Considerations on the Castrop formula for calculation of intraocular lens power.

<h4>Background</h4>To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae.<h4>Methods</h4>The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Achim Langenbucher, Nóra Szentmáry, Alan Cayless, Johannes Weisensee, Ekkehard Fabian, Jascha Wendelstein, Peter Hoffmann
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/02252d721f964cee809c6d52c5a0ad71
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:02252d721f964cee809c6d52c5a0ad71
record_format	dspace
spelling	oai:doaj.org-article:02252d721f964cee809c6d52c5a0ad712021-12-02T20:05:23ZConsiderations on the Castrop formula for calculation of intraocular lens power.1932-620310.1371/journal.pone.0252102https://doaj.org/article/02252d721f964cee809c6d52c5a0ad712021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252102https://doaj.org/toc/1932-6203<h4>Background</h4>To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae.<h4>Methods</h4>The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive surfaces. This was compared against the SRKT, Hoffer-Q, Holladay1, simplified Haigis with 1 optimized constant and Haigis formula with 3 optimized constants. A large dataset of preoperative biometric values, lens power data and postoperative refraction data was split into training and test sets. The training data were used for formula constant optimization, and the test data for cross-validation. Constant optimization was performed for all formulae using nonlinear optimization, minimising root mean squared prediction error.<h4>Results</h4>The constants for all formulae were derived with the Levenberg-Marquardt algorithm. Applying these constants to the test data, the Castrop formula showed a slightly better performance compared to the classical formulae in terms of prediction error and absolute prediction error. Using the Castrop formula, the standard deviation of the prediction error was lowest at 0.45 dpt, and 95% of all eyes in the test data were within the limit of 0.9 dpt of prediction error.<h4>Conclusion</h4>The calculation concept of the Castrop formula and one potential option for optimization of the 3 Castrop formula constants (C, H, and R) are presented. In a large dataset of 1452 data points the performance of the Castrop formula was slightly superior to the respective results of the classical formulae such as SRKT, Hoffer-Q, Holladay1 or Haigis.Achim LangenbucherNóra SzentmáryAlan CaylessJohannes WeisenseeEkkehard FabianJascha WendelsteinPeter HoffmannPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0252102 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Achim Langenbucher Nóra Szentmáry Alan Cayless Johannes Weisensee Ekkehard Fabian Jascha Wendelstein Peter Hoffmann Considerations on the Castrop formula for calculation of intraocular lens power.
description	<h4>Background</h4>To explain the concept of the Castrop lens power calculation formula and show the application and results from a large dataset compared to classical formulae.<h4>Methods</h4>The Castrop vergence formula is based on a pseudophakic model eye with 4 refractive surfaces. This was compared against the SRKT, Hoffer-Q, Holladay1, simplified Haigis with 1 optimized constant and Haigis formula with 3 optimized constants. A large dataset of preoperative biometric values, lens power data and postoperative refraction data was split into training and test sets. The training data were used for formula constant optimization, and the test data for cross-validation. Constant optimization was performed for all formulae using nonlinear optimization, minimising root mean squared prediction error.<h4>Results</h4>The constants for all formulae were derived with the Levenberg-Marquardt algorithm. Applying these constants to the test data, the Castrop formula showed a slightly better performance compared to the classical formulae in terms of prediction error and absolute prediction error. Using the Castrop formula, the standard deviation of the prediction error was lowest at 0.45 dpt, and 95% of all eyes in the test data were within the limit of 0.9 dpt of prediction error.<h4>Conclusion</h4>The calculation concept of the Castrop formula and one potential option for optimization of the 3 Castrop formula constants (C, H, and R) are presented. In a large dataset of 1452 data points the performance of the Castrop formula was slightly superior to the respective results of the classical formulae such as SRKT, Hoffer-Q, Holladay1 or Haigis.
format	article
author	Achim Langenbucher Nóra Szentmáry Alan Cayless Johannes Weisensee Ekkehard Fabian Jascha Wendelstein Peter Hoffmann
author_facet	Achim Langenbucher Nóra Szentmáry Alan Cayless Johannes Weisensee Ekkehard Fabian Jascha Wendelstein Peter Hoffmann
author_sort	Achim Langenbucher
title	Considerations on the Castrop formula for calculation of intraocular lens power.
title_short	Considerations on the Castrop formula for calculation of intraocular lens power.
title_full	Considerations on the Castrop formula for calculation of intraocular lens power.
title_fullStr	Considerations on the Castrop formula for calculation of intraocular lens power.
title_full_unstemmed	Considerations on the Castrop formula for calculation of intraocular lens power.
title_sort	considerations on the castrop formula for calculation of intraocular lens power.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/02252d721f964cee809c6d52c5a0ad71
work_keys_str_mv	AT achimlangenbucher considerationsonthecastropformulaforcalculationofintraocularlenspower AT noraszentmary considerationsonthecastropformulaforcalculationofintraocularlenspower AT alancayless considerationsonthecastropformulaforcalculationofintraocularlenspower AT johannesweisensee considerationsonthecastropformulaforcalculationofintraocularlenspower AT ekkehardfabian considerationsonthecastropformulaforcalculationofintraocularlenspower AT jaschawendelstein considerationsonthecastropformulaforcalculationofintraocularlenspower AT peterhoffmann considerationsonthecastropformulaforcalculationofintraocularlenspower
_version_	1718375462274596864

Considerations on the Castrop formula for calculation of intraocular lens power.

Ejemplares similares