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Culqui, D., (2010). Factores de riesgo para el abandono del tratamiento antituberculoso esquema I y II Perú 2004 [Tesis, Universidad Nacional Mayor de San Marcos]. https://hdl.handle.net/20.500.12672/2497
Culqui, D., Factores de riesgo para el abandono del tratamiento antituberculoso esquema I y II Perú 2004 [Tesis]. PE: Universidad Nacional Mayor de San Marcos; 2010. https://hdl.handle.net/20.500.12672/2497
@misc{renati/477666,
title = "Factores de riesgo para el abandono del tratamiento antituberculoso esquema I y II Perú 2004",
author = "Culqui Lévano, Dante Roger",
publisher = "Universidad Nacional Mayor de San Marcos",
year = "2010"
}
Title: Factores de riesgo para el abandono del tratamiento antituberculoso esquema I y II Perú 2004
Authors(s): Culqui Lévano, Dante Roger
OCDE field: https://purl.org/pe-repo/ocde/ford#3.00.00
Issue Date: 2010
Institution: Universidad Nacional Mayor de San Marcos
Abstract: Antecedentes: El control de la tuberculosis es un complejo reto para la salud pública en el mundo que involucra asegurar el acceso al diagnóstico, tratamiento y cura de los pacientes. Se sabe que el no cumplimiento del tratamiento puede llevar a complicaciones fatales y a la emergencia de cepas resistentes. La identificación y el entendimiento de los factores que determinan el no cumplimiento del tratamiento, proveerán información para aumentar la eficacia de los programas de control.
Objetivo: Identificar factores de riesgo para el abandono del tratamiento antituberculosis en el Perú.
Material y métodos: Se realizó un estudio de casos y controles en las provincias de mayor incidencia de abandono de tratamiento durante el año 2004. Se seleccionaron 295 casos y 590 controles y la relación de casos a controles fue de 1:2 los factores relacionados al abandono de tratamiento, se evaluaron mediante análisis de riesgo.
Resultados: Se identificó como factores de riesgo para el abandono el presentar una edad entre 15 y 20 años (OR=1.78/1.02-3.13) o mayor de 40 años (OR=1.68/1.12-2.51),el presentar un nivel de educación inferior: secundaria (OR=1.88/1.09-3.26), primaria (OR=2.46/1.24-4.86), así como presentar al menos 1 Necesidad Básica Insatisfecha (NBI) (OR=1.67/1.09-2.54), el considerar al personal capacitado a medias (OR=1.63/1.06-2.52), así como el presentar el antecedente de abandono anterior (OR=7.06/4.32-11.53), así como manifestar disconformidad con la información recibida por el personal: considerar elemental (regular) la información recibida (OR=3.64/1.11-11.88), mostrarse insatisfecho o muy insatisfecho con la información recibida (OR=5.38/1.33-21.73).
Conclusiones Es evidente que a pesar que existen muchos factores reconocidos en la bibliografía como factores de riesgo para el abandono de tratamiento, luego del análisis con la regresión logística, son solamente nueve los factores que podrían considerarse factores pronósticos de abandono de tratamiento.
Background: Tuberculosis control is a complex public health challenge in the world that involves ensuring access to diagnosis, treatment and cure of patients. It is known that no treatment compliance can lead to fatal complications and the emergence of resistant strains. The identification and understanding of the determinants of treatment noncompliance, provide information to enhance the effectiveness of control programs. Objective: To identify risk factors for noncompliance with tuberculosis treatment in Peru. Methods: We performed a case-control study in the provinces with the highest incidence of treatment noncompliance in 2004. We selected 295 cases and 590 controls and cases to controls ratio of 1:2 will be factors related to noncompliance of treatment were assessed by risk analysis. Results: We identified risk factors for noncompliance the present age from 15 to 20 years (OR = 1.78/1.02-3.13) or > 40 years (OR = 1.68/1.12-2.51), the present level of education Bottom: secondary (OR = 1.88/1.09-3.26), primary (OR = 2.46/1.24-4.86) and submit at least 1 unmet basic needs (NBI) (OR = 1.67/1.09-2.54), to consider personnel trained half (OR = 1.63/1.06-2.52) and presenting a history of previous of noncompliance (OR = 7.06/4.32-11.53), and to express disagreement with the information received by staff, to consider elementary (regular) information received (OR = 3.64/1.11-11.88), appear dissatisfied or very dissatisfied with the information received (OR = 5.38/1.33-21.73). Conclusions: It is evident that although there are many factors known in the literature as risk factors for discontinuing treatment after logistic regression analysis, are only nine factors that could be considered predictors of treatment dropout.
Background: Tuberculosis control is a complex public health challenge in the world that involves ensuring access to diagnosis, treatment and cure of patients. It is known that no treatment compliance can lead to fatal complications and the emergence of resistant strains. The identification and understanding of the determinants of treatment noncompliance, provide information to enhance the effectiveness of control programs. Objective: To identify risk factors for noncompliance with tuberculosis treatment in Peru. Methods: We performed a case-control study in the provinces with the highest incidence of treatment noncompliance in 2004. We selected 295 cases and 590 controls and cases to controls ratio of 1:2 will be factors related to noncompliance of treatment were assessed by risk analysis. Results: We identified risk factors for noncompliance the present age from 15 to 20 years (OR = 1.78/1.02-3.13) or > 40 years (OR = 1.68/1.12-2.51), the present level of education Bottom: secondary (OR = 1.88/1.09-3.26), primary (OR = 2.46/1.24-4.86) and submit at least 1 unmet basic needs (NBI) (OR = 1.67/1.09-2.54), to consider personnel trained half (OR = 1.63/1.06-2.52) and presenting a history of previous of noncompliance (OR = 7.06/4.32-11.53), and to express disagreement with the information received by staff, to consider elementary (regular) information received (OR = 3.64/1.11-11.88), appear dissatisfied or very dissatisfied with the information received (OR = 5.38/1.33-21.73). Conclusions: It is evident that although there are many factors known in the literature as risk factors for discontinuing treatment after logistic regression analysis, are only nine factors that could be considered predictors of treatment dropout.
Link to repository: https://hdl.handle.net/20.500.12672/2497
Discipline: Epidemiología
Grade or title grantor: Universidad Nacional Mayor de San Marcos. Facultad de Medicina. Unidad de Posgrado
Grade or title: Magíster en Epidemiología
Register date: 20-Aug-2013
This item is licensed under a Creative Commons License