Effect of High Altitude on the Survival of COVID-19 Patients in Intensive Care Unit: A Cohort Study.

Purpose: The effect of high altitude ( ≥ 1500 m) and its potential association with mortality by COVID-19 remains controversial. We assessed the effect of high altitude on the survival/discharge of COVID-19 patients requiring intensive care unit (ICU) admission for mechanical ventilation compared to individuals treated at sea level. Methods: A retrospective cohort multi-center study of consecutive adults patients with a positive RT-PCR test for COVID-19 who were mechanically ventilated between March and November 2020. Data were collected from two sea-level hospitals and four high-altitude hospitals in Ecuador. The primary outcome was ICU and hospital survival/discharge. Survival analysis was conducted using semi-parametric Cox proportional hazards models. Results: Of the study population (n = 670), 35.2% were female with a mean age of 58.3 ± 12.6 years. On admission, high-altitude patients were more likely to be younger (57.2 vs. 60.5 years old), presented with less comorbidities such as hypertension (25.9% vs. 54.9% with p-value <.001) and diabetes mellitus (20.5% vs. 37.2% with p-value <.001), less probability of having a capillary refill time > 3 sec (13.7% vs. 30.1%, p-value <.001), and less severity-of-illness condition (APACHE II score, 17.5 ± 8.1 vs. 20 ± 8.2, p < .01). After adjusting for key confounders high altitude is associated with significant higher probabilities of ICU survival/discharge (HR: 1.74 [95% CI: 1.46-2.08]) and hospital survival/discharge (HR: 1.35 [95% CI: 1.18-1.55]) than patients treated at sea level. Conclusions: Patients treated at high altitude at any time point during the study period were 74% more likely to experience ICU survival/discharge and 35% more likely to experience hospital survival/discharge than to the sea-level group. Possible reasons for these findings are genetic and physiological adaptations due to exposure to chronic hypoxia.

A Comparative Study of Post-Quantum Cryptosystems for Internet-of-Things Applications.

The existence of quantum computers and Shor's algorithm poses an imminent threat to classical public-key cryptosystems. These cryptosystems are currently used for the exchange of keys between servers and clients over the Internet. The Internet of Things (IoT) is the next step in the evolution of the Internet, and it involves the connection of millions of low-powered and resource-constrained devices to the network. Because quantum computers are becoming more capable, the creation of a new cryptographic standard that cannot be compromised by them is indispensable. There are several current proposals of quantum-resistant or post-quantum algorithms that are being considered for future standards. Given that the IoT is increasing in popularity, and given its resource-constrained nature, it is worth adapting those new standards to IoT devices. In this work, we study some post-quantum cryptosystems that could be suitable for IoT devices, adapting them to work with current cryptography and communication software, and conduct a performance measurement on them, obtaining guidelines for selecting the best for different applications in resource-constrained hardware. Our results show that many of these algorithms can be efficiently executed in current IoT hardware, providing adequate protection from the attacks that quantum computers will eventually be capable of.

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks.

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, researchers have incorporated novelty modules in robots to develop automatic exploration and inspection tasks. The visual sensor is one of the preferred sensors to perform this task. However, there exist problems as illumination changes, occlusion, and scale, among others. Besides, novelty detectors vary their performance depending on the specific application scenario. In this work, we propose a visual novelty detection framework for specific exploration and inspection tasks based on evolved novelty detectors. The system uses deep features to represent the visual information captured by the robots and applies a global optimization technique to design novelty detectors for specific robotics applications. We verified the performance of the proposed system against well-established state-of-the-art methods in a challenging scenario. This scenario was an outdoor environment covering typical problems in computer vision such as illumination changes, occlusion, and geometric transformations. The proposed framework presented high-novelty detection accuracy with competitive or even better results than the baseline methods.

Obstacle Recognition using Computer Vision and Convolutional Neural Networks for Powered Prosthetic Leg Applications.

In this work we combine computer vision and a machine learning algorithm, Convolutional Neural Networks (CNNs), to identify obstacles that powered prosthetic leg users might encounter during walking. Our motivation is that powered prosthetic legs could react in synchronicity with their users by recognizing and anticipating the terrain in front of them. We focus on identifying stairs and doors that are within the visual field of a person. To achieve this, we used a compact CNN architecture to optimize image processing for real-time applications. We built and tested a wearable system prototype that included a camera mounted on a pair of glasses and a single-board computer. The prototype was used by able-bodied users to collect and label obstacle and non-obstacle videos, which were used later to train the CNN. In validation, the system was able to recognize around 90% of obstacles across different indoor and outdoor scenarios. The accuracy achieved and the practicality of the prototype shows the potential of computer vision and machine learning in the field of powered prosthetic legs.

Sensor Compromise Detection in Multiple-Target Tracking Systems.

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques.

Infecciones nosocomiales en pacientes sometidos a tratamiento quirúrgico en el Servicio de Cirugía Cardiotorácica del Hospital Carlos Andrade Marín / Nosocomial infections in patients who undergo surgical treatment in the cardiothoracic surgery department at Carlos Andrade Marín Hospital

Introducción: Las infecciones nosocomiales de pacientes sometidos a cirugía cardiaca constituyen una complicación relevante que puede incrementar la estancia hospitalaria y la morbimortalidad. En el presente estudio identificamos diferentes factores de riesgo prequirúrgicos, quirúrgicos y postquirúrgicos que podrían tener relación con este tipo de infecciones. Materiales y métodos: Es un estudio descriptivo de pacientes que ingresaron para tratamiento quirúrgico por patologías cardiacas y pericárdicas al Servicio de Cirugía Cardiotorácica del Hospital Carlos Andrade Marín de septiembre 2014 a septiembre 2015. Resultados: Durante el período considerado Estudiamos 291 pacientes que ingresaron para resolución quirúrgica de patología cardiaca; 43 (14.7%) desarrollaron infecciones nosocomiales; 22 mujeres y 21 hombres. La edad promedio (±DE) fue 56.8 (±12.8) años. Los principales tipos de infección nosocomial fueron respiratorias, urinarias, infección de sitio quirúrgico superficial y profunda, del mediastino y saco piopericardio. Discusión: Alrededor el 43% de las infecciones en nuestros pacientes fueron causadas por bacilos gramnegativos, ello sugiere la necesidad de dar una cobertura antibiótica empírica amplia contra estos microorganismos hasta tener resultados definitivos de bacteriología.

Introduction: Nosocomial infections in patients who undergp cardiac surgery are significant complication that increase hospital stay, morbidity and mortality. In the present study, different risk factors: presurgical, surgical and post-surgical could be related to nosocomial infections as described. Methods: This is a descriptive retrospective study of patients admitted to the cardiac surgical ward at Carlos Andrade Marín Hospital in the period, September 2014 to September 2015. Results: During the period under review 291 patients were admitted for surgical resolution of heart diseases. Among them, 43 (14.7%) developed nosocomial infections. There were 22 women and 21 men, with a mean age of 56.8 (SD) (12.8). The main types of nosocomial infections were upper respiratory tract, 36%; uncomplicated lower urinary tract infection; 34.8%; superficial and deep surgical site infection, 15%; nosocomial pneumonia 7%, mediastinitis 7%; pyopericardium, 2%. Discusion: Around 43 % of infections in our patientes were caused by gram-negative bacteria, suggesting the need to use employ a broad spectrum coverage against these microorganisms until bacteriological results are known.

Topografía aterosclerótica obtenida por coronariografía prequirúrgica en pacientes intervenidos de revascularización coronaria / Atherosclerotic topography obtained by presurgical coronariography in patients undergoing coronary revascularization

El síndrome coronario es un desbalance entre demanda miocárdica y entrega coronaria usualmente causado por estenosis ateroscleróticas, la mayoría de las lesiones de ubican en la coronaria izquierda, especialmente en la descendente anterior . Los factores de riesgo cardiovascular clásicos son útiles como predictores del cuadro pero no explican la selectividad vascular izquierda sin recurrir a comprender la hemodinamia local coronaria. En este sentido, se debe tener en cuenta lo siguiente: 1) En la coronaria derecha el flujo tiende a ser constante en todo el ciclo cardiaco, en la izquierda es bifásico y el 80% se produce en diástole, el endotelio está expuesto a mayor estrés. 2) En las ramas de la coronaria izquierda, el miocardio en sístole comprime el sistema subendocárdico y provoca flujo retrógrado, los vasos epicárdicos son reservorio del flujo que asciende y aumentan su diámetro estresando su pared, en la coronaria derecha no se produce este fenómeno. 3) La vasculatura coronaria acompaña al miocardio en cada contracción por lo que es torsionada, estirada y aplanada, las ramas de la coronaria izquierda están expuestas a mayor deformación geométrica. 4) La coronaria izquierda tiene más ramifcaciones que la derecha lo que induce más turbulencia. La presentación clínica, consideraciones terapéuticas, complicaciones y pronóstico dependen de varios aspectos, entre ellos, el vaso afectado. La valoración de los factores de riesgo cardiovascular predice el desarrollo del cuadro, pero no el vaso que podría lesionarse. En nuestro medio no existe una descripción estadística amplia que haya reportado la predominancia izquierda y que permita añadir los factores hemodiná- micos estresantes de la pared coronaria al riesgo cardiovascular.

Coronary syndrome is an imbalance between myocardial demand and coronary delivery usually caused by atherosclerotic stenosis, the majority of lesions are located in the left coronary artery, especially in the anterior descending. Classic cardiovascular risk factors are useful as predictors of the picture but do not explain the left vascular selectivity without resort to understanding local coronary hemodynamics. In this sense, the following should be taken into account: 1) In the right coronary the flow tends to be constant throughout the cardiac cycle, on the left It is biphasic and 80% is produced in diastole, the endothelium is exposed to increased stress 2) In the branches of the left coronary, the myocardium in systole compresses the subendocardial system and causes retrograde flow, the epicardial vessels are reservoirs of the ascending fl ow its diameter stressing its wall, in the right coronary does not occur this phenomenon. 3) The coronary vasculature accompanies the myocardium in each contraction so it is twisted, stretched and flattened, the branches of the left coronary are exposed to greater deformation geometric 4) The left coronary has more ramifications than the right which induces more turbulence . The clinical presentation, therapeutic considerations, complications and prognosis depend on several aspects, including the affected vessel. The assessment of cardiovascular risk factors predicts the development of the condition, but not the vessel that could be injured. In our there is no broad statistical description that has reported the left predominance and that allows adding hemodynamic factors stressful mycoses of the coronary wall to cardiovascular risk