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dc.contributor.advisorTello Hernández, Alejandrospa
dc.contributor.authorCabal López, Pablo Danielspa
dc.date.accessioned2020-06-26T20:01:42Z
dc.date.available2020-06-26T20:01:42Z
dc.date.issued2018-06-07
dc.identifier.urihttp://hdl.handle.net/20.500.12749/1787
dc.description.abstractLas causas de compromiso visual definido como una disminución de la agudeza visual (AV) menor de 20/40 en la escala de Snellen, y de ceguera definido como una AV igual o peor a 20/200 a nivel mundial son múltiples. La catarata definida como la opacificación del cristalino de cualquier etilologia sigue siendo la principal causa de ceguera prevenible y reversible a nivel mundial(1) Se estima que para el año 2004 había solo en Estados Unidos 3.4 millones de individuos mayores de 40 años afectados por esta condición.(2) La disminución de la AV es uno de los factores de riesgo más importantes para la afectación de la calidad de vida de los individuos, esto genera un costo importante para los diferentes sistemas de salud teniendo en cuenta que este tipo de personas son más proclives a sufrir de accidentes y sus habilidades físicas y sociales se ven profundamente comprometidas. Es por esto que se considera como un problema de Salud Pública a nivel mundial, y de ahí la importancia tanto de diagnosticarla como de poder tratarla a tiempo antes de que ocurran complicaciones oculares relacionadas con el crecimiento del cristalino que puedan llevar a comprometer la visión de forma permanente e irreversible. Metodología Estudio de cohorte retrospectiva con datos secundarios de base de datos anonimizada de 98 pacientes que fueron intervenidos de cirugía de catarata con colocación de lente intraocular SN60WF IQ de Alcon durante los años 2015 y 2017 en el centro oftalmológico Virgilio Galvis, con longitudes axiales entre 22 y 26mm y operados por un mismo cirujano. Resultados En conjunto la fórmula SRK-T2 tiene el mejor desempeño y la fórmula con el menor desempeño es la Haigis sin diferencia estadísticamente significativa entre ellas. La fórmula biométrica que mejor despeño tuvo teniendo en cuenta el porcentaje y número de pacientes dentro de las 0.5D de error dióptrico predicho fue la Hill-RBF y la de menor desempeño la Haigis nuevamente sin tampoco encontrarse una diferencia estadísticamente significativa entre ellas. Los resultados de las demás fórmulas son muy similares entre ellos. Conclusiones Teniendo en cuenta los resultados en la clasificación de errores de predicción dentro de las 0.5D y de la clasificación de los promedios de error absoluto de predicción, se puede concluir sin significancia estadística que la fórmula que tiende a tener mejor desempeño al calcular el poder dióptrico con la constante 119.0 optimizada por la ULIB para el lente intraocular IQ en pacientes con longitudes axiales de 22-26 mm es la Hill-RBF y que la que menor desempeño tiende a tener es la Haigis.spa
dc.description.tableofcontents• Resumen del Proyecto • Justificación • Marco Teórico • Estado del Arte • Objetivos • Metodología • Resultados • Discusión • Conclusionesspa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleComparación de fórmulas biométricas para el cálculo del poder del lente intraocular IQspa
dc.title.translatedComparison of biometric formulas for calculating the power of the IQ intraocular lenseng
dc.degree.nameEspecialista en Oftalmologíaspa
dc.coverageBucaramanga (Santander, Colombia)spa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ciencias de la Saludspa
dc.publisher.programEspecialización en Oftalmologíaspa
dc.description.degreelevelEspecializaciónspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.localTesisspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.subject.keywordsBiometric formulaeng
dc.subject.keywordsWaterfalleng
dc.subject.keywordsVisual acuityeng
dc.subject.keywordsQuality of lifeeng
dc.subject.keywordsIntraocular lenseng
dc.subject.keywordsMedicineeng
dc.subject.keywordsOphthalmologyeng
dc.subject.keywordsResearcheng
dc.subject.keywordsRefraction of lighteng
dc.subject.keywordsCataract surgeryeng
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
dc.relation.referencesCabal López, Pablo Daniel (2018). Comparación de fórmulas biométricas para el cálculo del poder del lente intraocular IQ. Bucaramanga (Santander, Colombia) : Universidad Autónoma de Bucaramanga UNABspa
dc.relation.references1. Klein BE, Howard KP, Lee KE, Klein R. Changing Incidence of Lens Extraction Over Twenty Years: the Beaver Dam Eye Study. Ophthalmology. 2014;121(1):1-11.spa
dc.relation.references2. Saaddine L, Benjamin S, Pan L, Venkat Narayan K, Tierney E, Kanjilal S, et al. Prevalence of Visual Impairment and Selected Eye Diseases Among Persons Aged >50 Years With and Without Diabetes --- United States, 2002. Morb Mortal Wkly Rep. 2004;53(45):1069-71.spa
dc.relation.references3. Guo C, Wang Z, He P, Chen G, Zheng X. Prevalence, causes and social factors of visual impairment among Chinese Adults: based on a national survey. Int J Environ Res Public Health. 2017;14(1034):1-11.spa
dc.relation.references4. Al-Sheikh M, Iafe NA, Phasukkijwatana N, Sadda SR, Sarraf D. Biomarkers of neovascular activity in age-related macular degeneration using OCT angiography. Retina. 2017;1.spa
dc.relation.references5. Gollogly HE, Hodge DO, St. Sauver JL, Erie JC. Increasing incidence of cataract surgery: Population-based study. J Cataract Refract Surg. 2013;39(9):1383-9.spa
dc.relation.references6. Steinert RF, Chang DF, Bissen-Miyajima H, Fine IH, Gimbel H V, Koch DD, et al. Cataract Surgery. 2010. all.spa
dc.relation.references7. Saaddine J, Benjamin S, Pan L, Venkat Narayan K, Tierney E, Kanjilal S. Prevalence of Visual Impairment and Selected Eye Diseases Among Persons Aged ≥50 Years With and Without Diabetes --- United States, 2002 [Internet]. CDC. 2004 [citado 7 de octubre de 2017]. Disponible en: https://www.cdc.gov/MMWR/preview/mmwrhtml/mm5345a3.htmspa
dc.relation.references8. Karabela Y, Eliacik M, Kocabora MS, Erdur SK, Baybora H. Predicting the refractive outcome and accuracy of IOL power calculation after phacoemulsification using the SRK/T formula with ultrasound biometry in medium axial lengths. Clin Ophthalmol. 2017;11:1143-9.spa
dc.relation.references9. Bobrow JC, Beardsley TL, Jick SL, Rosenberg LF, Wiggins MN, Reich J, et al. Lens and cataract, Section 11. Basic and Clinical Science Course, American Academy of Ophthalmology. 2014. all.spa
dc.relation.references10. Kim YN, Park JH, Tchah H. Quantitative Analysis of Lens Nuclear Density Using Optical Coherence Tomography ( OCT ) with a Liquid Optics Interface : Correlation between OCT Images and LOCS III Grading. J Ophthalmol. 2016;2016.spa
dc.relation.references11. Chylack LT, Wolfe JK, Singer DM, Leske MC. The Lens Opacities Classification System III. Arch Ophthalmol. 1993;spa
dc.relation.references12. Hollick EJ, Spalton DJ, Ursell PG. The Effect of Polymethylmethacrylate , Silicone , and Polyacrylic Intraocular Lenses on Posterior Capsular Opacification 3 Years after Cataract Surgery. :49-55.spa
dc.relation.references13. Laboratories A. Product information AcrySof IQ Aspheric IOL. 2010. p. 1-14.spa
dc.relation.references14. Wintergerst MWM, Schultz T, Birtel J, Schuster AK, Pfeiffer N, Schmitz-Valckenberg S, et al. Algorithms for the Automated Analysis of Age-Related Macular Degeneration Biomarkers on Optical Coherence Tomography: A Systematic Review. Transl Vis Sci Technol. 2017;6(4):10.spa
dc.relation.references15. Cooke DL, Cooke TL. Prediction accuracy of preinstalled formulas on 2 optical biometers. J Cataract Refract Surg. 2016;42(3):358-62.spa
dc.relation.references16. Olsen T. Calculation of intraocular lens power : a review The statistical. Acta Ophthalmol Scand. 2007;472-85.spa
dc.relation.references17. Jeong J, Song H, Lee JK, Chuck RS, Kwon J-W. The effect of ocular biometric factors on the accuracy of various IOL power calculation formulas. BMC Ophthalmol. 2017;17(1):62.spa
dc.relation.references18. Plat J, Hoa D, Mura F, Busetto T, Schneider C, Payerols A, et al. Clinical and biometric determinants of actual lens position after cataract surgery. J Cartaract Refract Surg. 2017;43(2):195-200.spa
dc.relation.references19. Roberts T V., Hodge C, Sutton G, Lawless M. Comparison of Hill-radial basis function, Barrett Universal and current third generation formulas for the calculation of intraocular lens power during cataract surgery. Clin Experiment Ophthalmol. 2017;spa
dc.relation.references20. Kongsap P. Comparison of a new optical biometer and a standard biometer in cataract patients. Eye Vis. 2016;3(1):27.spa
dc.relation.references21. Ventura B V., Ventura MC, Wang L, Koch DD, Weikert MP. Comparison of biometry and intraocular lens power calculation performed by a new optical biometry device and a reference biometer. J Cataract Refract Surg. 2017;43(1):74-9.spa
dc.relation.references22. Hoffer KJ, Hoffmann PC, Savini G. Comparison of a new optical biometer using swept-source optical coherence tomography and a biometer using optical low-coherence reflectometry. J Cataract Refract Surg. 2016;42(8):1165-72.spa
dc.relation.references23. Kane JX, Van Heerden A, Atik A, Petsoglou C. Accuracy of 3 new methods for intraocular lens power selection. J Cataract Refract Surg. 2017;43(3):333-9.spa
dc.relation.references24. Roberts TV, Hodge C, Sutton G, Lawless M, contributors to the Vision Eye Institute IOL outcomes registry. Comparison of Hill-radial basis function, Barrett Universal and current third generation formulas for the calculation of intraocular lens power during cataract surgery: Calculation of intraocular lens power. Clin Experiment Ophthalmol. abril de 2018;46(3):240-6.spa
dc.relation.references25. Hashemi H, Khabazkhoob M, Rezvan F, Fotouhi A, Asgari S, Miraftab M. Effect of anterior chamber depth on the choice of intraocular lens calculation formula in patients with normal axial length. Middle East Afr J Ophthalmol. 2014;21(4):307.spa
dc.relation.references26. Gale RP, Saldana M, Johnston RL, Zuberbuhler B, McKibbin M. Benchmark standards for refractive outcomes after NHS cataract surgery. Eye. enero de 2009;23(1):149-52.spa
dc.relation.references27. Melles RB, Holladay JT, Chang WJ. Accuracy of Intraocular Lens Calculation Formulas. Ophthalmology. febrero de 2018;125(2):169-78.spa
dc.relation.references28. Kane JX, Van Heerden A, Atik A, Petsoglou C. Intraocular lens power formula accuracy: Comparison of 7 formulas. J Cataract Refract Surg. octubre de 2016;42(10):1490-500.spa
dc.relation.references29. Aristodemou P, Knox Cartwright NE, Sparrow JM, Johnston RL. Intraocular lens formula constant optimization and partial coherence interferometry biometry: Refractive outcomes in 8108 eyes after cataract surgery. J Cataract Refract Surg. enero de 2011;37(1):50-62.spa
dc.relation.references30. Wang J-K, Chang S-W. Optical biometry intraocular lens power calculation using different formulas in patients with different axial lengths. Int J Ophthalmol. 2013;6(2):150-4.spa
dc.relation.references31. Hoffer KJ. Clinical results using the Holladay 2 intraocular lens power formula. J Cataract Refract Surg. agosto de 2000;26(8):1233-7.spa
dc.relation.references32. Narváez J, Zimmerman G, Stulting RD, Chang DH. Accuracy of intraocular lens power prediction using the Hoffer Q, Holladay 1, Holladay 2, and SRK/T formulas. J Cataract Refract Surg. diciembre de 2006;32(12):2050-3.spa
dc.contributor.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001009125*
dc.contributor.googlescholarhttps://scholar.google.es/citations?hl=es#user=puxZHKYAAAAJ*
dc.contributor.scopushttps://www.scopus.com/authid/detail.uri?authorId=6603664598*
dc.subject.lembFórmula biométricaspa
dc.subject.lembCatarataspa
dc.subject.lembAgudeza visualspa
dc.subject.lembCalidad de vidaspa
dc.subject.lembLente intraocularspa
dc.subject.lembMedicinaspa
dc.subject.lembOftalmologíaspa
dc.subject.lembInvestigacionesspa
dc.description.abstractenglishThe causes of visual impairment defined as a decrease in visual acuity (VA) less than 20/40 on the Snellen scale, and of blindness defined as VA equal to or worse than 20/200 worldwide are multiple. Cataract defined as the opacification of the lens of any ethylology continues to be the main cause of preventable and reversible blindness worldwide (1) It is estimated that in 2004 there were only 3.4 million individuals over 40 years of age affected by this condition in the United States. (2) The decrease in VA is one of the most important risk factors for affecting the quality of life of individuals, this generates a significant cost for the different health systems, taking into account that these types of people are more prone to suffer accident and their physical and social skills are deeply compromised. This is why it is considered a Public Health problem worldwide, and hence the importance of both diagnosing it and being able to treat it in time before ocular complications related to lens growth occur that may lead to compromise the vision of permanently and irreversibly. Methodology Retrospective cohort study with secondary data from an anonymized database of 98 patients who underwent cataract surgery with placement of the Alcon SN60WF IQ intraocular lens during the years 2015 and 2017 at the Virgilio Galvis ophthalmological center, with axial lengths between 22 and 26mm and operated by the same surgeon. Results Overall, the SRK-T2 formula has the best performance and the formula with the lowest performance is the Haigis with no statistically significant difference between them. The biometric that had the best performance formula taking into account the percentage and number of patients within 0.5D of predicted diopter error was Hill-RBF and the one with the lowest performance was Haigis again, without finding a statistically significant difference between them. The results of the other formulas are very similar to each other. Conclusions Taking into account the results in the classification of prediction errors within 0.5D and of the classification of the averages of absolute prediction error, it can be concluded without statistical significance that the formula that tends to have better performance when calculating the diopter power with the constant 119.0 optimized by the ULIB for the IQ intraocular lens in patients with axial lengths of 22-26 mm is the Hill-RBF and the lowest performance tends to be the Haigis.eng
dc.subject.proposalRefracción de la luz
dc.subject.proposalCirugía de catarata
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.description.learningmodalityModalidad Presencialspa


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