular CES-D items vs. final CES-D evaluations of depression, proved by significance p < 0.001 for 18 of 20 CES-D items. These findings supported the effectiveness of the one-on-one session methodology in questionnaire surveys for older adults. The postulation that cases of self-reported depression included somewhat different information about the patient than nurse-reported depression concerning the same patient was supported with the evidence that, in spite of the significant correlation between the Barthel Index and HADS-Depression, R = −0.17, p = 0.016, and in spite of the significant correlation between CES-D and HADS-Depression, the correlation between the Barthel Index and CES-D, equal to R = −0.08 was insignificant at p = 0.244. The findings of this study, considered jointly, support the valuableness of the CES-D scale for use in one-on-one surveys for older adults.