ABSTRACT
Objective To formulate a five-level pediatric emergency triage standard and evaluate the efficacy and reliability of it in determining severity of emergency pediatric patients.Methods According to the assessment methods in Pediatric Advanced Life Support recommended by American Heart Association and American Academy of Pediatrics,we formulated a five-level pediatric emergency triage standard based on the situation of our hospital and analyzed the data one year before and after the application of it.Results Before and after the application of the triage standard,the average satisfaction rate of emergency patients were (81.28 ± 3.97) ％ and (94.13 ± 4.62) ％,and there was significant difference (P ＜ 0.01) ; the proportion of whom became worse during waiting time were 1.83％ (628/34275) and 0.04％ (16/36 187),and there was significant difference (P ＜0.01) ;the average waiting time of emergency admission patients were (12.71 ± 2.32) min and (3.34 ± 1.95) min,and there was significant difference (P ＜0.01) ;the misjudgment rate of severity were 3.78％ (1 296/34 275) and 0.57％ (205/36 187),and there was significant difference (P ＜ 0.05).Conclusion The five-level triage standard is objective,easy to master,and suitable for pediatric triage.It can quickly sort out critical cases from emergency pediatric patients,which can improve the effectiveness of emergency service,make use of medical resources rationally and somewhat solve the problem of overcrowding.
ABSTRACT
Autism diagnosis requires validated diagnostic tools employed by mental health professionals with expertise in autism spectrum disorders. This conventionally requires lengthy information processing and technical understanding of each of the areas evaluated in the tools. Classifying the impact of these areas and proposing a system that can aid experts in the diagnosis is a complex task. This paper presents the methodology used to find the most significant items from the ADOS-G tool to detect Autism Spectrum Disorders through Feed-forward Artificial Neural Networks with back-propagation training. The number of cases for the network training data was determined by using the Taguchi method with Orthogonal Arrays reducing the sample size from 531,441 to only 27. The trained network provides an accuracy of 100% with 11 different cases used only for validation, which provides a specificity and sensitivity of 1. The network was used to classify the 12 items from the ADOS-G tool algorithm into three levels of impact for Autism diagnosis: High, Medium and Low. It was found that the items "Showing", "Shared enjoyment in Interaction" and "Frequency of vocalization directed to others", are the areas of highest impact for Autism diagnosis. The methodology here presented can be replicated to different Autism diagnosis tests to classify their impact areas as well.
El diagnóstico del autismo requiere del uso de herramientas de diagnóstico validadas internacionalmente que son utilizadas por los profesionales de la salud expertos en trastornos del espectro autista, lo cual requiere de procesamiento de mucha información y un entendimiento técnico de cada una de las áreas evaluadas en ellas. La clasificación del impacto que tienen cada una de estas áreas, así como la propuesta de un sistema que pueda ayudar a los expertos en el diagnóstico, es una tarea compleja, por lo que en este artículo se presenta una metodología utilizada para encontrar los elementos más significativos de la herramienta de diagnóstico de autismo ADOS-G a través de redes neuronales artificiales entrenadas con retropropagación del error. El número de casos para entrenamiento de la red se seleccionó utilizando el método de Taguchi con arreglos ortogonales, reduciendo el tamaño de la muestra de 531,441 a solo 27 casos. La red entrenada tiene una exactitud del 100% validada con 11 casos diferentes de niños evaluados para diagnóstico de trastorno del espectro autista con lo que se obtuvo una especificidad y sensibilidad de 1. La red neuronal artificial se utilizó para clasificar los 12 elementos del algoritmo de la herramienta ADOS-G en tres niveles de impacto: Alto, Medio y Bajo. Se encontró que los elementos "Mostrar", "Placer compartido durante la interacción" y "Frecuencia de vocalizaciones dirigidas a otros" son las áreas de mayor impacto para el diagnóstico de autismo. La metodología presentada puede ser replicada para diferentes herramientas de diagnóstico de autismo para clasificar sus áreas de mayor impacto también.
ABSTRACT
Research on history of TCM should serve for development of TCM today.Researchers in history of prescriptions of Chinese materia medica should think the question about development of prescriptions of Chinese materia medica.Three problems about development of prescriptions of Chinese materia medica are brought forward currently.Firstly what is area of it in science,whether method of treatment and preparation are attached to it .Secondly whether classify of it is accordant to theory of TCM and method of treatment.Thirdly the Pharmacopoeia hold in the prescriptions .The items of Pharmacopoeia couldn’t satisfy clinical needs of TCM in processing and dosage.A standard of prescription should be drawn besides the Pharmacopoeia.
ABSTRACT
Objective: To apply fuzzy clustering analysis to determination of 10 inorganic elements and Cu/Zn ratio in 13 kinds of traditional Chinese medicine cured for vascular disease. Methods: By FAAS (flame atomic absorption spectrometry) sodium, calcium, magnesium, potassium, iron, chromium, nickel, manganese, copper and zinc were determined. By range analysis, correlation coefficients and relative fuzzy matrix were calculated.Results: Correlation coeffieients ? were mostly in the range of 0.55～0.80, especially ?=0.95 between Buzhangnaoxintong Capsule and Xinbao Pill. Conclusion: On condition that trace and macro elements are relatively rich and clustering correlation coefficients are larger, therapentic effects among traditional Chinese medicines cured for vascular disease are also similar. This suggests that trace elements, macro elements and Cu/Zn ratio have much to do with therapeutic effect.