Repeatability of biometric measures from the LenStar LS900 in a cataractous population

To investigate the repeatability of biometric measures and assess interactions between their uncertainties for use in an error propagation model, using patient data. Cross-sectional non-randomised study evaluating a dataset containing 969 LenStar 900 biometric measurements taken before cataract surg...

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Published inPloS one Vol. 20; no. 5; p. e0321786
Main Authors Langenbucher, Achim, Szentmáry, Nóra, Wendelstein, Jascha, Cayless, Alan, Hoffmann, Peter, Cooke, David
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 05.05.2025
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Summary:To investigate the repeatability of biometric measures and assess interactions between their uncertainties for use in an error propagation model, using patient data. Cross-sectional non-randomised study evaluating a dataset containing 969 LenStar 900 biometric measurements taken before cataract surgery. Only complete scans with at least 3 successful measurements for each eye performed on the same day were considered. For each sequence, the aggregated mean (AMEAN) and population standard deviations (ASD) were derived. The within-subject standard deviation Sw was extracted for: corneal thickness, CCT, anterior chamber depth ACD, lens thickness LT, axial length AL, corneal diameter WTW, and the keratometric power vector components equivalent power KEQ, and the projections of corneal astigmatism KC0 and KC45. Correlations between the uncertainties were assessed using Spearman rank correlations. For the 266 eyes matching the inclusion criteria, Sw was 3.6/ 24.7/35.5/ 17.7/ 107.5 µm for CCT/ ACD/ LT/ AL WTW and 0.18/ 0.12/ 0.10 dioptres for KEQ/ KC0/ KC45. The keratometric axis ASD is inversely proportional to the keratometric astigmatism AMEAN. LT and ACD uncertainties are strongly negatively correlated, with KEQ and KC0 uncertainties moderately correlated. The uncertainty and correlation data presented here could be used to define a Monte-Carlo based error propagation model mapping the biometric measures and uncertainties to variations in predicted refraction after cataract surgery. We recommend using power vector components for error propagation models since the large decay over keratometric astigmatism makes keratometric axis uncertainty unreliable.
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Competing Interests: The authors competing interests are specified in the manuscript.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0321786