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Prediction of effective Lens position using anterior segment optical coherence tomography in Chinese subjects with angle closure

PURPOSE: To assess the accuracy of biometric parameters measured by anterior segment optical coherence tomography (AS-OCT) and partial coherence interferometry (PCI) in prediction of effective lens position (ELP) compared with previous formulas in PACG patients. METHODS: 121 PACG eyes were randomly...

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Detalles Bibliográficos
Autores principales: Wu, Yuzhou, Zhang, Shunhua, Zhong, Yong, Bian, Ailing, Zhang, Yang, Wang, Zaowen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8711180/
https://www.ncbi.nlm.nih.gov/pubmed/34961542
http://dx.doi.org/10.1186/s12886-021-02213-w
Descripción
Sumario:PURPOSE: To assess the accuracy of biometric parameters measured by anterior segment optical coherence tomography (AS-OCT) and partial coherence interferometry (PCI) in prediction of effective lens position (ELP) compared with previous formulas in PACG patients. METHODS: 121 PACG eyes were randomly divided into training set (85 eyes) and validation set (36 eyes) with same procedure including AS-OCT, PCI, phacoemulsification and IOL implantation surgery. Preoperative anterior chamber depth (pre-ACD), scleral spur depth (SSD), scleral spur width (SSW), lens vault (LV) and cornea thickness (CT) were measured from AS-OCT image. Axial length (AL) and corneal power (K) were measured by PCI. All the 7 parameters were analyzed by multiple linear regression in training set and a statistic regression formula was developed. In validation set, one-way ANOVA was applied to compare the new regression formula with Sanders-Retzlaff-Kraff theoretic (SRK/T), Holladay 1, Haigis, and a regression formula developed in previous study. RESULTS: The coefficient of determination (R(2)) of different parameter combinations are 0.19 (pre-ACD, AL), 0.25 (AL, K) and 0.49 (SSD, AL, SSW) in training set. In validation set, the correlation between predicted and measured ELP are: new formula (R(2) = 0.50, P = 0.9947) Holladay 1 (R(2) = 0.12, P < 0.0001), SRK/T (R(2) = 0.11, P < 0.0001) and Haigis (R(2) = 0.06, P < 0.0001). CONCLUSION: Among 7 tested parameters, pre-ACD contribute little in ELP prediction. Formula consist of SSD, AL and SSW showed better accuracy than other formulas tested.