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dc.contributor.advisorMachado Romero, Carlos Alfonso
dc.contributor.advisorOchoa Vera, Miguel Enrique
dc.contributor.advisorVargas Ramírez, Leslie Katherine
dc.contributor.authorVásquez Pinto, Luis Enrique
dc.coverage.spatialBucaramanga (Santander, Colombia)spa
dc.date.accessioned2020-08-15T05:44:35Z
dc.date.available2020-08-15T05:44:35Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/20.500.12749/7185
dc.description.abstractIntroducción: La Falla cardíaca es un síndrome clínico caracterizado por síntomas y signos de congestión sistémica secundarios al aumento de las presiones de llenado en las cámaras del corazón, el cual se asocia a una alta mortalidad. Dentro de los factores que contribuyen al desarrollo y progresión de la falla cardíaca se han descrito los trastornos respiratorios del sueño. La prevalencia de estos trastornos, principalmente el síndrome de apnea/hipopnea obstructiva del sueño (SAHOS) es mucho más alta en los pacientes con falla cardíaca que en la población general. Debido a esto, se han diseñado múltiples herramientas de tamizaje para identificar apnea del sueño en diferentes poblaciones, dentro de estas las más comúnmente utilizadas son la escala de somnolencia de Epworth, el modelo STOP-Bang y el cuestionario de Berlín. A pesar de esto, la detección de pacientes con falla cardíaca y trastornos respiratorios del sueño puede ser difícil y la realización de polisomnografía, el estándar para el diagnóstico de la enfermedad, puede ser costoso, poco accesible y práctico en el ambiente hospitalario, lo que contribuye al subdiagnóstico. El objetivo de este estudio fue evaluar la utilidad de la aplicación de un modelo de tamizaje como el STOP-Bang en pacientes hospitalizados por falla cardíaca, su rendimiento en comparación con el estándar de diagnóstico y aportar en estrategias para la identificación sencilla de esta enfermedad. Metodología: Estudio de validez de criterio de prueba diagnóstica comparando el modelo STOP-Bang con la polisomnografía como estándar para el diagnóstico de trastornos respiratorios del sueño, en pacientes hospitalizados por falla cardiaca en la Clínica FOSCAL. Análisis estadístico con medidas de tendencia central, dispersión y frecuencia para variables sociodemográficas y clínicas cuantitativas y cualitativas. Cálculo de sensibilidad, especificidad, valores predictivos y razones de verosimilitud para cada punto de corte de la escala STOP-Bang. Resultados: Ingresaron al estudio 39 pacientes, de los cuales se incluyeron en el análisis 32 pacientes en quienes se aplicó la escala STOP-Bang y se realizó polisomnografía con un registro de sueño de al menos 3 horas. En su mayoría fueron pacientes masculinos (61,54%), con un promedio de edad de 74.76 años, con predominio de fracción de eyección conservada (66.67%), siendo la cardiopatía isquémica la principal etiología (51,28%). Como principal causa de descompensación se encontraron procesos infecciosos (33.33%). La hipertensión arterial (79.49%), la enfermedad renal crónica (56.41%) y la dislipidemia (41.03%) fueron las comorbilidades principalmente asociadas. El riesgo de presentar un trastorno del sueño por un puntaje ≥3 puntos en la escala STOP-Bang fue del 92.31%, con una prevalencia del 84.38%. La media del IAH fue de 27.43 eventos/hora. Finalmente se encontró, con un punto de corte de ≥ 3 puntos en la escala STOP-Bang, una sensibilidad del 92.6%, especificidad del 20%, valor predictivo positivo del 86.2%, valor predictivo negativo del 33.3%, razón de verosimilitud positiva de 1.16 y negativa de 0.37, con un área bajo la curva de 0.7032, encontrando en el análisis bivariado una asociación estadísticamente significativa entre tener un riesgo alto de SAHOS según la escala STOP-Bang y su diagnóstico por estudio polisomnográfico. Conclusión: Se realizó una caracterización de la población estudiada identificando las principales causas de descompensación y variables asociadas a la falla cardíaca similares a lo descrito en la literatura. Se documentó una elevada prevalencia de trastornos respiratorios del sueño con una importante proporción de pacientes que requieren tratamiento. En pacientes hospitalizados por falla cardíaca descompensada la escala STOP-Bang puede ser una herramienta aplicable para tamizaje de trastornos respiratorios del sueño, principalmente en escenarios con limitación para el acceso al estándar diagnóstico, sin embargo, se requiere realizar estudios con mayor poder estadístico.spa
dc.description.tableofcontentsLISTADO DE TABLAS ….…………………………………………………………………………..…..………………. 8 LISTADO DE FIGURAS …………………………………………………………………………..……..……………… 9 RESUMEN Y PALABRAS CLAVES ..………………………………………………………………..………………. 10 1. JUSTIFICACIÓN Y PLANTEAMIENTO DEL PROBLEMA .…………………………...………….……. 12 2. MARCO TEÓRICO……………………………………………………………………………………….…………… 13 2.1. Definición y clasificación de la falla cardíaca………………………………………..……………… 13 2.2. Etiología de la falla cardíaca……………………………………………………………………..………….. 17 2.3. Epidemiología de la falla cardíaca ……………………………………………………………..………. 20 2.4. Diagnóstico de falla cardíaca ……………………………………………………………………………… 21 2.5. Hospitalizaciones por falla cardíaca …………………………………………………………………… 24 2.6. Definiciones y diagnóstico del síndrome de apnea/hipopnea obstructiva del sueño…………………………………………………………………………………………………………………………… 25 2.7. Epidemiología del SAHOS……………………………………………………………………………………… 27 2.8. Métodos de tamizaje y escala STOP-BANG, su utilidad en el SAHOS…………………….. 29 2.9. SAHOS y falla cardíaca .………………………………………………………………………………………. 31 3. ESTADO DEL ARTE…………………………………………………………………………………………………… 33 4. OBJETIVOS………………………………………………………………………………………………………………. 35 4.1. Objetivo general………………………………………………………………………………………………….. 35 4.2. Objetivos específicos……………………………………………………………………………………………. 35 5. METODOLOGÍA………………………………………………………………………………………………………. 36 5.1. Tipo de estudio……………………………………………………………………………………………………. 36 5.2. Población…………………………………………………………………………………………………………….. 36 5.3. Criterios de inclusión……………………………………………………………………………………………. 36 5.4. Criterios de exclusión…………………………………………………………………………………………… 36 5.5. Muestra………………………………….……………………………………………………………………………. 37 5.6. Tipo de muestreo…….………………………………………………………………………………………….. 37 5.7. Recolección de la información…………………………………………………………………………….. 37 5.8. Procesamiento y control de la calidad de los datos………………………………………………. 39 5.9. Variables……………………………………………………………………………………………………………… 39 5.10. Análisis Estadístico univariado……………………………………………………………………………. 50 5.11. Análisis Estadístico bivariado y de validez de criterio………………………………………….. 50 6. CONSIDERACIONES ÉTICAS………………………………………………………………………………………. 51 7. RESULTADOS……………………………………………………………………………………………………………. 52 8. DISCUSIÓN………………………………………………………………………………………………………………. 62 9. FORTALEZAS Y LIMITACIONES………………………………………………………………………………….. 65 10. CONCLUSIONES……………………………………………………………………………………………………… 66 11. ANEXOS……………………………………………………………………………………………………………….... 68 12. REFERENCIAS BIBLIOGRÁFICAS………………………………………………………………………………. 81spa
dc.format.mimetypeapplication/pdf
dc.language.isospaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleUtilidad de la escala Stop-Bang para la detección de alteraciones del sueño en pacientes hospitalizados por falla cardíacaspa
dc.title.translatedUsefulness of the Stop-Bang scale for detecting sleep disturbances in patients hospitalized for heart failureeng
dc.degree.nameEspecialista en Medicina Internaspa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ciencias de la Salud
dc.publisher.programEspecialización en Medicina Interna
dc.description.degreelevelEspecializaciónspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.localTesisspa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.subject.keywordsInternal medicine
dc.subject.keywordsMedicine
dc.subject.keywordsMedical sciences
dc.subject.keywordsHealth sciences
dc.subject.keywordsHeart failure
dc.subject.keywordsSleep disordered breathing
dc.subject.keywordsApnea
dc.subject.keywordsSleep disorders
dc.subject.keywordsHeart diseases
dc.subject.keywordsTreatment
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNAB
dc.identifier.reponamereponame:Repositorio Institucional UNAB
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersionspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2
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dc.description.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001434641spa
dc.description.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001543126spa
dc.description.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000898465spa
dc.identifier.orcidhttps://orcid.org/0000-0002-3792-8019
dc.identifier.orcidhttps://orcid.org/0000-0001-6826-721X
dc.identifier.orcidhttps://orcid.org/0000-0002-4552-3388
dc.description.scopushttps://www.scopus.com/authid/detail.uri?authorId=36987156500spa
dc.description.researchgatehttps://www.researchgate.net/profile/Miguel_Ochoa7spa
dc.subject.lembMedicina internaspa
dc.subject.lembMedicinaspa
dc.subject.lembCiencias médicasspa
dc.subject.lembTrastornos del sueñospa
dc.subject.lembEnfermedades cardíacasspa
dc.subject.lembTratamientospa
dc.identifier.repourlrepourl:https://repository.unab.edu.cospa
dc.description.abstractenglishIntroduction: Heart failure is a clinical syndrome characterized by signs and symptoms of systemic congestion secondary to the increase in filling pressures in the chambers of the heart, which is associated with high mortality. Among the factors that contribute to the development and progression of heart failure, sleep respiratory disorders have been described. The prevalence of these disorders, mainly obstructive sleep apnea / hypopnea syndrome, is much higher in patients with heart failure than in the general population. Due to this, multiple screening tools have been designed to identify sleep apnea in different populations, among these the most commonly used are the Epworth sleepiness scale, the STOP-Bang model and the Berlin questionnaire. Despite this, detection of patients with heart failure and sleep-disordered breathing can be difficult, and polysomnography, the standard for diagnosing the disease, can be expensive, inaccessible, and not practical in the hospital setting, which contributes to underdiagnosis. The objective of this study was to evaluate the utility of applying a screening model such as the STOP-Bang in patients hospitalized for heart failure, its performance compared to the diagnostic standard and to contribute to strategies for the simple identification of this disease. Methodology: Study of the validity of the diagnostic test criteria comparing the STOP-Bang model with polysomnography as a standard for the diagnosis of sleep-disordered breathing disorders, in patients hospitalized for heart failure at the FOSCAL Clinic. Statistical analysis with measures of central tendency, dispersion and frequency for quantitative and qualitative sociodemographic and clinical variables. Calculation of sensitivity, specificity, predictive values and likelihood ratios for each cut-off point of the STOP-Bang scale. Results: 39 patients entered the study, of which 32 patients were included in the analysis in whom the STOP-Bang scale was applied and polysomnography was performed with a sleep record of at least 3 hours. The majority were male patients (61.54%), with an average age of 74.76 years, with a predominance of preserved ejection fraction (66.67%), with ischemic heart disease being the main etiology (51.28%). Infectious processes were found as the main cause of decompensation (33.33%). High blood pressure (79.49%), chronic kidney disease (56.41%) and dyslipidemia (41.03%) were the mainly associated comorbidities. The risk of presenting a sleep disorder due to a score of ≥3 points on the STOP-Bang scale was 92.31%, with a prevalence of 84.38%. The mean AHI mean was 27.43 events / hour. Finally, with a cut-off point of ≥ 3 points on the STOP-Bang scale, a sensitivity of 92.6%, specificity of 20%, positive predictive value of 86.2%, negative predictive value of 33.3%, positive likelihood ratio of 1.16 and negative of 0.37, with an area under the curve of 0.7032, finding in the bivariate analysis a statistically significant association between having a high risk of sleep breathing disorder according to the STOP-Bang scale and its diagnosis by polysomnography. Conclusion: A characterization of the studied population was performed identifying the main causes of decompensation and variables associated with heart failure similar to that described in the literature. A high prevalence of sleep respiratory disorders was documented with a significant proportion of patients requiring treatment. In hospitalized patients due to decompensated heart failure, the STOP-Bang scale can be an applicable tool for screening sleep-disordered breathing, mainly in settings with limited access to the diagnostic standard, however, studies with greater statistical power are required.spa
dc.subject.proposalCiencias de la saludspa
dc.subject.proposalFalla cardíacaspa
dc.subject.proposalApnea del sueñospa
dc.subject.proposalStop bangspa
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*


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