Factores asociados a la no-adherencia al tratamiento farmacológico antihipertensivo en pacientes de un hospital del seguro social / Factors associated with non-adherence to antihypertensive treatment in patients with social security

Introducción: La falta de adherencia a la terapia antihipertensiva contribuye directamente a que los pacientes coexistan con hipertensión, desencadenando mayor riesgo de morbilidad y mortalidad. Así, la falta de adherencia al tratamiento se convierte en una de las principales causas de hipertensión no controlada en la población. Evaluamos los factores asociados a la no-adherencia al tratamiento antihipertensivo en pacientes de cardiología de un hospital de EsSalud en San Juan de Lurigancho-Lima, durante el 2017. Material y Métodos: Estudio analítico-transversal, se incluyeron pacientes que acudieron a consultorio externo de cardiología con historia previa de hipertensión esencial y se excluyeron hipertensión secundaria por otras causas biológicas. Se utilizó el Test de Morisky-Green Morisky Medication Adherence Scale (MMAS-4) para evaluar la no-adherencia al tratamiento antihipertensivo. Resultados: De los 270 participantes de estudio, el 69% (n=185) eran adultos mayores de 65 años, 46% (n=124) varones y el 76% (n=118) tenían pareja estable. Entre los antecedentes clínicos, el 60% (n=122) reportó diagnóstico clínico de hipertensión arterial, el 30% (n=80) de diabetes mellitus tipo II y el 27% (n=73) no-adherencia al tratamiento. Los factores asociados a la no-adherencia de tratamiento fueron sexo masculino (ORa: 0,45, IC95% 0,20-1,04), trabajador independiente (ORa:3,88, IC95% 1,51-9,97), IMC mayor de 30 (ORa:0,23, IC95% 0,07-0,70). Conclusiones: en los pacientes con diagnóstico de hipertensión esencial existen factores de riesgo modificables y no modificables asociados a la no-adherencia al tratamiento. Se deben considerar estos factores para implementar estrategias de tamizaje y focalizar las intervenciones para adherir a los pacientes renuentes a su tratamiento.

Background:Lack of adherence to antihypertensive therapy contributes directly to patients coexisting with hypertension, triggering increased risk of morbidity and mortality. Thus, nonadherence to treatment becomes one of the main causes of uncontrolled hypertension in the population. We evaluated the factors associated with non-adherence to antihypertensive treatment in cardiology patients of an EsSalud hospital in San Juan de Lurigancho-Lima, during 2017. Material and Methods: Analytical-crossover study, patients attending cardiology outpatient clinic with previous history of essential hypertension were included and secondary hypertension due to other biological causes were excluded. The Morisky-Green Morisky Medication Adherence Scale (MMAS-4) was used to assess non-adherence to antihypertensive treatment. Results: Of the 270 study participants, 69% (n=185) were adults older than 65 years, 46% (n=124) were male and 76% (n=118) had a stable partner. Among the clinical history, 60% (n=122) reported clinical diagnosis of arterial hypertension, 30% (n=80) of type II diabetes mellitus and 27% (n=73) non-adherence to treatment. Factors associated with non-adherence to treatment were male sex (ORa: 0.45, 95%CI 0.20-1.04), self-employed (ORa:3.88, 95%CI 1.51-9.97), BMI greater than 30 (ORa:0.23, 95%CI 0.07-0.70). Conclusions: in patients with a diagnosis of essential hypertension there are modifiable and non-modifiable risk factors associated with non-adherence to treatment. These factors should be considered in order to implement screening strategies and target interventions to adhere to treatment in reluctant patients.

Measurement of Acceleration Response Functions with Scalable Low-Cost Devices. An Application to the Experimental Modal Analysis.

One of the most popular options in the Structural Health Monitoring field is the tracking of the modal parameters, which are estimated through the frequency response functions of the structure, usually in the form of accelerances, which are computed as the ratio between the measured accelerations and the applied forces. This requires the use of devices capable of synchronously recording accelerations at several points of the structure at high sampling rates and the subsequent computational analysis using the recorded data. To this end, this work presents and validates a new scalable acquisition system based on multiple myRIO devices and digital MEMS (Micro-Electro-Mechanical System) accelerometers, intended for modal analysis of large structures. A simple form of this system was presented by the authors in a previous work, showing that a single board with some accelerometers connected to it got to obtain high quality measurements in both time and frequency domains. Now, a larger system composed by several slave boards connected and synchronized to a master one is presented. Delays lower than 100 ns are found between the synchronised channels of the proposed system. For validation purposes, a case study is presented where the devices are deployed on a timber platform to estimate its modal properties, which are compared with the ones provided by a commercial system, based on analog accelerometers, to show that similar results are obtained at a significantly lower cost.

Feasibility of Using a MEMS Microphone Array for Pedestrian Detection in an Autonomous Emergency Braking System.

Pedestrian detection by a car is typically performed using camera, LIDAR, or RADAR-based systems. The first two systems, based on the propagation of light, do not work in foggy or poor visibility environments, and the latter are expensive and the probability associated with their ability to detect people is low. It is necessary to develop systems that are not based on light propagation, with reduced cost and with a high detection probability for pedestrians. This work presents a new sensor that satisfies these three requirements. An active sound system, with a sensor based on a 2D array of MEMS microphones, working in the 14 kHz to 21 kHz band, has been developed. The architecture of the system is based on an FPGA and a multicore processor that allow the system to operate in real time. The algorithms developed are based on a beamformer, range and lane filters, and a CFAR (Constant False Alarm Rate) detector. In this work, tests have been carried out with different people and in different ranges, calculating, in each case and globally, the Detection Probability and the False Alarm Probability of the system. The results obtained verify that the developed system allows the detection and estimation of the position of pedestrians, ensuring that a vehicle travelling at up to 50 km/h can stop and avoid a collision.

Design and Validation of a Scalable, Reconfigurable and Low-Cost Structural Health Monitoring System.

This paper presents the design, development and testing of a low-cost Structural Health Monitoring (SHM) system based on MEMS (Micro Electro-Mechanical Systems) triaxial accelerometers. A new control system composed by a myRIO platform, managed by specific LabVIEW software, has been developed. The LabVIEW software also computes the frequency response functions for the subsequent modal analysis. The proposed SHM system was validated by comparing the data measured by this set-up with a conventional SHM system based on piezoelectric accelerometers. After carrying out some validation tests, a high correlation can be appreciated in the behavior of both systems, being possible to conclude that the proposed system is sufficiently accurate and sensitive for operative purposes, apart from being significantly more affordable than the traditional one.

Feasibility of Discriminating UAV Propellers Noise from Distress Signals to Locate People in Enclosed Environments Using MEMS Microphone Arrays.

Detecting and finding people are complex tasks when visibility is reduced. This happens, for example, if a fire occurs. In these situations, heat sources and large amounts of smoke are generated. Under these circumstances, locating survivors using thermal or conventional cameras is not possible and it is necessary to use alternative techniques. The challenge of this work was to analyze if it is feasible the integration of an acoustic camera, developed at the University of Valladolid, on an unmanned aerial vehicle (UAV) to locate, by sound, people who are calling for help, in enclosed environments with reduced visibility. The acoustic array, based on MEMS (micro-electro-mechanical system) microphones, locates acoustic sources in space, and the UAV navigates autonomously by closed enclosures. This paper presents the first experimental results locating the angles of arrival of multiple sound sources, including the cries for help of a person, in an enclosed environment. The results are promising, as the system proves able to discriminate the noise generated by the propellers of the UAV, at the same time it identifies the angles of arrival of the direct sound signal and its first echoes reflected on the reflective surfaces.

Implementation of a Virtual Microphone Array to Obtain High Resolution Acoustic Images.

Using arrays with digital MEMS (Micro-Electro-Mechanical System) microphones and FPGA-based (Field Programmable Gate Array) acquisition/processing systems allows building systems with hundreds of sensors at a reduced cost. The problem arises when systems with thousands of sensors are needed. This work analyzes the implementation and performance of a virtual array with 6400 (80 × 80) MEMS microphones. This virtual array is implemented by changing the position of a physical array of 64 (8 × 8) microphones in a grid with 10 × 10 positions, using a 2D positioning system. This virtual array obtains an array spatial aperture of 1 × 1 m². Based on the SODAR (SOund Detection And Ranging) principle, the measured beampattern and the focusing capacity of the virtual array have been analyzed, since beamforming algorithms assume to be working with spherical waves, due to the large dimensions of the array in comparison with the distance between the target (a mannequin) and the array. Finally, the acoustic images of the mannequin, obtained for different frequency and range values, have been obtained, showing high angular resolutions and the possibility to identify different parts of the body of the mannequin.

Design and Evaluation of a Scalable and Reconfigurable Multi-Platform System for Acoustic Imaging.

This paper proposes a scalable and multi-platform framework for signal acquisition and processing, which allows for the generation of acoustic images using planar arrays of MEMS (Micro-Electro-Mechanical Systems) microphones with low development and deployment costs. Acoustic characterization of MEMS sensors was performed, and the beam pattern of a module, based on an 8 × 8 planar array and of several clusters of modules, was obtained. A flexible framework, formed by an FPGA, an embedded processor, a computer desktop, and a graphic processing unit, was defined. The processing times of the algorithms used to obtain the acoustic images, including signal processing and wideband beamforming via FFT, were evaluated in each subsystem of the framework. Based on this analysis, three frameworks are proposed, defined by the specific subsystems used and the algorithms shared. Finally, a set of acoustic images obtained from sound reflected from a person are presented as a case study in the field of biometric identification. These results reveal the feasibility of the proposed system.

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

Performance evaluation of a biometric system based on acoustic images.

An acoustic electronic scanning array for acquiring images from a person using a biometric application is developed. Based on pulse-echo techniques, multifrequency acoustic images are obtained for a set of positions of a person (front, front with arms outstretched, back and side). Two Uniform Linear Arrays (ULA) with 15 λ/2-equispaced sensors have been employed, using different spatial apertures in order to reduce sidelobe levels. Working frequencies have been designed on the basis of the main lobe width, the grating lobe levels and the frequency responses of people and sensors. For a case-study with 10 people, the acoustic profiles, formed by all images acquired, are evaluated and compared in a mean square error sense. Finally, system performance, using False Match Rate (FMR)/False Non-Match Rate (FNMR) parameters and the Receiver Operating Characteristic (ROC) curve, is evaluated. On the basis of the obtained results, this system could be used for biometric applications.

A configurable sensor network applied to ambient assisted living.

The rising older people population has increased the interest in ambient assisted living systems. This article presents a system for monitoring the disabled or older persons developed from an existing surveillance system. The modularity and adaptability characteristics of the system allow an easy adaptation for a different purpose. The proposed system uses a network of sensors capable of motion detection that includes fall warning, identification of persons and a configurable control system which allows its use in different scenarios.