A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Pediatric asthma incidence in Texas and associations with ambient ozone levels in an urban area an analysis using Medicaid claims data

Few recent estimates of childhood asthma incidence exist in the literature, although the importance of incidence surveillance for understanding asthma risk factors has been recognized. Asthma prevalence, morbidity and mortality reports have repeatedly shown that low-income children are disproportionately impacted by the disease. The aim of this study was to demonstrate the utility of Medicaid claims data for providing statewide estimates of asthma incidence. Medicaid Analytic Extract (MAX) data for Texas children ages 0-17 enrolled in Medicaid between 2004 and 2007 were used to estimate incidence overall and by age group, gender, race and county of residence. A 13+ month period of continuous enrollment was required in order to distinguish incident from prevalent cases identified in the claims data. Age-adjusted incidence of asthma was 4.26/100 person-years during 2005-2007, higher than reported in other populations. Incidence rates decreased with age, were higher for males than females, differed by race, and tended to be higher in rural than urban areas. With this study, we were able to demonstrate the utility of MAX data for estimating asthma incidence, and create a dataset of incident cases to use in further analysis. ^ In subsequent analyses, we investigated a possible association between ambient air pollutants and incident asthma among Medicaid-enrolled children in Harris County Texas between 2005 and 2007. This population is at high risk for asthma, and living in an area with historically poor air quality. We used a time-stratified case-crossover design and conditional logistic regression to calculate odds ratios, adjusted for weather variables and aeroallergens, to assess the effect of increases in ozone, NO2 and PM2.5 concentrations on risk of developing asthma. Our results show that a 10 ppb increase in ozone was significantly associated with asthma during the warm season (May-October), with the strongest effect seen when a 6-day cumulative lag period was used to compute the exposure metric (OR=1.05, 95% CI, 1.02–1.08). Similar results were seen for NO2 and PM 2.5 (OR=1.07, 95% CI, 1.03–1.11 and OR=1.12, 95% CI, 1.03–1.22, respectively). PM2.5 also had significant effects in the cold season (November-April), 5-day cumulative lag: OR=1.11, 95% CI, 1.00–1.22. When compared with children in the lowest quartile of O3 exposure, the risk for children in the highest quartile was 20% higher. This study indicates that these pollutants are associated with newly-diagnosed childhood asthma in this low-income urban population, particularly during the summer months. ^

Risk factors for metabolic syndrome among overweight and obese Hispanic children attending a pediatric clinic in New Braunfels, Texas

Childhood obesity is a persistent problem in the U.S., especially among Hispanics. Health complications like hypertension, type II diabetes, and metabolic syndrome (Met-S) are being seen at younger ages, and current screening procedures may be inadequate. This study sought to describe the risk factors for Met-S present in a sample of 106 overweight and obese Hispanic children, aged 5-14 years, participating in Nutrition and Exercise Start Today (NEST), a randomized weight management intervention trial at a rural health clinic in New Braunfels, Texas; and to determine associations between these factors and other clinical and socio-demographic characteristics linked to obesity. Baseline data was analyzed for the prevalence of large waist circumference (WC), elevated blood pressure (BP), high fasting serum glucose and serum triglycerides (TG), and low serum HDL cholesterol, in relationship with selected sample characteristics. Main findings included high baseline prevalence rates of large WC (77%), reduced HDL (57%), and elevated BP (30%). WC was significantly associated with BMI percentile and the serum liver function test alanine aminotransferase (ALT) by Fisher's exact test (p<0.001 and p=0.032, respectively), while there were significant relationships between HDL and both female gender and ALT. BMI percentile and ALT were associated with all sets of Met-S diagnostic criteria examined. BMI percentile also had a strong association (p=0.005) with total number of Met-S risk factors, while ALT had a weaker association (p=0.093). WC is a low-cost, simple measure whose use may improve clinic surveillance for childhood obesity and complications like Met-S. WC, BP, HDL and ALT may be used as part of targeted screening for obesity complications like Met-S, particularly in situations where resources are limited.^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Observations from the Balcony: Directions for Pediatric Health Disparities Research and Policy

In 2002, the Institute of Medicine released Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, a landmark monograph documenting health disparities in the U.S. health care system. Since the publication of Unequal Treatment, the field of pediatric health disparities research has advanced significantly with a proliferation of studies examining a wide array of topics concerning inequities in child health. Advances in health care policy and legislation have also added to a heightened discourse on pediatric health disparities. While there has been substantial activity in efforts to address pediatric health disparities, questions remain regarding whether these efforts have changed the trajectory of health equity among children. The aim of this paper is to examine the practical challenges of addressing pediatric health disparities in the dynamic context of global changes in health care research, policy, and legislation relevant to children. Using the Adaptive Leadership framework, this paper outlines a conceptual model for assessing the scope of progress made in addressing pediatric health disparities, diagnoses the continued adaptive challenges of pediatric health disparities, and provides an agenda for further work and future investment.

Debriefing after resuscitations in a pediatric emergency department

Multiple guidelines recommend debriefing of actual resuscitations to improve clinical performance. We implemented a novel standardized debriefing program using a Debriefing In Situ Conversation after Emergent Resuscitations Now (DISCERN) tool. Following the development of the evidence-based DISCERN tool, we conducted an observational study of all resuscitations (intubation, CPR, and/or defibrillation) at a pediatric emergency department (ED) over one year. Resuscitation interventions, patient survival, and physician team leader characteristics were analyzed as predictors for debriefing. Each debriefing's participants, time duration, and content were recorded. Thematic content of debriefings was categorized by framework approach into Team Emergency Assessment Measure (TEAM) elements. There were 241 resuscitations and 63 (26%) debriefings. A higher proportion of debriefings occurred after CPR (p<0.001) or ED death (p<0.001). Debriefing participants always included an attending and nurse; the median number of staff roles present was six. Median interval (from resuscitation end to start of debriefing) & debriefing durations were 33 (IQR 15,67) and 10 minutes (IQR 5,12), respectively. Common TEAM themes included co-operation/coordination (30%), communication (22%), and situational awareness (15%). Stated reasons for not debriefing included: unnecessary (78%), time constraints (19%), or other reasons (3%). Debriefings with the DISCERN tool usually involved higher acuity resuscitations, involved most of the indicated personnel, and lasted less than 10 minutes. This qualitative tool could be adapted to other settings. Future studies are needed to evaluate for potential impacts on education, quality improvement programming, and staff emotional well-being.^

The prevention of catheter related bloodstream infections in a pediatric population

Catheter related bloodstream infections are a significant barrier to success in many inpatient healthcare facilities. The goal of this study was to analyze and determine if an evidence based methodology to reduce the number of catheter related bloodstream infections in a pediatric inpatient healthcare facility had significant impact on the infection rate. Catheter related bloodstream infection rates were compared before and after program implementation. The patient population was selected based upon a recommendation in the 2010 National Healthcare Safety Network report on device related infections. This report indicated a need for more data on pediatric populations requiring admission to a long term care facility. The study design is a retrospective cohort study. Catheter related bloodstream infection data was gathered between 2008 and 2011. In October of 2008 a program implementation began to reduce the number of catheter related bloodstream infections. The key components of this initiative were to implement a standardized catheter maintenance checklist, introduce the usage of a chlorhexadine gluconate based product for catheter maintenance and skin antisepsis, and a multidisciplinary education plan that focused on hand hygiene and aseptic technique. The catheter related bloodstream infection rate in 2008 was 21.21 infections per 1000 patient-line days. After program implementation the 2009 catheter related bloodstream infection rate dropped to 1.11 per 1000 patient-line days. The infection rates in 2010 and 2011 were 2.19 and 1.47 respectively. Additionally, this study demonstrated that there was a potential cost savings of $620,000 to $1,240,000 between 2008 and 2009. In conclusion, an evidence based program based upon CDC guidelines can have a significant impact on catheter related bloodstream infection rates. ^

Circadian rhythm profiles in porcine ICU subjects

Purpose: To explore the natural trajectory of circadian rhythms of sedation requirement, core body temperature (CBT), pulmonary mechanics (PM), and gas exchange (GE) in mechanically ventilated swine, as these variables affect the duration of mechanical ventilation. ^ Design: A secondary analysis to describe and compare circadian rhythms of study variables in swine mechanically ventilated for ≤ 7 days. ^ Setting: Porcine Intensive Care Unit (ICU).^ Sample: Six male swine. ^ Methods: Sedation requirements were recorded hourly and the CBT, PM and GE variables were sampled every 1 s – 1 min for ≤ 7 days. The data sets for each pig with > 5 days ICU length of stay were divided into one section representing the first 3 days and one section representing subsequent days. The Lomb periodogram was used to estimate the circadian time period for each variable, and cosinor analysis with the estimated time period to obtain amplitude and mesor. Circadian to ultradian bandpower ratio to assess rhythm quality and stability over time and goodness-of-fit index to describe biological significance of a rhythm were used. Together, these two parameters were used to define rhythm robustness over time. The masking effect of sedation as a potential confounder of the circadian rhythms of CBT, PM, and GE was explored, and circadian rhythm profiles of CBT of pigs in the ICU setting were compared with those of the same pigs in the ambulatory setting. ^ Results: All pigs had significant rhythms in CBT, respiratory rate, and peripheral oxygen saturation across ICU data sets. Healthier pigs had more robust rhythms of study variables over time. Sedation did not appear to mask the circadian rhythms of CBT, PM, and GE. The circadian rhythm of CBT was less robust in the ICU setting than in the ambulatory setting. ^ Conclusions: Individual subject observations provided preliminary evidence that robustness of rhythms varies with subject acuity. Comparison of profiles of circadian rhythms among ICU subjects with similar acuity and disease processes is warranted to determine if the profiles in the present study are reproducible. Identification of consistent patterns may provide insight into subject morbidity and timing of such therapeutic interventions as weaning from mechanical ventilation. ^

Weight-for-age percentile and its association to community acquired methicillin resistant Staphylococcus aureus among pediatric patients in Houston, TX

BACKGROUND: Weight has been implicated as a risk factor for symptomatic community-acquired methicillin resistant Staphylococcus Aureus (CA-MRSA). Information from Texas Children's Hospital (TCH) in Houston, TX was used to implement a case-control study to assess weight-for-age percentile (WFA), race and seasonal exposure as risk factors. ^ METHODS: A retrospective chart review to collect data from TCH was conducted covering the time period January 1st, 2008 to May 31st, 2011. Cases were confirmed and identified by the infectious disease department and were matched on a 1:1 ratio to controls that were seen by the emergency department for non-infected fractures from June 1st, 2008 to May 31st, 2011. Data abstraction was performed using TCH's electronic medical records (EMR) system (EPIC ®). ^ RESULTS: Of 702 CA-MRSA identified cases, ages 9 to 16.99, 564 (80.3%) had the variable `weight' present in their EMR, were not duplicates and not determined to be outliers. Cases were randomly matched to a pool of available controls (n=1864) according to age and gender, yielding 539 1:1 matched pairs (95.5% case matching success) with a total study sample size, N=1078. Case median age was 13.38 years with the majority being White (66.05%) and male (59.4%). Adjusted conditional logistic regression analysis of the matched pairs identified the following risk factors to presenting with CA-MRSA infection among pediatric patients, ages 9 to 16.99 years: a) Individual weight in the highest (75th-99.9th) WFA quartile (OR=1.36; 95% confidence interval [CI]=1.06-1.74; P= 0.016), b) Infection during summer months (OR: 1.69; 95% CI=1.2-2.38; P= 0.003), c) patients of African American race/ethnicity (OR= 1.48; 95% CI=1.13-1.95; P= 0.004). ^ CONCLUSIONS: Pediatric patients, 9 to 16.99 years of age, in the highest WFA quartile (75th-99.9th), or of African-American race had an associated increased risk of presenting with CA-MRSA infection. Furthermore, children in this population were at a higher risk of contracting CA-MRSA infection during the summer season.^

A new way of teaching different subjects in a foreign language in the Building Engineering Degree at the Universidad Politécnica.

The European Union has been promoting linguistic diversity for many years as one of its main educational goals. This is an element that facilitates student mobility and student exchanges between different universities and countries and enriches the education of young undergraduates. In particular, a higher degree of competence in the English language is becoming essential for engineers, architects and researchers in general, as English has become the lingua franca that opens up horizons to internationalisation and the transfer of knowledge in today’s world. Many experts point to the Integrated Approach to Contents and Foreign Languages System as being an option that has certain benefits over the traditional method of teaching a second language that is exclusively based on specific subjects. This system advocates teaching the different subjects in the syllabus in a language other than one’s mother tongue, without prioritising knowledge of the language over the subject. This was the idea that in the 2009/10 academic year gave rise to the Second Language Integration Programme (SLI Programme) at the Escuela Arquitectura Técnica in the Universidad Politécnica Madrid (EUATM-UPM), just at the beginning of the tuition of the new Building Engineering Degree, which had been adapted to the European Higher Education Area (EHEA) model. This programme is an interdisciplinary initiative for the set of subjects taught during the semester and is coordinated through the Assistant Director Office for Educational Innovation. The SLI Programme has a dual goal; to familiarise students with the specific English terminology of the subject being taught, and at the same time improve their communication skills in English. A total of thirty lecturers are taking part in the teaching of eleven first year subjects and twelve in the second year, with around 120 students who have voluntarily enrolled in a special group in each semester. During the 2010/2011 academic year the degree of acceptance and the results of the SLI Programme have been monitored. Tools have been designed to aid interdisciplinary coordination and to analyse satisfaction, such as coordination records and surveys. The results currently available refer to the first and second year and are divided into specific aspects of the different subjects involved and into general aspects of the ongoing experience.

First steps in the discovery of patterns in the academic results of telecommunication engineering students in the subjects Analysis of Circuits and Mathematics

In this paper, the results of six years of research in engineering education, in the application of the European Higher Education Area (EHEA) to improve the performance of the students in the subject Analysis of Circuits of Telecommunication Engineering, are analysed taking into consideration the fact that there would be hidden variables that both separate students into subgroups and show the connection among several basic subjects such as Analysis of Circuits (AC) and Mathematics (Math). The discovery of these variables would help us to explain the characteristics of the students through the teaching and learning methodology, and would show that there are some characteristics that instructors do not take into account but that are of paramount importance

Simulation of academic performance rates, estimation of indicators of subjects and of a complete degree

The purpose of this paper is to present a program written in Matlab-Octave for the simulation of the time evolution of student curricula, i.e, how students pass their subjects along time until graduation. The program computes, from the simulations, the academic performance rates for the subjects of the study plan for each semester as well as the overall rates, which are a) the efficiency rate defined as the ratio of the number of students passing the exam to the number of students who registered for it and b) the success rate, defined as the ratio of the number of students passing the exam to the number of students who not only registered for it but also actually took it. Additionally, we compute the rates for the bachelor academic degree which are established for Spain by the National Quality Evaluation and Accreditation Agency (ANECA) and which are the graduation rate (measured as the percentage of students who finish as scheduled in the plan or taking an extra year) and the efficiency rate (measured as the percentage of credits which a student who graduated has really taken). The simulation is done in terms of the probabilities of passing all the subjects in their study plan. The application of the simulator to Polytech students in Madrid, where requirements for passing are specially stiff in first and second year subjects, is particularly relevant to analyze student cohorts and the probabilities of students finishing in the minimum of four years, or taking and extra year or two extra years, and so forth. It is a very useful tool when designing new study plans. The calculation of the probability distribution of the random variable "number of semesters a student has taken to complete the curricula and graduate" is difficult or even unfeasible to obtain analytically, and this is even truer when we incorporate uncertainty in parameter estimation. This is why we apply Monte Carlo simulation which not only provides illustration of the stochastic process but also a method for computation. The stochastic simulator is proving to be a useful tool for identification of the subjects most critical in the distribution of the number of semesters for curriculum vitae (CV) completion and subsequently for a decision making process in terms of CV planning and passing standards in the University. Simulations are performed through a graphical interface where also the results are presented in appropriate figures. The Project has been funded by the Call for Innovation in Education Projects of Universidad Politécnica de Madrid (UPM) through a Project of its school Escuela Técnica Superior de Ingenieros Industriales ETSII during the period September 2010-September 2011.

Comparing the effectiveness of equivalence partitioning, branch testing and code reading by stepwise abstraction applied by subjects

Some verification and validation techniques have been evaluated both theoretically and empirically. Most empirical studies have been conducted without subjects, passing over any effect testers have when they apply the techniques. We have run an experiment with students to evaluate the effectiveness of three verification and validation techniques (equivalence partitioning, branch testing and code reading by stepwise abstraction). We have studied how well able the techniques are to reveal defects in three programs. We have replicated the experiment eight times at different sites. Our results show that equivalence partitioning and branch testing are equally effective and better than code reading by stepwise abstraction. The effectiveness of code reading by stepwise abstraction varies significantly from program to program. Finally, we have identified project contextual variables that should be considered when applying any verification and validation technique or to choose one particular technique.

Study about the Problem of Dropping of Subjects by Students During an Academinc Year at the University.

In university studies, it is not unusual for students to drop some of the subjects they have enrolled in for the academic year. They start by not attending lectures, sometimes due to neglect or carelessness, or because they find the subject too difficult, this means that they lose the continuity in the topics that the professor follows. If they try to attend again they discover that they hardly understand anything and become discouraged and so decide to give up attending lectures and study on their own. However some fail to turn up to do their final exams and the failure rate of those who actually do the exams is high. The problem is that this is not only the case with one specific subject, but it is often the same with many subjects. The result is that students arent’s productive enough, wasting time and also prolonging their years of study which entails a great cost for families. Degree courses structured to be conducted and completed in three academic courses, it may in fact take up to an average of six or more academic courses. In this paper, we have studied this problem, which apart from the waste of money and time, produces frustration in the student, who finds that he has not been able to achieve what he had proposed at the beginning of the course. It is quite common, to find students who do not even pass nor 50% of the subjects they had enrolled in for the academic year. If this happens repeatedly to a student, it can be the point when he considers dropping out altogether. This is also a concern for the universities, especially in the early courses. In our experience as professors, we have found that students, who attend lectures regularly and follow the explanations, approach the final exams with confidence and rarely fail the subject. In this proposal we present some techniques and methods carried out to solve in possible, the problem of lack of attendance to lectures. This involves "rewarding students for their assistance and participation in lectures". Rewarding assistance with a "prize" that counts for the final mark on the subject and involving more participation in the development of lectures. We believe that we have to teach students to use the lectures as part of their learning in a non-passive way. We consider the professor's work as fundamental in terms of how to convey the usefulness of these topics explained and the applications that they will have for their professional life in the future. In this way the student see for himself the use and importance of what he is learning. When his participation is required, he will feel more involved and confident participating in the educational system. Finally we present statistical results of studies carried out on different degrees and on different subjects over two consecutive years. In the first year we assessed only the final exams without considering the students attendance, or participation. In the second year, we have applied the techniques and methods proposed here. In addition we have compared the two ways of assessing subjects.

Reliability and reproductibility of skin temperature of overweight subjects by an infrared thermograpy software designed for human beings

The technical improvement and new applications of Infrared Thermography (IRT) with healthy subjects should be accompanied by results about the reproducibility of IRT measurements in different popula-tion groups. In addition, there is a remarkable necessity of a larger supply on software to analyze IRT images of human beings. Therefore, the objectives of this study were: firstly, to investigate the reproducibility of skin temperature (Tsk) on overweight and obese subjects using IRT in different Regions of Interest (ROI), moments and side-to-side differences (?T); and secondly, to check the reliability of a new software called Termotracker®, specialized on the analysis of IRT images of human beings. Methods: 22 overweight and obese males (11) and females (11) (age: 41,51±7,76 years; height: 1,65±0,09 m; weight: 82,41±11,81 Kg; BMI: 30,17±2,58 kg/m²) were assessed in two consecutive thermograms (5 seconds in-between) by the same observer, using an infrared camera (FLIR T335, Sweden) to get 4 IRT images from the whole body. 11 ROI were selected using Termotracker® to analyze its reproducibility and reliability through Intra-class Correlation Coefficient (ICC) and Coefficient of Variation (CV) values. Results: The reproducibility of the side-to-side differences (?T) between two consecutive thermograms was very high in all ROIs (Mean ICC = 0,989), and excellent between two computers (Mean ICC = 0,998). The re-liability of the software was very high in all the ROIs (Mean ICC = 0,999). Intraexaminer reliability analysing the same subjects in two consecutive thermograms was also very high (Mean ICC = 0,997). CV values of the different ROIs were around 2%. Conclusions: Skin temperature on overweight subjects had an excellent reproducibility for consecutive ther-mograms. The reproducibility of thermal asymmetries (?T) was also good but it had the influence of several factors that should be further investigated. Termotracker® reached excellent reliability results and it is a relia-ble and objective software to analyse IRT images of humans beings.