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Factores laboratoriales predictores de mortalidad por cetoacidos diabética en la unidad de trauma shock del Hospital Regional de Loreto 2020-2021

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OBJECTIVE: To recognize the laboratory factors that influence mortality in patients with Diabetic Ketoacidosis upon admission to the Trauma Shock Unit of the Regional Hospital of Loreto 2020-2021. MATERIAL AND METHODS: An observational, descriptive study of a series of cases will be carried out to r...

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Detalles Bibliográficos
Autor: Saenz Roncal, Diego Miguel
Formato: tesis de maestría
Fecha de Publicación:2023
Institución:Universidad Nacional De La Amazonía Peruana
Repositorio:UNAPIquitos-Institucional
Lenguaje:español
OAI Identifier:oai:repositorio.unapiquitos.edu.pe:20.500.12737/9198
Enlace del recurso:https://hdl.handle.net/20.500.12737/9198
Nivel de acceso:acceso abierto
Materia:Mortalidad
Diagnóstico por imagen
Técnicas de laboratotio clínico
Cetoacidosis diabética
https://purl.org/pe-repo/ocde/ford#3.02.18
Descripción
Sumario:OBJECTIVE: To recognize the laboratory factors that influence mortality in patients with Diabetic Ketoacidosis upon admission to the Trauma Shock Unit of the Regional Hospital of Loreto 2020-2021. MATERIAL AND METHODS: An observational, descriptive study of a series of cases will be carried out to recognize the laboratory factors that influence mortality in patients with Diabetic Ketoacidosis, upon admission to the Trauma Shock Unit of the Regional Hospital of Loreto 2020- 2021. For the presentation of the information, statistical tables will be used. The general characteristics will be made through descriptive statistics. Numerical analysis will include measures of central tendency (mean, median, mode, standard deviation, etc.). The variables will be analyzed according to discharge status (discharged or deceased – 48 hours) using the chi-square test with Pearson's coefficient in the case of categorical variables, and the use of the Student's t-test in the case of continuous variables.The binary logistic regression model will be used to predict mortality through potential risk factors (independent variables) towards the dependent variable (mortality), taking a value of p<0.05 as statistically significant. RESULTS: They will be obtained according to the completion of the schedule for data analysis. CONCLUSIONS: They will be carried out once the results are obtained.
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