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ntroducción: en Chile, la circulación del virus SARS-CoV-2 se inició el 03 de marzo de 2020, desencadenando un rápido aumento de casos en el país. Los datos epidemiológicos y de movilidad fueron fundamentales, para evitar la propagación y severidad de la infección. Sin embargo, la limitación de ser extrapolados desde niveles de división administrativa mayor a niveles menores, ha dificultado la toma de decisiones. Una forma de resolver esto, es analizar y visualizar los datos de la infección en su contexto local, como los datos recopilados desde la Atención Primaria en Salud. Materiales y Métodos: estudio que analizó y visualizó, mediante Microsoft Excel, Stata y Looker Studio, 173.881 exámenes de SARS-CoV-2 realizados en la Corporación Municipal de Viña del Mar (366.981 beneficiarios), durante los años 2021-2022. Resultados: Se obtuvieron 33.633 casos positivos para SARS-CoV-2, de los cuales 11.084 pertenecen al rango etario entre 30 a 49 años. CESFAM Dr. Jorge Kaplán presentó mayor cantidad de casos positivos (5.838), mientras que CECOSF Villa Hermosa la menor cantidad (628). CECOSF Sergio Donoso y Santa Julia presentaron una cantidad notable de casos positivos entre 0 a 14 y 70 a 79 años, respectivamente. Discusión: existió una relación importante entre la cantidad de muestras y casos positivos según lugar de toma de muestra, jurisdicción, población per cápita atendida por jurisdicción y su distribución espacial. Conclusión: la metodología realizada permitió analizar y visualizar los datos de infección por SARS-CoV-2 por jurisdicción, lo que se puede utilizar para observar tendencias y generar estrategias para la comuna.
Introduction: in Chile, the circulation of the SARS-CoV-2 virus began on March 3, 2020, triggering a rapid increase in cases in the country. Epidemiological and mobility data were essential to prevent the spread and severity of the infection. However, the limitation of being extrapolated from higher levels of administrative division to lower levels has made decision-making difficult. One way to solve this is to analyze and visualize infection data in its local context, such as data collected from Primary Health Care.Materials and Methods: a study that analyzed and visualized, using Microsoft Excel, Stata, and Looker Studio, 173,881 SARS-CoV-2 tests performed in the Viña del Mar Municipal Corporation (366,981 beneficiaries) during 2021-2022.Results: there were 33,633 positive cases for SARS-CoV-2, of which 11,084 were in the age range between 30 and 49 years. CESFAM Dr. Jorge Kaplán had the highest positive cases (5,838), while CECOSF Villa Hermosa had the lowest number (628). CECOSF Sergio Donoso and Santa Julia had a notable number of positive cases between 0 and 14 and 70 to 79 years, respectively. Discussion: there was a significant re lationship between the number of samples and positive cases by sampling site, jurisdiction, population per capita served by jurisdiction, and spatial distribution. Conclusion: The methodology used allowed for the analysis and visualization of SARS-CoV-2 infection data by jurisdiction, which the municipality can use to observe trends and generate strategies.
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AIM: To promote the Clinical Data Inter-change Standards Consortium (CDISC) standard in clinical trials and promote the standardization of clinical trial data. METHODS: To combine the implementation guide of Analysis Data Model (ADaM) and common problems of actual data, and to introduce the application of analytical data model ADaM in the safety of bioequivalence trails of generic drugs. RESULTS: For different types of clinical trial data, according to various situations that may occur, a safety analysis data set that meets the standards was generated. CONCLUSION: Under the background of the continuous development of generic drugs in China and the low degree of standardization of clinical trial data, the use of CDISC standards in clinical research can promote the standardization of clinical trial data, and can also shorten the time of statistical analysis and accelerate the process of drug development.
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Con frecuencia en las investigaciones médicas se requiere analizar datos de tipo longitudinal que no pueden ser analizados por los métodos estadísticos clásicos de series cronológicas. El objetivo de este trabajo es presentar la factibilidad del uso del método exploratorio multivariado STATIS (Structuration des Tableaux A Trois Indices de la Statistique) en un estudio antropométrico de una muestra de 57 mujeres adultas mayores de 60 años (rango: 69-82 años) del Gran Santiago, Chile, que fueron estudiadas en 5 ocasiones durante un período de 30 meses. Las variables de interés son las mediciones antropométricas: peso, talla, circunferencia brazo, circunferencia pantorrilla, circunferencia cintura, circunferencia cadera, altura rodilla; medidas cada 6 meses. Las variables peso, circunferencia de brazo, circunferencia de pantorrilla, circunferencia de cintura y circunferencia de cadera, fueron las más correlacionadas con el primer eje de compromiso y responden fundamentalmente a medidas de composición corporal como adiposidad y masa muscular. El eje 2, caracterizado por la talla y la altura de rodilla, responde al tamaño del esqueleto. Los resultados obtenidos sugieren una evolución cronológica regular en los primeros 24 meses de observación, con un cambio de estructura a los 30 meses del estudio, así como una clasificación de grupos con diferente composición corporal.
Although in medical research the use of longitudinal data to analyze short time periods is frequently required, it does not permit the use of classic statistical methods for chronological series. The objective of this study is to present the possibility and plausibility of using the STATIS method (Structuration des Tableaux A Trois Indices de la Statistique), an explorative method for data analysis, in a study of the body composition of a sample of 57 women over 68 years of age in Santiago, Chile who were observed over a period of 30 months. The variables analyzed (measured every 6 months) were the following anthropometric measurements: weight, height, arm circumference, calf circumference, waist circumference, hip circumference and knee height. The results obtained suggested a regular chronological evolution during the first 24 months of observation with a change in structure after 30 months of the study, thereby classifying subjects according to body composition.
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Humanos , Feminino , Idoso , Idoso de 80 Anos ou mais , Constituição Corporal , Chile , Estudos Longitudinais , Análise Multivariada , Reprodutibilidade dos Testes , Fatores de TempoRESUMO
Microarray technology are being performed more widely than ever before on many areas in lifescience,although the technology is still evolving,the challenge of performing a microarray experiment is no longer in the data generation,but in extracting useful information and utilizing it to get the results with biological meanings.Some methods and tools used for expressional microarray data mining based on previous work were summarized.These methods include gene clustering,GO analysis,regulating pathway analysis,and related algorithm.We hope this can be helpful for those researchers who are implementing expressional microarray for biological analysis.
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Statistical analysis plan (SAP) is an important guidance document in clinical research which is intended to be a comprehensive and detailed description of the methods and presentation of data analyses proposed for a clinical research. The analysis plan will be completed after finalising the protocol and should be finalised before treatment unblinding, to provide full details, even to the extent of including templates of tables, listings and figures to be presented in the statistical report. Any changes between the methods in the protocol and analysis plan will be explained in the analysis plan. In order to improve the quality of TCM clinical research, it is need to optimize the SAP. Considerations in optimizing the SAP include: determine the analysis sets and analysis variables, select analysis methods and statistical software.