Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms.

Breast cancer is the most common cancer in women. Ultrasound is one of the most used techniques for diagnosis, but an expert in the field is necessary to interpret the test. Computer-aided diagnosis (CAD) systems aim to help physicians during this process. Experts use the Breast Imaging-Reporting and Data System (BI-RADS) to describe tumors according to several features (shape, margin, orientation...) and estimate their malignancy, with a common language. To aid in tumor diagnosis with BI-RADS explanations, this paper presents a deep neural network for tumor detection, description, and classification. An expert radiologist described with BI-RADS terms 749 nodules taken from public datasets. The YOLO detection algorithm is used to obtain Regions of Interest (ROIs), and then a model, based on a multi-class classification architecture, receives as input each ROI and outputs the BI-RADS descriptors, the BI-RADS classification (with 6 categories), and a Boolean classification of malignancy. Six hundred of the nodules were used for 10-fold cross-validation (CV) and 149 for testing. The accuracy of this model was compared with state-of-the-art CNNs for the same task. This model outperforms plain classifiers in the agreement with the expert (Cohen's kappa), with a mean over the descriptors of 0.58 in CV and 0.64 in testing, while the second best model yielded kappas of 0.55 and 0.59, respectively. Adding YOLO to the model significantly enhances the performance (0.16 in CV and 0.09 in testing). More importantly, training the model with BI-RADS descriptors enables the explainability of the Boolean malignancy classification without reducing accuracy.

Probabilistic graphical model for the evaluation of the emotional and dramatic personality disorders.

Personality disorders are psychological ailments with a major negative impact on patients, their families, and society in general, especially those of the dramatic and emotional type. Despite all the research, there is still no consensus on the best way to assess and treat them. Traditional assessment of personality disorders has focused on a limited number of psychological constructs or behaviors using structured interviews and questionnaires, without an integrated and holistic approach. We present a novel methodology for the study and assessment of personality disorders consisting in the development of a Bayesian network, whose parameters have been obtained by the Delphi method of consensus from a group of experts in the diagnosis and treatment of personality disorders. The result is a probabilistic graphical model that represents the psychological variables related to the personality disorders along with their relations and conditional probabilities, which allow identifying the symptoms with the highest diagnostic potential. This model can be used, among other applications, as a decision support system for the assessment and treatment of personality disorders of the dramatic or emotional cluster. In this paper, we discuss the need to validate this model in the clinical population along with its strengths and limitations.

Daily Estimation of Global Solar Irradiation and Temperatures Using Artificial Neural Networks through the Virtual Weather Station Concept in Castilla and León, Spain.

In this article, the interpolation of daily data of global solar irradiation, and the maximum, average, and minimum temperatures were measured. These measurements were carried out in the agrometeorological stations belonging to the Agro-climatic Information System for Irrigation (SIAR, in Spanish) of the Region of Castilla and León, in Spain, through the concept of Virtual Weather Station (VWS), which is implemented with Artificial Neural Networks (ANNs). This is serving to estimate data in every point of the territory, according to their geographic coordinates (i.e., longitude and latitude). The ANNs of the Multilayer Feed-Forward Perceptron (MLP) used are daily trained, along with data recorded in 53 agro-meteorological stations, and where the validation of the results is conducted in the station of Tordesillas (Valladolid). The ANN models for daily interpolation were tested with one, two, three, and four neurons in the hidden layer, over a period of 15 days (from 1 to 15 June 2020), with a root mean square error (RMSE, MJ/m2) of 1.23, 1.38, 1.31, and 1.04, respectively, regarding the daily global solar irradiation. The interpolation of ambient temperature also performed well when applying the VWS concept, with an RMSE (°C) of 0.68 for the maximum temperature with an ANN of four hidden neurons, 0.58 for the average temperature with three hidden neurons, and 0.83 for the minimum temperature with four hidden neurons.

Long-term outcomes of an advanced hybrid closed-loop system: A focus on different subpopulations.

BACKGROUND: The long-term benefit provided by advanced hybrid closed-loop (AHCL) systems needs to be assessed in general populations and specific subpopulations. METHODS: A prospective evaluation of subjects initiating the AHCL system 780G was performed. Time in range (70-180 mg/dl) (TIR), <70 mg/dl, <54 mg/dl, >180 mg/dl and >250 mg/dl were compared, at baseline and after one year, in different subpopulations, according to previous treatment (pump vs MDI), age (> or ≤25 years old) and hypoglycaemia risk at baseline. RESULTS: 135 subjects were included (age: 35 ± 15 years, 64 % females, diabetes duration: 21 ± 12 years). An increase in TIR was found, from 67.26 ± 11.80 % at baseline to 77.41 ± 8.85 % after one year (p < 0.001). All the subgroups showed a significant improvement in TIR, time > 180 mg/dl and >250 mg/dl. At the 1-year evaluation, no significant differences were found, between previous pump users and MDI subjects. Children and young adults had a lower time < 70 mg/dl than adults. Subjects with a high risk of hypoglycaemia at baseline had a higher time spent at <70 mg/dl and <54 mg/dl than low-risk individuals. CONCLUSION: The initial benefit provided by the AHCL system is sustained in the long term. MDI subjects obtain the same outcomes as subjects with pump experience.

Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain.

This study evaluates the predictive modeling of the daily ambient temperature (maximum, Tmax; average, Tave; and minimum, Tmin) and its hourly estimation (T0h, …, T23h) using artificial neural networks (ANNs) for agricultural applications. The data, 2004-2010, were used for training and 2011 for validation, recorded at the SIAR agrometeorological station of Mansilla Mayor (León). ANN models for daily prediction have three neurons in the output layer (Tmax(t + 1), Tave(t + 1), Tmin(t + 1)). Two models were evaluated: (1) with three entries (Tmax(t), Tave(t), Tmin(t)), and (2) adding the day of the year (J(t)). The inclusion of J(t) improves the predictions, with an RMSE for Tmax = 2.56, Tave = 1.65 and Tmin = 2.09 (°C), achieving better results than the classical statistical methods (typical year Tave = 3.64 °C; weighted moving mean Tmax = 2.76, Tave = 1.81 and Tmin = 2.52 (°C); linear regression Tave = 1.85 °C; and Fourier Tmax = 3.75, Tave = 2.67 and Tmin = 3.34 (°C)) for one year. The ANN models for hourly estimation have 24 neurons in the output layer (T0h(t), …, T23h(t)) corresponding to the mean hourly temperature. In this case, the inclusion of the day of the year (J(t)) does not significantly improve the estimations, with an RMSE = 1.25 °C, but it improves the results of the ASHRAE method, which obtains an RMSE = 2.36 °C for one week. The results obtained, with lower prediction errors than those achieved with the classical methods, confirm the interest in using the ANN models for predicting temperatures in agricultural applications.

Surgical Risk Following Anatomic Lung Resection in Thoracic Surgery: A Prediction Model Derived from a Spanish Multicenter Database. / Riesgo quirúrgico tras resección pulmonar anatómica en cirugía torácica. Modelo predictivo a partir de una base de datos nacional multicéntrica.

INTRODUCTION: The aim of this study was to develop a surgical risk prediction model in patients undergoing anatomic lung resections from the registry of the Spanish Video-Assisted Thoracic Surgery Group (GEVATS). METHODS: Data were collected from 3,533 patients undergoing anatomic lung resection for any diagnosis between December 20, 2016 and March 20, 2018. We defined a combined outcome variable: death or Clavien Dindo grade IV complication at 90 days after surgery. Univariate and multivariate analyses were performed by logistic regression. Internal validation of the model was performed using resampling techniques. RESULTS: The incidence of the outcome variable was 4.29% (95% CI 3.6-4.9). The variables remaining in the final logistic model were: age, sex, previous lung cancer resection, dyspnea (mMRC), right pneumonectomy, and ppo DLCO. The performance parameters of the model adjusted by resampling were: C-statistic 0.712 (95% CI 0.648-0.750), Brier score 0.042 and bootstrap shrinkage 0.854. CONCLUSIONS: The risk prediction model obtained from the GEVATS database is a simple, valid, and reliable model that is a useful tool for establishing the risk of a patient undergoing anatomic lung resection.

Sum-Product Networks: A Survey.

A sum-product network (SPN) is a probabilistic model, based on a rooted acyclic directed graph, in which terminal nodes represent probability distributions and non-terminal nodes represent convex sums (weighted averages) and products of probability distributions. They are closely related to probabilistic graphical models, in particular to Bayesian networks with multiple context-specific independencies. Their main advantage is the possibility of building tractable models from data, i.e., models that can perform several inference tasks in time proportional to the number of edges in the graph. They are somewhat similar to neural networks and can address the same kinds of problems, such as image processing and natural language understanding. This paper offers a survey of SPNs, including their definition, the main algorithms for inference and learning from data, several applications, a brief review of software libraries, and a comparison with related models.

Prevention, Diagnosis and Management of Post-Surgical Mediastinitis in Adults Consensus Guidelines of the Spanish Society of Cardiovascular Infections (SEICAV), the Spanish Society of Thoracic and Cardiovascular Surgery (SECTCV) and the Biomedical Research Centre Network for Respiratory Diseases (CIBERES).

This is a consensus document of the Spanish Society of Cardiovascular Infections (SEICAV), the Spanish Society of Thoracic and Cardiovascular Surgery (SECTCV) and the Biomedical Research Centre Network for Respiratory Diseases (CIBERES). These three entities have brought together a multidisciplinary group of experts that includes anaesthesiologists, cardiac and cardiothoracic surgeons, clinical microbiologists, infectious diseases and intensive care specialists, internal medicine doctors and radiologists. Despite the clinical and economic consequences of sternal wound infections, to date, there are no specific guidelines for the prevention, diagnosis and management of mediastinitis based on a multidisciplinary consensus. The purpose of the present document is to provide evidence-based guidance on the most effective diagnosis and management of patients who have experienced or are at risk of developing a post-surgical mediastinitis infection in order to optimise patient outcomes and the process of care. The intended users of the document are health care providers who help patients make decisions regarding their treatment, aiming to optimise the benefits and minimise any harm as well as the workload.

Compromiso laboral: nueva escala para su medición / Work Engagement: New scale for its measurement

Resumen Introducción. Uno de los factores más determinantes del rendimiento laboral es el grado de compromiso de las personas con las actividades que realizan. El objetivo de esta investigación es el desarrollo y análisis psicométrico de una nueva escala para la evaluación del compromiso laboral. Método. Se empleó una muestra de 599 trabajadores en activo, el 51% clasificados como emprendedores. El 53% fueron hombres y la media de edad fue de 44.41 años (DT = 8.78). Resultados. La nueva escala desarrollada consta de 10 ítems y muestra una estructura esencialmente unidimensional. La fiabilidad fue excelente (α = .92; ω = .92), y se obtuvieron evidencias de validez en relación con el Clima Organizacional (r = .540), Personalidad Emprendedora (r = .701), Felicidad (r = .674), Reparación Emocional (r = .470), y Estabilidad Emocional (r = .440). Conclusión. La escala desarrollada para la evaluación del compromiso laboral muestra unas buenas propiedades psicométricas, constituyendo una herramienta muy adecuada para su utilización tanto en investigación como en contextos profesionales aplicados.

Abstract Introduction. One of the most determining factors of work performance is the degree of engagement of people to the activities they carry out. The objective of this research is the development and psychometric analysis of a new scale for the evaluation of work engagement. Method. A sample of 599 active workers was used, 51% classified as entrepreneurs. 53% were men and the mean age was 44.41 years (SD = 8.78). Results. The new scale consists of 10 items and shows an essentially one-dimensional structure. Reliability was excellent (α = .92; ω = .92), and evidence of validity was obtained in relation to Organizational Climate (r = .540), Entrepreneurial Personality (r = .701), Happiness (r = .674), Emotional Repair (r = .470), and Emotional Stability (r = .440). Conclusion. The scale developed for the evaluation of work engagement shows good psychometric properties, constituting a very suitable tool for its use both in research and in applied professional contexts.

Amelioration of user experiences and glycaemic outcomes with an Advanced Hybrid Closed Loop System in a real-world clinical setting.

AIMS: Automation in diabetes technology is rapidly evolving. The aim was to evaluate the real-world glycemic outcomes and user acceptance after 3 months of using the Medtronic 780G Advanced Hybrid Closed-Loop (AHCL) system. METHODS: A prospective analysis was performed. A glucose target of 100 mg/dl and an active insulin time of 2 h were set. Capillary HbA1c, 2-week of pump and sensor data and several satisfaction questionnaire scores were compared at baseline and after 3 months of using the AHCL system. RESULTS: 52 subjects were selected (age: 43 ±â€¯12 years, sex: 73% female, diabetes duration: 27 ±â€¯11 years, higher education: 31%). Time in range (TIR) 70-180 mg/dl increased from 67.3 ±â€¯13.6% to 80.1 ±â€¯7.5% and time >180 mg/dl and >250 mg/dl were reduced (16.8 ±â€¯8.4 vs 29.4 ±â€¯15.1%, 2.7 ±â€¯3.0% vs 6.9 ±â€¯7.8%, respectively) (all p < 0.001), while time in hypoglycaemia remained below recommended targets. Time in Auto-Mode and sensor use were 94 ±â€¯10% and 90 ±â€¯11%, respectively. Auto-correction boluses represented 29 ±â€¯12% of bolus insulin. Fear of hypoglycaemia, diabetes quality of life, sleep quality and satisfaction with the monitoring system improved after 3 months. CONCLUSION: The real-world use of the AHCL system Medtronic 780G provides an 80.1% TIR 70-180 mg/dl with minimal hypoglycaemia and an increased level of patient satisfaction.

Cost-effectiveness analysis with unordered decisions.

INTRODUCTION: Cost-effectiveness analysis (CEA) is used increasingly in medicine to determine whether the health benefit of an intervention is worth the economic cost. Decision trees, the standard decision modeling technique for non-temporal domains, can only perform CEAs for very small problems. Influence diagrams can model much larger problems, but only when the decisions are totally ordered. OBJECTIVE: To develop a CEA method for problems with unordered or partially ordered decisions, such as finding the optimal sequence of tests for diagnosing a disease. METHODS: We explain how to model those problems using decision analysis networks (DANs), a new type of probabilistic graphical model, somewhat similar to Bayesian networks and influence diagrams. We present an algorithm for evaluating DANs with two criteria, cost and effectiveness, and perform some experiments to study its computational efficiency. We illustrate the representation framework and the algorithm using a hypothetical example involving two therapies and several tests and then present a DAN for a real-world problem, the mediastinal staging of non-small cell lung cancer. RESULTS: The evaluation of a DAN with two criteria, cost and effectiveness, returns a set of intervals for the willingness to pay, separated by incremental cost-effectiveness ratios (ICERs). The cost, the effectiveness, and the optimal intervention are specific for each interval, i.e., they depend on the willingness to pay. CONCLUSION: Problems involving several unordered decisions can be modeled with DANs and evaluated in a reasonable amount of time. OpenMarkov, an open-source software tool developed by our research group, can be used to build the models and evaluate them using a graphical user interface.

Rapid Improvement in Time in Range After the Implementation of an Advanced Hybrid Closed-Loop System in Adolescents and Adults with Type 1 Diabetes.

Background: Advanced hybrid closed-loop (AHCL) systems represent the next step of automation intended to maximize normoglycemia in people with type 1 diabetes (T1D). In the AHCL MiniMed 780G system, different algorithm glucose targets for insulin infusion are available and autocorrection boluses are delivered. The aim was to prospectively evaluate the impact of the implementation of this AHCL system in a clinical setting. Materials and Methods: T1D subjects using a sensor-augmented pump with predictive low-glucose suspend (SAP-PLGS) were upgraded to AHCL. Baseline, every 3 days, 2-week and 1-month sensor and pump data were downloaded. Glucose target was set to 100 mg/dL and active insulin time to 2 h for all the subjects. Time in different glucose ranges was compared. Results: Fifty-two T1D subjects were included (age: 43 ± 12 years, 73% females, diabetes duration: 27 ± 11 years, HbA1c: 7.2% ± 0.9%, time in SAP-PLGS: 5 ± 2 years). Time in range (TIR) 70-180 mg/dL increased from 67.3% ± 13.6% at baseline to 79.6% ± 7.9% at 1 month (P = 0.001). Time in hyperglycemia >180 and >250 mg/dL decreased from 29.4% ± 15.1% to 17.3% ± 8.6% and from 6.9% ± 7.8% to 2.5% ± 2.4%, respectively (P = 0.001). No differences in time in hypoglycemia <70 or <54 mg/dL were found. Time in Auto Mode was 97% ± 4%, and autocorrection insulin was 31% ± 14% of bolus insulin. Four hours postprandial glucose was improved from 162 ± 26 mg/dL at baseline to 142 ± 16 mg/dL at 1 month (P = 0.001). No severe hypoglycemia or diabetic ketoacidosis episodes occurred. Conclusion: AHCL systems allow well-controlled T1D patients to rapidly increase their TIR. The most aggressive settings allow optimal outcomes in TIR, without increasing hypoglycemia frequency.

Acoustic projection by electro-osmosis.

Electro-osmosis (EO) is a non-traditional pumping and transduction mechanism with the ability to project acoustic energy in fluids. This investigation experimentally validates the influence of zeta potential, a well-studied physical characteristic used for quantifying the efficacy of an EO pump, on generation of sound pressure level. Acoustic signals of discrete frequencies were observed from 130 Hz to over 150 kHz. EO-type projectors are an attractive technology in that it does not contain moving parts, can be fabricated using a variety of materials, is intrinsically resilient to effects of hydrostatic pressure, and may be designed on the micro-electromechanical system scale.

Assessment of the Enterprising Personality: A Short Form of The BEPE Battery.

BACKGROUND: Enterprising personality is related to business creation and success. The objective of this study was the development and psychometric analysis of a reduced version of the BEPE Battery for the Evaluation of Enterprising Personality. METHOD: We used a sample of 1,170 people, 60% women, with a mean age of 42.34 years (SD = 12.96). We carried out psychometric analyses within the frameworks of Classical Test Theory and Item Response Theory models. RESULTS: The short version (BEPE-16) consists of 16 items, demonstrating an essentially unidimensional structure. The reliability was excellent (α= .94; Ω= .94) and evidence of validity was found in relation to various variables: Measure Of Entrepreneurial Talents And Abilities (META test) (r=.71), extraversion (r=.57), conscientiousness (r=.50), neuroticism (r=-.54). The correlation between scores from the BEPE-16 and the original version was very high (r=.95). CONCLUSIONS: The BEPE-16 reduced version for the evaluation of enterprising personality demonstrated good psychometric properties, both in terms of reliability and validity. As such, it can be used in place of the original when the professional or research circumstances require it.

Spanish Video-Assisted Thoracic Surgery Group: Method, Auditing, and Initial Results From a National Prospective Cohort of Patients Receiving Anatomical Lung Resections.

INTRODUCTION: Our study sought to know the current implementation of video-assisted thoracoscopic surgery (VATS) for anatomical lung resections in Spain. We present our initial results and describe the auditing systems developed by the Spanish VATS Group (GEVATS). METHODS: We conducted a prospective multicentre cohort study that included patients receiving anatomical lung resections between 12/20/2016 and 03/20/2018. The main quality controls consisted of determining the recruitment rate of each centre and the accuracy of the perioperative data collected based on six key variables. The implications of a low recruitment rate were analysed for "90-day mortality" and "Grade IIIb-V complications". RESULTS: The series was composed of 3533 cases (1917 VATS; 54.3%) across 33 departments. The centres' median recruitment rate was 99% (25-75th:76-100%), with an overall recruitment rate of 83% and a data accuracy of 98%. We were unable to demonstrate a significant association between the recruitment rate and the risk of morbidity/mortality, but a trend was found in the unadjusted analysis for those centres with recruitment rates lower than 80% (centres with 95-100% rates as reference): grade IIIb-V OR=0.61 (p=0.081), 90-day mortality OR=0.46 (p=0.051). CONCLUSIONS: More than half of the anatomical lung resections in Spain are performed via VATS. According to our results, the centre's recruitment rate and its potential implications due to selection bias, should deserve further attention by the main voluntary multicentre studies of our speciality. The high representativeness as well as the reliability of the GEVATS data constitute a fundamental point of departure for this nationwide cohort.

Prospective Analysis of the Impact of Commercialized Hybrid Closed-Loop System on Glycemic Control, Glycemic Variability, and Patient-Related Outcomes in Children and Adults: A Focus on Superiority Over Predictive Low-Glucose Suspend Technology.

Background: Automatization of insulin delivery by closed-loop systems represents a major step in type 1 diabetes management. The aim of this study was to analyze the effect of the commercialized hybrid closed-loop system, the MiniMed 670G system, on glycemic control, glycemic variability, and patient satisfaction. Methods: A prospective study, including type 1 diabetes patients consecutively starting on the 670G system in one adult and two pediatric hospitals, was performed. Baseline and 3-month visits were documented. Two weeks of data from the system were downloaded. Glycemic variability measures were calculated. Adults and adolescents completed a set of questionnaires (Gold and Clarke scores, Hypoglycemia Fear Survey, Diabetes Quality of Life [DQoL], Diabetes Treatment Satisfaction [DTS], Diabetes Distress Scale, Pittsburgh Sleep Quality Index). Results: Fifty-eight patients were included (age: 28 ± 15 years [7-63], <18 years old: 38% [n = 22], 59% [n = 34] females, previous use of SAP-PLGS [predictive low-glucose suspend]: 60% [n = 35]). HbA1c was reduced from 57 ± 10 to 53 ± 7 mmol/L (7.4% ± 0.9% to 7.0% ± 0.6%) (P < 0.001) and time in range 70-180 mg/dL was increased from 63.0% ± 11.4% to 72.7% ± 8.7% (P < 0.001). In patients with high baseline hypoglycemia risk, time <54 and <70 mg/dL were reduced from 0.9% ± 1.1% to 0.45% ± 0.7% (P = 0.021) and from 3.3% ± 2.8% to 2.1% ± 2.1% (P = 0.019), respectively. Glycemic variability measures improved. Time in auto mode was 85% ± 17%, the number of auto mode exits was 0.6 ± 0.3 per day, and the number of alarms was 8.5 ± 3.7 per day. Fear of hypoglycemia, DQoL, DTS, and diabetes distress improved, while the percentage of patients with poor sleep quality was reduced. The discontinuation rate was 3%. Conclusion: The commercialized hybrid closed-loop system improves glycemic control and glycemic variability in children and adults, reducing the burden of living with type 1 diabetes.

Prognostic assessment of valvular surgery in active infective endocarditis: multicentric nationwide validation of a new score developed from a meta-analysis.

OBJECTIVES: Several risk prediction models have been developed to estimate the risk of mortality after valve surgery for active infective endocarditis (IE), but few external validations have been conducted to assess their accuracy. We previously developed a systematic review and meta-analysis of the impact of IE-specific factors for the in-hospital mortality rate after IE valve surgery, whose obtained pooled estimations were the basis for the development of a new score (APORTEI). The aim of the present study was to assess its prognostic accuracy in a nationwide cohort. METHODS: We analysed the prognostic utility of the APORTEI score using patient-level data from a multicentric national cohort. Patients who underwent surgery for active IE between 2008 and 2018 were included. Discrimination was evaluated using the area under the receiver operating characteristic curve, and the calibration was assessed using the calibration slope and the Hosmer-Lemeshow test. Agreement between the APORTEI and the EuroSCORE I was also analysed by Lin's concordance correlation coefficient (CCC), the Bland-Altman agreement analysis and a scatterplot graph. RESULTS: The 11 variables that comprised the APORTEI score were analysed in the sample. The APORTEI score was calculated in 1338 patients. The overall observed surgical mortality rate was 25.56%. The score demonstrated adequate discrimination (area under the receiver operating characteristic curve = 0.75; 95% confidence interval 0.72-0.77) and calibration (calibration slope = 1.03; Hosmer-Lemeshow test P = 0.389). We found a lack of agreement between the APORTEI and EuroSCORE I (concordance correlation coefficient = 0.55). CONCLUSIONS: The APORTEI score, developed from a systematic review and meta-analysis, showed an adequate estimation of the risk of mortality after IE valve surgery in a nationwide cohort.

New uses and formulations of glucagon for hypoglycaemia.

Hypoglycaemia is the more frequent complication of insulin therapy and the main barrier to tight glycaemic control. Injectable glucagon and oral intake of carbohydrates are the recommended treatments for severe and non-severe hypoglycaemia episodes, respectively. Nasal glucagon is currently being developed as a ready-to-use device, to simplify severe hypoglycaemia rescue. Stable forms of liquid glucagon could open the field for different approaches for mild to moderate hypoglycaemia treatment, such as mini-doses of glucagon or continuous subcutaneous glucagon infusion as a part of dual-hormone closed-loop systems. Pharmaceutical companies are developing stable forms of native glucagon or glucagon analogues for that purpose.

Survey of Crimean-Congo Hemorrhagic Fever Enzootic Focus, Spain, 2011-2015.

During 2011-2015, we conducted a Crimean-Congo hemorrhagic fever virus (CCHFV) survey in captured ticks that were feeding mainly on wild and domestic ungulates in Spain, where presence of this virus had been reported previously. We detected CCHFV RNA in Hyalomma lusitanicum and H. marginatum ticks for 3 of the 5 years. The rate of infected ticks was 2.78% (44/1,579), which was similar to those for other countries in Europe with endemic foci for CCHFV (Kosovo, Bulgaria, and Albania). These data confirm the established spread of CCHFV into western Europe. Phylogenetic study of the small RNA segment showed Africa-3 clade as the only genotype identified, although we observed cocirculation of genetic variants during 2011 and 2015. We could not rule out genetic reassortments because of lack of sequence data for the medium and large RNA segments of the virus genome.

Evaluation of Markov Models with Discontinuities.

Background. Several methods, such as the half-cycle correction and the life-table method, were developed to attenuate the error introduced in Markov models by the discretization of time. Elbasha and Chhatwal have proposed alternative "corrections" based on numerical integration techniques. They present an example whose results suggest that the trapezoidal rule, which is equivalent to the half-cycle correction, is not as accurate as Simpson's 1/3 and 3/8 rules. However, they did not take into consideration the impact of discontinuities. Objective. To propose a method for evaluating Markov models with discontinuities. Design. Applying the trapezoidal rule, we derive a method that consists of adjusting the model by setting the cost at each point of discontinuity to the mean of the left and right limits of the cost function. We then take from the literature a model with a cycle length of 1 year and a discontinuity on the cost function and compare our method with other "corrections" using as the gold standard an equivalent model with a cycle length of 1 day. Results. As expected, for this model, the life-table method is more accurate than assuming that transitions occur at the beginning or the end of cycles. The application of numerical integration techniques without taking into account the discontinuity causes large errors. The model with averaged cost values yields very small errors, especially for the trapezoidal and the 1/3 Simpson rules. Conclusion. In the case of discontinuities, we recommend applying the trapezoidal rule on an averaged model because this method has a mathematical justification, and in our empirical evaluation, it was more accurate than the sophisticated 3/8 Simpson rule.