Effects of cardiac rehabilitation in patients with ventricular assist devices: a scoping review.

INTRODUCTION: Ventricular assist devices represent a treatment option for patients with advanced heart failure, offering control over various haemodynamic variables. Similarly, the prescription of exercise within a cardiac rehabilitation programme for heart failure patients is recommended to reduce symptoms, and hospitalisations, improve cardiorespiratory fitness, and increase exercise tolerance. Therefore, exercise prescription can impact those with ventricular assist devices. Given the limited evidence on exercise-based cardiac rehabilitation programmes for this population, this review aims to describe the most commonly used strategies and their health benefits when physical exercise is included in a cardiac rehabilitation programme for patients with ventricular assist devices. MATERIALS AND METHODS: An exploratory review was conducted through searches in the databases: PubMed, SCOPUS, PeDro, and ScienceDirect. The search was limited to studies published between 2013 and 2023. Filters were applied independently by title, abstract, and full text. The included articles were analysed based on the description of the types of cardiac rehabilitation strategies used in patients with ventricular assist devices. RESULTS: Seven articles were included. Each programme employed a cardiopulmonary exercise test before prescribing physical exercise. The most commonly used strategy was aerobic exercise, predominantly high-intensity interval training (HIIT) with intensities close to 90% of peak VO2, followed by continuous moderate-intensity exercise. Limb strength exercises were included in three programmes. CONCLUSIONS: The analysed literature suggests that cardiac rehabilitation in patients with ventricular assist devices is safe and can provide benefits in cardiorespiratory fitness and exercise tolerance. High-intensity interval training is identified as an appropriate strategy for achieving results, offering short-term improvements.

Medicina regenerativa de cartílago: efecto del tratamiento con ácido hialurónico reticulado bifásico en lesiones osteocondrales / Regenerative medicine: effect of treatment with biphasic cross-linked hyaluronic acid in osteochondral lesions

Objetivo: Evaluar si el tratamiento con ácido hialurónico reticulado bifásico de lesiones osteocondrales promovería la regeneración del tejido cartilaginoso, favoreciendo así la reparación de la lesión. Materiales y métodos: Quince conejos hembra adultos fueron divididos aleatoriamente en tres grupos: grupo 1, de control; grupo 2 y grupo 3, sometidos a una estrategia quirúrgica de lesión osteocondral en la rodilla derecha (4 mm de diámetro, 5 mm de profundidad), el grupo 3 recibió tratamiento con 0,2 ml de ácido hialurónico por vía intrarticular después de la cirugía. Se realizaron controles clínicos, bioquímicos, histopatológicos y estudios por imágenes. Resultados: Se detectaron menos casos de dolor a la palpación en el grupo 3 que en el grupo 2 a partir de los 45 días. En la resonancia magnética, casi todas las muestras del grupo 3 tenían signos de regeneración del tejido cartilaginoso en el sitio de la lesión, sin edema óseo, ni derrame articular significativo. Los estudios histopatológicos de las muestras del grupo 3 indicaron un aumento de la matriz extracelular propia de tejido cartilaginoso, comparada con la del grupo 2, con hipercelularidad, dada por condrocitos, los que formaban grupos isogénicos axiales y coronales. Conclusiones: Este estudio brinda evidencias de que el tratamiento con ácido hialurónico reticulado bifásico en unidades experimentales de conejos con lesión osteocondral no tuvieron dolor en etapas tempranas después de la lesión, a diferencia de las unidades intervenidas y sin dicho tratamiento. A su vez, los estudios por imágenes e histopatológico mostraron la reparación del tejido dañado.

Objective: To demonstrate whether treatment with biphasic cross-linked hyaluronic acid in osteochondral lesions promotes the regeneration of cartilage tissue. Materials and methods: Fifteen adult female rabbits were randomly assigned to three groups. G1 was the control group, whereas G2 and G3 underwent surgery to treat an osteochondral injury in the right knee (4mm diameter, 5mm depth). G3 received treatment with 0.2 ml of hyaluronic acid intrarticularly after surgery. Clinical, biochemical, histopathological controls and imaging studies were performed. Results:Clinically, G3 exhibited less pain on palpation than G2 after 45 days. In G3, almost all samples showed evidence of cartilage tissue regeneration at the injury site, with neither bone edema or considerable joint effusion detected on MRI. The histological tests of G3 samples revealed an increase in the extracellular matrix of cartilaginous tissue when compared to G2, with hypercellularity caused by chondrocytes that formed axial and coronal isogenic groups. Conclusions: This study provides evidence that treatment with biphasic cross-linked hyaluronic acid in experimental units of rabbits with osteochondral injuries did not cause pain in the early stages of the injury. In turn, imaging and histopathological studies revealed that the injured tissue had been repaired.

Different Ventricular Fibrillation Types in Low-Dimensional Latent Spaces.

The causes of ventricular fibrillation (VF) are not yet elucidated, and it has been proposed that different mechanisms might exist. Moreover, conventional analysis methods do not seem to provide time or frequency domain features that allow for recognition of different VF patterns in electrode-recorded biopotentials. The present work aims to determine whether low-dimensional latent spaces could exhibit discriminative features for different mechanisms or conditions during VF episodes. For this purpose, manifold learning using autoencoder neural networks was analyzed based on surface ECG recordings. The recordings covered the onset of the VF episode as well as the next 6 min, and comprised an experimental database based on an animal model with five situations, including control, drug intervention (amiodarone, diltiazem, and flecainide), and autonomic nervous system blockade. The results show that latent spaces from unsupervised and supervised learning schemes yielded moderate though quite noticeable separability among the different types of VF according to their type or intervention. In particular, unsupervised schemes reached a multi-class classification accuracy of 66%, while supervised schemes improved the separability of the generated latent spaces, providing a classification accuracy of up to 74%. Thus, we conclude that manifold learning schemes can provide a valuable tool for studying different types of VF while working in low-dimensional latent spaces, as the machine-learning generated features exhibit separability among different VF types. This study confirms that latent variables are better VF descriptors than conventional time or domain features, making this technique useful in current VF research on elucidation of the underlying VF mechanisms.

Prognosis patients with COVID-19 using deep learning.

BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensive biomarkers could be impossible for many low budget hospitals. Timely identification of the risk of mortality of COVID-19 patients (RMCPs) is essential to improve hospitals' management systems and resource allocation standards. METHODS: For the mortality risk prediction, this research work proposes a COVID-19 mortality risk calculator based on a deep learning (DL) model and based on a dataset provided by the HM Hospitals Madrid, Spain. A pre-processing strategy for unbalanced classes and feature selection is proposed. To evaluate the proposed methods, an over-sampling Synthetic Minority TEchnique (SMOTE) and data imputation approaches are introduced which is based on the K-nearest neighbour. RESULTS: A total of 1,503 seriously ill COVID-19 patients having a median age of 70 years old are comprised in the research work, with 927 (61.7%) males and 576 (38.3%) females. A total of 48 features are considered to evaluate the proposed method, and the following results are achieved. It includes the following values i.e., area under the curve (AUC) 0.93, F2 score 0.93, recall 1.00, accuracy, 0.95, precision 0.91, specificity 0.9279 and maximum probability of correct decision (MPCD) 0.93. CONCLUSION: The results show that the proposed method is significantly best for the mortality risk prediction of patients with COVID-19 infection. The MPCD score shows that the proposed DL outperforms on every dataset when evaluating even with an over-sampling technique. The benefits of the data imputation algorithm for unavailable biomarker data are also evaluated. Based on the results, the proposed scheme could be an appropriate tool for critically ill Covid-19 patients to assess the risk of mortality and prognosis.

Automatic ladybird beetle detection using deep-learning models.

Fast and accurate taxonomic identification of invasive trans-located ladybird beetle species is essential to prevent significant impacts on biological communities, ecosystem functions, and agricultural business economics. Therefore, in this work we propose a two-step automatic detector for ladybird beetles in random environment images as the first stage towards an automated classification system. First, an image processing module composed of a saliency map representation, simple linear iterative clustering superpixels segmentation, and active contour methods allowed us to generate bounding boxes with possible ladybird beetles locations within an image. Subsequently, a deep convolutional neural network-based classifier selects only the bounding boxes with ladybird beetles as the final output. This method was validated on a 2, 300 ladybird beetle image data set from Ecuador and Colombia obtained from the iNaturalist project. The proposed approach achieved an accuracy score of 92% and an area under the receiver operating characteristic curve of 0.977 for the bounding box generation and classification tasks. These successful results enable the proposed detector as a valuable tool for helping specialists in the ladybird beetle detection problem.

Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value.

Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.

An approach to automatic classification of Culicoides species by learning the wing morphology.

Fast and accurate identification of biting midges is crucial in the study of Culicoides-borne diseases. In this work, we propose a two-stage method for automatically analyzing Culicoides (Diptera: Ceratopogonidae) species. First, an image preprocessing task composed of median and Wiener filters followed by equalization and morphological operations is used to improve the quality of the wing image in order to allow an adequate segmentation of particles of interest. Then, the segmentation of the zones of interest inside the biting midge wing is made using the watershed transform. The proposed method is able to produce optimal feature vectors that help to identify Culicoides species. A database containing wing images of C. obsoletus, C. pusillus, C. foxi, and C. insignis species was used to test its performance. Feature relevance analysis indicated that the mean of hydraulic radius and eccentricity were relevant for the decision boundary between C. obsoletus and C. pusillus species. In contrast, the number of particles and the mean of the hydraulic radius was relevant for deciding between C. foxi and C. insignis species. Meanwhile, for distinguishing among the four species, the number of particles and zones, and the mean of circularity were the most relevant features. The linear discriminant analysis classifier was the best model for the three experimental classification scenarios previously described, achieving averaged areas under the receiver operating characteristic curve of 0.98, 0.90, and 0.96, respectively.

Spectral Analysis and Mutual Information Estimation of Left and Right Intracardiac Electrograms during Ventricular Fibrillation.

Ventricular fibrillation (VF) signals are characterized by highly volatile and erratic electrical impulses, the analysis of which is difficult given the complex behavior of the heart rhythms in the left (LV) and right ventricles (RV), as sometimes shown in intracardiac recorded Electrograms (EGM). However, there are few studies that analyze VF in humans according to the simultaneous behavior of heart signals in the two ventricles. The objective of this work was to perform a spectral and a non-linear analysis of the recordings of 22 patients with Congestive Heart Failure (CHF) and clinical indication for a cardiac resynchronization device, simultaneously obtained in LV and RV during induced VF in patients with a Biventricular Implantable Cardioverter Defibrillator (BICD) Contak Renewal IVTM (Boston Sci.). The Fourier Transform was used to identify the spectral content of the first six seconds of signals recorded in the RV and LV simultaneously. In addition, measurements that were based on Information Theory were scrutinized, including Entropy and Mutual Information. The results showed that in most patients the spectral envelopes of the EGM sources of RV and LV were complex, different, and with several frequency peaks. In addition, the Dominant Frequency (DF) in the LV was higher than in the RV, while the Organization Index (OI) had the opposite trend. The entropy measurements were more regular in the RV than in the LV, thus supporting the spectral findings. We can conclude that basic stochastic processing techniques should be scrutinized with caution and from basic to elaborated techniques, but they can provide us with useful information on the biosignals from both ventricles during VF.

Oportunidad en la salud digital: una respuesta al control de las demencias / Digital health services as a means to control dementia

The increase of the elderly population with a significant load of non-communicable diseases, accelerates pathological aging and increases the risk of dementia, generating a huge health, social and economic cost for any country. Dementia does not have an effective treatment yet, therefore, the focus must remain on prevention and early diagnosis. The early stages of dementia are known as mild cognitive impairment; at this stage is still possible to mitigate the progression of the disease, however, health systems worldwide face difficulties to provide universal access to health services, due to a lack of specialists and geographical distances, interfering with the access to healthcare centers. In this scenario, WHO urged countries to implement strategies to democratize and to expand the reach of health institutions. In this document, we briefly review the global and local situation of dementias and discuss some attempts to control their progression by using revolutionary digital tools. We believe the focus should be on the population that is just beginning to show cognitive impairment.

[Digital health services as a means to control dementia]. / Oportunidad en la salud digital: una respuesta al control de las demencias.

The increase of the elderly population with a significant load of non-communicable diseases, accelerates pathological aging and increases the risk of dementia, generating a huge health, social and economic cost for any country. Dementia does not have an effective treatment yet, therefore, the focus must remain on prevention and early diagnosis. The early stages of dementia are known as mild cognitive impairment; at this stage is still possible to mitigate the progression of the disease, however, health systems worldwide face difficulties to provide universal access to health services, due to a lack of specialists and geographical distances, interfering with the access to healthcare centers. In this scenario, WHO urged countries to implement strategies to democratize and to expand the reach of health institutions. In this document, we briefly review the global and local situation of dementias and discuss some attempts to control their progression by using revolutionary digital tools. We believe the focus should be on the population that is just beginning to show cognitive impairment.

Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP -hard by Caprara ( 1997 ). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

Formación, investigación, educación y sociedad como parte de las buenas prácticas desde la internacionalización universitaria / Training, research, education and society as part of good practices from university internationalization

En la actualidad, es creciente el establecimiento de relaciones entre las universidades, para contribuir al desarrollo de la educación superior en cada lugar. Esta tendencia se refleja en intercambios académicos permanentes, de forma institucionalizada; el desarrollo de proyectos de investigación de manera conjunta y la educación a distancia. En estos escenarios, se materializan programas curriculares de pregrado y postgrado, se generan convenios de colaboración y redes de cooperación(AU)

Humanismo, medicina y sociedad en el pensamiento de Fidel Castro

Estudiar el humanismo exterioriza cualquier directriz de pensamiento que ratifique la dignidad del ser humano. Sobre esta base, se puede desentrañar al humanismo de las formas más diversas. Las grandes dimensiones del pensamiento humanista de Fidel Castro Ruz, parten de la convicción de justicia social como un medio de reivindicación, sobre la base de la igualdad. El presente trabajo, demuestra a través de discursos y reflexiones de Fidel Castro Ruz, sobre la sociedad y la medicina, su visión humanista. Se emplearon métodos del nivel teórico, particularmente el histórico lógico y del nivel empírico, la revisión de fuentes documentales. Se han referenciado 22 documentos, que refieren el legado histórico de la obra de Fidel Castro. En ella se demuestra su proyección, su lucha contra las adversidades, por lograr los cambios necesarios en la sociedad cubana, contribuir al mejoramiento de los pueblos y en particular es reconocida en ella, su preocupación por la salud de todos, la ética, la solidaridad, la fidelidad, la honestidad con la historia y sobre todo, su percepción perenne en aras del bienestar de la humanidad.

Studying humanism externalizes any guideline of thought, which enphasize the dignity of the human being. On this basis, humanism can be unraveled in the most diverse ways. The great dimensions of humanist thought of Fidel Castro Ruz, start from the conviction of social justice as a means of vindication, on the basis of equality. The present study demonstrates, through speeches and reflections of Fidel Castro Ruz, about science and medicine, his humanistic vision. Methods of the theoretical level were used, particularly the logical historical one; and from the empirical level, the review of documentary sources. 22 documents have been referenced, which refer to the historical legacy of the work of Fidel Castro. Through his works we can see his projection, his struggle against adversity, to achieve the necessary changes in Cuban society, contributing to the improvement of the peoples and, in special, his concern for the health of all, ethics, solidarity, fidelity, honesty with history and above all, its perennial perception for the welfare of humanity.

Multiparametric Monitoring in Equatorian Tomato Greenhouses (I): Wireless Sensor Network Benchmarking.

In recent years, attention has been paid to wireless sensor networks (WSNs) applied to precision agriculture. However, few studies have compared the technologies of different communication standards in terms of topology and energy efficiency. This paper presents the design and implementation of the hardware and software of three WSNs with different technologies and topologies of wireless communication for tomato greenhouses in the Andean region of Ecuador, as well as the comparative study of the performance of each of them. Two companion papers describe the study of the dynamics of the energy consumption and of the monitored variables. Three WSNs were deployed, two of them with the IEEE 802.15.4 standard with star and mesh topologies (ZigBee and DigiMesh, respectively), and a third with the IEEE 802.11 standard with access point topology (WiFi). The measured variables were selected after investigation of the climatic conditions required for efficient tomato growth. The measurements for each variable could be displayed in real time using either a laboratory virtual instrument engineering workbench (LabVIEWTM) interface or an Android mobile application. The comparative study of the three networks made evident that the configuration of the DigiMesh network is the most complex for adding new nodes, due to its mesh topology. However, DigiMesh maintains the bit rate and prevents data loss by the location of the nodes as a function of crop height. It has been also shown that the WiFi network has better stability with larger precision in its measurements.

Multiparametric Monitoring in Equatorian Tomato Greenhouses (II): Energy Consumption Dynamics.

Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes.

Multiparametric Monitoring in Equatorian Tomato Greenhouses (III): Environmental Measurement Dynamics.

World population growth currently brings unequal access to food, whereas crop yields are not increasing at a similar rate, so that future food demand could be unmet. Many recent research works address the use of optimization techniques and technological resources on precision agriculture, especially in large demand crops, including climatic variables monitoring using wireless sensor networks (WSNs). However, few studies have focused on analyzing the dynamics of the environmental measurement properties in greenhouses. In the two companion papers, we describe the design and implementation of three WSNs with different technologies and topologies further scrutinizing their comparative performance, and a detailed analysis of their energy consumption dynamics is also presented, both considering tomato greenhouses in the Andean region of Ecuador. The three WSNs use ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The present study provides a systematic and detailed analysis of the environmental measurement dynamics from multiparametric monitoring in Ecuadorian tomato greenhouses. A set of monitored variables (including CO2, air temperature, and wind direction, among others) are first analyzed in terms of their intrinsic variability and their short-term (circadian) rhythmometric behavior. Then, their cross-information is scrutinized in terms of scatter representations and mutual information analysis. Based on Bland⁻Altman diagrams, good quality rhythmometric models were obtained at high-rate sampling signals during four days when using moderate regularization and preprocessing filtering with 100-coefficient order. Accordingly, and especially for the adjustment of fast transition variables, it is appropriate to use high sampling rates and then to filter the signal to discriminate against false peaks and noise. In addition, for variables with similar behavior, a longer period of data acquisition is required for the adequate processing, which makes more precise the long-term modeling of the environmental signals.

Force Trends and Pulsatility for Catheter Contact Identification in Intracardiac Electrograms during Arrhythmia Ablation.

The intracardiac electrical activation maps are commonly used as a guide in the ablation of cardiac arrhythmias. The use of catheters with force sensors has been proposed in order to know if the electrode is in contact with the tissue during the registration of intracardiac electrograms (EGM). Although threshold criteria on force signals are often used to determine the catheter contact, this may be a limited criterion due to the complexity of the heart dynamics and cardiac vorticity. The present paper is devoted to determining the criteria and force signal profiles that guarantee the contact of the electrode with the tissue. In this study, we analyzed 1391 force signals and their associated EGM recorded during 2 and 8 s, respectively, in 17 patients (82 ± 60 points per patient). We aimed to establish a contact pattern by first visually examining and classifying the signals, according to their likely-contact joint profile and following the suggestions from experts in the doubtful cases. First, we used Principal Component Analysis to scrutinize the force signal dynamics by analyzing the main eigen-directions, first globally and then grouped according to the certainty of their tissue-catheter contact. Second, we used two different linear classifiers (Fisher discriminant and support vector machines) to identify the most relevant components of the previous signal models. We obtained three main types of eigenvectors, namely, pulsatile relevant, non-pulsatile relevant, and irrelevant components. The classifiers reached a moderate to sufficient discrimination capacity (areas under the curve between 0.84 and 0.95 depending on the contact certainty and on the classifier), which allowed us to analyze the relevant properties in the force signals. We conclude that the catheter-tissue contact profiles in force recordings are complex and do not depend only on the signal intensity being above a threshold at a single time instant, but also on time pulsatility and trends. These findings pave the way towards a subsystem which can be included in current intracardiac navigation systems assisted by force contact sensors, and it can provide the clinician with an estimate of the reliability on the tissue-catheter contact in the point-by-point EGM acquisition procedure.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Rotura del tríceps braquial derecho en un atleta de béisbol. Presentación de un caso / Rupture of the right brachial triceps in a baseball athlete. A case report

Introducción: la rotura del tendón distal del tríceps es una lesión muy infrecuente; representa apenas 0,8 por ciento de todas las lesiones tendinosas. Es frecuente en hombres deportistas, debido probablemente al régimen de entrenamiento. La causa de la lesión es usualmente una caída con la mano en extensión; al estar contraído el tríceps, la fuerza de desaceleración en el brazo ocasiona la rotura.Objetivo: presentar un caso de rotura del tríceps braquial derecho en un atleta de béisbol.Presentación del caso: paciente masculino de 34 años de edad, atleta de béisbol; al capturar un lanzamiento apoyó su mano izquierda y sintió un intenso dolor en la cara posterior del codo izquierdo, lo que le imposibilitó continuar el juego. En el examen físico se constató el signo del hachazo en el tendón distal del tríceps, con aumento de volumen e imposibilidad para extender el codo; la ecografía de partes blandas mostró signos de rotura total del tendón y se orientó tratamiento quirúrgico. En la operación se confirmó la desinserción en el olécranon; se realizó sutura transósea, se inmovilizó el codo a aproximadamente 60 grados de flexión durante seis semanas y posteriormente el paciente comenzó la rehabilitación.Discusión: el paciente no presentó antecedentes patológicos personales ni de infiltraciones con esteroides alrededor del codo; el mecanismo de producción de la lesión fue indirecto, y consecuencia de la práctica deportiva.Conclusiones: la reparación primaria temprana de la lesión es importante porque, independientemente de la técnica quirúrgica empleada, evita recurrir posteriormente a las técnicas de reconstrucción(AU)

Introduction: rupture of the distal triceps tendon is a very uncommon injury; it represents only 0,8 percent of all tendon injuries. It is frequent in athletic men, probably due to their training regimen. The cause of the injury is usually a fall with the hand in extension; when the triceps is contracted, the deceleration force on the arm causes the rupture.Objective: to present a case of right brachial triceps rupture in a baseball athlete.Case presentation: 34-year-old male patient, baseball athlete; when capturing a pitch supported his left hand and felt an intense pain in the back side of the left elbow, which prevented him to continue the game. On physical examination, hatchet strike defect in the distal tendon of the triceps was found, with an increase in volume and impossibility to extend the elbow; ultrasound of soft tissues showed signs of total rupture of the tendon and surgical treatment was oriented. In the operation the deinsertion in the olecranon was confirmed; transosseous suture was performed, the elbow was immobilized at approximately 60 degrees of flexion for six weeks, and then the patient began rehabilitation.Discussion: the patient did not present personal pathological antecedents or infiltrations with steroids around the elbow; the mechanism of production of the injury was indirect, and a consequence of the sport practice.Conclusions: early primary repair of the lesion is important because, regardless of the surgical technique used, it avoids recurring reconstruction techniques(AU)

[Clinical features of patients with influenza-like illness who went to a third level center in the winter of 2013-2014]. / Características clínicas de pacientes que acudieron por enfermedad tipo influenza a un centro de tercer nivel en el invierno de 2013-2014.

BACKGROUND: Between October 2013 and April 2014, the Centers for Disease Control and Prevention reported a high incidence of AH1N1 influenza cases. Not all suspicious cases of influenza are confirmed; however, all patients need treatment and generate additional costs to the institutions. Our objective was to describe the characteristics of the patients treated for influenza suspicion at Hospital de Especialidades in Centro Médico Nacional Siglo XXI during a new epidemic. METHODS: Cross-sectional study of all cases admitted at the Emergency Service (of the aforementioned hospital) for influenza-like illness, defined according to current guidelines. Based on these guidelines, we analyzed the risk factors that may have increased the severity of the infection. RESULTS: We registered a total of 109 patients with a mean age of 44 years, 78 % were under 60 years of age, 62 % were women, 75 % had at least one comorbidity, such as obesity (26 %) or hypertension (27 %). Only 65 patients had results from a confirmatory test, 33.8 % had positive diagnosis, and 21 % of them eventually died. CONCLUSIONS: The frequency of confirmed cases for influenza infection is low. The risk factors associated with complications and increased mortality are hypertension, leukocytosis and clinical presentation of severe acute respiratory syndrome.

Introducción: el Centro para el Control y Prevención de Enfermedades (CDC, por sus siglas en inglés) registró, entre octubre de 2013 y abril de 2014, el pico más alto de casos relacionados con la influenza AH1N1. No todos los casos sospechosos de influenza resultan positivos, pero todos les generan costos a las instituciones. Nuestro objetivo fue describir las características de la población que acude con sospecha de influenza al Hospital de Especialidades del Centro Médico Nacional Siglo XXI durante una nueva epidemia. Métodos: estudio transversal de casos admitidos al servicio de Urgencias del hospital mencionado por sospecha de influenza de acuerdo con las guías de práctica clínica. Con base en estas se analizaron los factores asociados a la severidad de la infección. Resultados: se registraron 109 pacientes con promedio de 44 años edad; el 78 % de ellos tenía menos de 60 años; el 62 % fueron mujeres; 75 % tenía por lo menos un factor de riesgo como obesidad (26 %) o hipertensión (27 %). Solo 65 pacientes tuvieron prueba confirmatoria, 33.8 % fueron diagnóstico positivo y 21 % de ellos fallecieron. Conclusiones: la frecuencia de casos confirmados de influenza es baja. Los factores asociados a mortalidad en los casos confirmados son la presencia de hipertensión, de leucocitosis y la presentación clínica de insuficiencia respiratoria aguda grave (IRAG).