Determination of Personalized IOL-Constants for the Haigis Formula under Consideration of Measurement Precision

The capabilities of a weighted least squares approach for the optimization of the intraocular lens (IOL) constants for the Haigis formula are studied in comparison to an ordinary least squares approach. The weights are set to the inverse variances of the effective optical anterior chamber depth. The...

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Veröffentlicht in:PloS one 2016-07, Vol.11 (7), p.e0158988-e0158988
Hauptverfasser: Schröder, Simon, Leydolt, Christina, Menapace, Rupert, Eppig, Timo, Langenbucher, Achim
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Leydolt, Christina
Menapace, Rupert
Eppig, Timo
Langenbucher, Achim
description The capabilities of a weighted least squares approach for the optimization of the intraocular lens (IOL) constants for the Haigis formula are studied in comparison to an ordinary least squares approach. The weights are set to the inverse variances of the effective optical anterior chamber depth. The effect of random measurement noise is simulated 100000 times using data from N = 69 cataract patients and the measurement uncertainty of two different biometers. A second, independent data set (N = 33) is used to show the differences that can be expected between both methods. The weighted least squares formalism reduces the effect of measurement error on the final constants. In more than 64% it will result in a better approximation, if the measurement errors are estimated correctly. The IOL constants can be calculated with higher precision using the weighted least squares method.
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subjects Anterior chamber
Biology and Life Sciences
Biometrics
Care and treatment
Cataracts
Cornea
Error analysis
Humans
Interferometry
Intraocular lenses
Least squares method
Lens, Crystalline
Medicine and Health Sciences
Models, Theoretical
Noise
Noise measurement
Optimization
Optometry - methods
Physical Sciences
Physiological aspects
Tomography
Transplants & implants
title Determination of Personalized IOL-Constants for the Haigis Formula under Consideration of Measurement Precision
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