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Modelos de autoreportes para detección de enfermedades periodontales

revisión sistemática
Authors: Miguel Hazael Russell Hernández; Michelle Rustrián Campillo; Maria Gabriela Nachón-García;

Modelos de autoreportes para detección de enfermedades periodontales

Abstract

Introducción: La enfermedad periodontal es una de las patologías infecciosas más prevalentes. El autorreporte es eficaz para evaluar características poblacionales, factores de riesgo y enfermedades. Por su rentabilidad, son prometedores como alternativa a las medidas periodontales clínicas en poblaciones donde pueden ser imprácticas o tener costos inaccesibles. Objetivo: Analizar artículos especializados para establecer la efectividad de los modelos de autorreporte como diagnóstico preliminar periodontal. Método: Búsqueda de artículos en inglés y español, en cuatro bases de datos indexadas utilizando modelo PICO y flujo PRISMA. Discusión: El autorreporte es una herramienta útil que puede implementarse en salud pública. Las medidas de autoinforme no reemplazan al examen bucal completo para diagnosticar periodontitis, pero pueden ser útiles en el seguimiento y vigilancia de condiciones periodontales en poblaciones. Conclusión: Los autocuestionarios muestran potencial para detectar enfermedad periodontal en estudios epidemiológicos, siendo un valioso recurso para vigilancia e implementación de políticas en salud pública.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
Average
Average
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