Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital

In a typical intensive care unit of a healthcare facilities, many sensors are connected to patients to measure high frequency physiological data. Currently, measurements are registered from time to time, possibly every hour. With this data lost, we are losing many opportunities to discover new patterns in vital signs that could lead to earlier detection of pathologies. The early detection of pathologies gives physicians the ability to plan and begin treatments sooner or potentially stop the progression of a condition, possibly reducing mortality and costs. The data generated by medical equipment are a Big Data problem with near real-time restrictions for processing medical algorithms designed to predict pathologies. This type of system is known as realtime big data analytics systems. This paper analyses if proposed system architectures can be applied in the Francisco Lopez Lima Hospital (FLLH), an Argentinian hospital with relatively high financial constraints. Taking into account this limitation, we describe a possible architectural approach for the FLLH, a mix of a local computing system at FLLH and a public cloud computing platform. We believe this work may be useful to promote the research and development of such systems in intensive care units of hospitals with similar characteristics to the FLLH.Facultad de Informátic

Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital

In a typical intensive care unit of a healthcare facilities, many sensors are connected to patients to measure high frequency physiological data. Currently, measurements are registered from time to time, possibly every hour. With this data lost, we are losing many opportunities to discover new patterns in vital signs that could lead to earlier detection of pathologies. The early detection of pathologies gives physicians the ability to plan and begin treatments sooner or potentially stop the progression of a condition, possibly reducing mortality and costs. The data generated by medical equipment are a Big Data problem with near real-time restrictions for processing medical algorithms designed to predict pathologies. This type of system is known as realtime big data analytics systems. This paper analyses if proposed system architectures can be applied in the Francisco Lopez Lima Hospital (FLLH), an Argentinian hospital with relatively high financial constraints. Taking into account this limitation, we describe a possible architectural approach for the FLLH, a mix of a local computing system at FLLH and a public cloud computing platform. We believe this work may be useful to promote the research and development of such systems in intensive care units of hospitals with similar characteristics to the FLLH.Facultad de Informátic

Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital

In a typical intensive care unit of a healthcare facilities, many sensors are connected to patients to measure high frequency physiological data. Currently, measurements are registered from time to time, possibly every hour. With this data lost, we are losing many opportunities to discover new patterns in vital signs that could lead to earlier detection of pathologies. The early detection of pathologies gives physicians the ability to plan and begin treatments sooner or potentially stop the progression of a condition, possibly reducing mortality and costs. The data generated by medical equipment are a Big Data problem with near real-time restrictions for processing medical algorithms designed to predict pathologies. This type of system is known as realtime big data analytics systems. This paper analyses if proposed system architectures can be applied in the Francisco Lopez Lima Hospital (FLLH), an Argentinian hospital with relatively high financial constraints. Taking into account this limitation, we describe a possible architectural approach for the FLLH, a mix of a local computing system at FLLH and a public cloud computing platform. We believe this work may be useful to promote the research and development of such systems in intensive care units of hospitals with similar characteristics to the FLLH.Facultad de Informátic

Trastornos del desarrollo en niños y adolescentes de la región de Los Ríos, Valdivia, Chile, 2006-2008

ResumenObjetivoEstudiar los posibles hallazgos de factores asociados antenatales, perinatales o posnatales, tanto de la madre como del niño, que tengan relevancia significativa en la aparición de trastornos del desarrollo.Pacientes y métodoSe creó una base de datos de todas las fichas clínicas de los pacientes con patología del desarrollo F80 a F90 CIE10 ingresados a la Unidad de Psiquiatría Infantil del Hospital Regional de Valdivia entre agosto de 2006 y diciembre de 2008. Total: 493 pacientes (48,7% del total de consultantes); grupo control de 32 niños sanos de consultorios de la ciudad. Se aplicó método estadístico odds ratio (95% confianza) para el análisis de algunas variables.ResultadosDestacan como factores de riesgo para desarrollar patología del desarrollo (p<0,005, 25% de frecuencia en población consultante): la prematurez, ser de sexo masculino, tener una madre con baja escolaridad, hospitalizaciones tempranas y enfermedades médicas antes de los 3 años (todos con odds ratio significativa). Además tener una madre psiquiátrica aumenta el doble el riesgo de desarrollar trastorno del desarrollo.ConclusiónSe requiere un trabajo colaborativo interdisciplinario entre neonatólogos, obstetras, psiquiatras infantiles y la atención primaria para detectar precozmente niños en riesgo.AbstractObjectivesTo study possible findings of factors in the antenatal, perinatal or postnatal period, in the mother or the child that may have an influence on the appearance of a developmental disorder.Patients and methodA Data Base of Clinical Histories from every patient with a developmental disorder (F80-F90 ICD10) was created. The patients attended the Child Psychiatric Unit at Hospital Regional of Valdivia, Chile, from August 2006 to December 2008. Total: 493 patientes (48.7% of the total of patients consulting); Control group: 32 healthy patients. Statistical method: odds ratio (95% confidence).ResultsThe main risk factors for developing a developmental disorder (P<.005, 25% frequency in the consulting population) are: prematurity, male sex, mother with low education, early hospitalizations, and medical illnesses (all with a significant odds ratio). Also, having a mother with psychiatric illness doubles the risk of having a developmental disorder.ConclusionIt requires an interdisciplinary collaborative work between neonatologists, obstetricians, child psychiatrists and the primary care to detect early children at risk

Aplicaciones de cómputo intensivo con impacto social

Los avances tecnológicos de los sistemas de cómputo paralelo y distribuido permiten el desarrollo de aplicaciones antes impensadas. Nuestra investigación se centra en desarrollar metodologías, modelos y soluciones informáticas para colaborar en la resolución de problemas que tengan una alta demanda computacional e impacto social. Hemos definido tres ejes de investigación: aplicaciones para la salud, aplicaciones de informática forense, y consumo energético de los sistemas de cómputo paralelo. Estas líneas de investigación se desarrollan en colaboración con una universidad nacionales y otra del extranjero, un hospital público, y un gabinete provincial de informática forense.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informátic

Aplicaciones de cómputo intensivo con impacto social

Los avances tecnológicos de los sistemas de cómputo paralelo y distribuido permiten el desarrollo de aplicaciones antes impensadas. Nuestra investigación se centra en desarrollar metodologías, modelos y soluciones informáticas para colaborar en la resolución de problemas que tengan una alta demanda computacional e impacto social. Hemos definido tres ejes de investigación: aplicaciones para la salud, aplicaciones de informática forense, y consumo energético de los sistemas de cómputo paralelo. Estas líneas de investigación se desarrollan en colaboración con una universidad nacionales y otra del extranjero, un hospital público, y un gabinete provincial de informática forense.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informátic

Aplicaciones de cómputo intensivo con impacto social

Los avances tecnológicos de los sistemas de cómputo paralelo y distribuido permiten el desarrollo de aplicaciones antes impensadas. Nuestra investigación se centra en desarrollar metodologías, modelos y soluciones informáticas para colaborar en la resolución de problemas que tengan una alta demanda computacional e impacto social. Hemos definido tres ejes de investigación: aplicaciones para la salud, aplicaciones de informática forense, y consumo energético de los sistemas de cómputo paralelo. Estas líneas de investigación se desarrollan en colaboración con una universidad nacionales y otra del extranjero, un hospital público, y un gabinete provincial de informática forense.Eje: Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informátic

Triatoma patagonica (Hemiptera, Reduviidae), a New Host for Triatoma virus

Previous authors demonstrated that Triatoma virus (TrV) is able to infect several species of triatomines when injected with viral inoculum obtained from its original host, T. infestans. Both vertical (transovarian) and horizontal (faecal-oral) mechanisms of viral transmission were also described. In this paper we report the experimental TrV infection of a wild species from southern Argentina, T. patagonica. The inoculum consisted of clarified gut contents of infected T. infestans rubbed on the chicken skin whereupon T. patagonica individuals were fed. The results demonstrate that this is another potential host for the virus, and that the oral route is also effective for experimental interspecific infections

SHORT COMMUNICATION - Triatoma patagonica (Hemiptera, Reduviidae), a New Host for Triatoma virus

Previous authors demonstrated that Triatoma   virus (TrV) is able to infect several species of triatomines when injected with viral inoculum obtained from its original host, T. infestans. Both vertical (transovarian) and horizontal (faecal-oral) mechanisms of viral transmission were also described. In this paper we report the experimental TrV infection of a wild species from southern Argentina, T. patagonica. The inoculum consisted of clarified gut contents of infected T. infestans rubbed on the chicken skin whereupon T. patagonica individuals were fed. The results demonstrate that this is another potential host for the virus, and that the oral route is also effective for experimental interspecific infections

Condominios familiares: una alternativa de solución residencial para familias allegadas en lotes tipo 9x18

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