Sistema de seguimiento y control eProtect infecciones respiratorias / eProtect respiratory infection monitoring and control system

Las infecciones del tracto respiratorio (ITR) son una de las principales causas de morbilidad y mortalidad en todo el mundo, y representan el 4,4 % de las muertes en todas las edades. A nivel mundial, se han observado disminuciones en la mortalidad causada por las ITR después de la introducción de las vacunas conjugadas contra Haemophilus influenzae tipo b, tos ferina y neumocócica. Sin embargo, las ITR siguen siendo una de las principales causas de mortalidad entre los niños pequeños y los ancianos en los países de ingresos bajos y medios. Se planteó un estudio donde se aplicó un sistema de seguimiento que sirvan para monitorear la vigilancia de las infecciones respiratorias agudas (IRA) en servicios de salud, por laboratorio y en unidades centinela en Perú. Participaron 67 médicos generales o cirujanos de 8 servicios de pediatría. 1453 casos de las IRA fueron de etiología viral, identificando al virus sincitial respiratorio (63,94%), Influenza AH1N1 (16,59%); en el caso de las neumonías bacterianas se aislaron Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae y Streptococcus beta hemolyticus. Durante la última década de reforma del sistema de salud, Perú ha hecho de la construcción de su sistema de APS una prioridad. Sin embargo, el sistema se enfrenta actualmente a desafíos para proporcionar atención de alta calidad y valor a la población debido a deficiencias en varias dimensiones. El sistema de APS ayudará a responder a la transición epidemiológica actual y futura epidemia brotes de manera más eficaz(AU)

Respiratory tract infections (RTIs) are one of the leading causes of morbidity and mortality worldwide, accounting for 4.4% of deaths in all ages. Globally, declines in mortality from RTIs have been observed after the introduction of Haemophilus influenzae type b, pertussis, and pneumococcal conjugate vaccines. However, RTIs remain a leading cause of mortality among young children and the elderly in low- and middle-income countries. A study was proposed where a monitoring system was applied to monitor the surveillance of acute respiratory infections (ARI) in health services, by laboratory and in sentinel units in Peru. A total of 67 general practitioners or surgeons from 8 pediatric services participated. 1453 cases of ARI were of viral aetiology, identifying the respiratory syncytial virus (63.94%), Influenza AH1N1 (16.59%); in the case of bacterial pneumonia, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae and Streptococcus beta hemolyticus were isolated. During the last decade of health system reform, Peru has made building its PHC system a priority. However, the system currently faces challenges in providing high quality and value care to the population due to deficiencies in several dimensions. The PHC system will help respond to current epidemiological transition and future epidemic outbreaks more effectively(AU)

Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine Learning

BACKGROUND: Monitoring and control of PM(2.5) are being recognized as key to address health issues attributed to PM(2.5). Availability of low-cost PM(2.5) sensors made it possible to introduce a number of portable PM(2.5) monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scattering–based PM(2.5) monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM(2.5) sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy.METHODS: This study discussed the calibration of a low-cost PM(2.5)-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM(2.5) sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM(2.5). Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference.RESULTS: Based on the performance of ML algorithms used, regression of the output of the PMD to PM(2.5) concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 μg/m³, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol.CONCLUSIONS: Calibration of a low-cost PMD, which is based on construction of PM(2.5) sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

Technological analysis and comparison for dose monitoring and control systems of two types of linear accelerators / 中国医学装备

Objective:To analyze and compare the dose monitoring and control systems of two types of medical linear accelerator systematically from the view of mechanical and electrical engineering, and establish the method of the quality assurance of the dosimetry system and the solution in the routine maintenance.Methods: To systematically compare and analyze the system of dose monitoring and control for two types of linear accelerators (Precise Elekta and C-series of Varian Medical Systems) from twofold aspects that included machine physics and electric engineering of medical linear accelerators.Results:The monitoring system that took ionization chamber as center was established between connotation of machine physics and concrete realization of electromechanical engineering, and explained the difference and similarity between open type and sealed type of ionization chamber, and the theory that Precise series needn't be serviced by PFN.Conclusion: Based on the analysis of ionization chambers structure of medical linear accelerators on the principle of quality assurance system, proposed dosimetric testing and adjustment method, and provide reference for the establishment of quality assurance system and technical procedures of the maintenance engineering.

Application of remote visiting & tracing system in neonate department / 医疗卫生装备

Objective To develop a neonate remote visiting & tracing system with present wireless network and neonate RFID system.Methods Standard MPEG-4 images from real-time monitoring were obtained by using multilevel video monitoring system based on wireless network.Dynamic IP support to video server was realized under various kinds of network bandwidth.Result Parents at home could see their neonates in hospital through Internet network.They also could observe the whole process of the treatment.If the doctor went on errands to other city,through the web they could know the status of the infant and give suggests at any moment.Conclusion Remote visiting & tracing system in neonate department is a significant reference to hospitals of the same kind.