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Abstract Objectives The aim of the present study was to predict the vault of implantable collamer lens (ICL) using a formula established based on the preoperative parameters. Methods This retrospective study included data on 226 eyes from 114 patients(the median age and range was 27.5 ± 5.7; 18–46 years) who underwent EVO-ICL surgery between May 2021 and April 2022. Preoperative parameters, such as anterior chamber depth (ACD) horizontal angle-to-angle diameter (ATA), Crystalline lens rise (CLR), and vault (1 week after surgery) were measured by anterior segment optical coherence tomography. The axial length of eyes (AL) and white-to-white (WTW) values were measured using an IOLmaster and calipers under a slit lamp separately. Result The mean WTW, ACD, horizontal ATA diameter, CLR, AL, and vault 1 week after surgery were 11.42 ± 0.37 mm, 3.25 ± 0.25 mm, 11.72 ± 0.44 mm, 45.78 ± 175.42 μm, 27.61 ± 1.93 mm, and 586.51 ± 254.54 μm respectively. Multivariate regression analysis showed that the ICL-width, ACD (β = 0.293), ATA (β =-0.657), CLR (β =-0.157), and the anterior chamber angle in temporal side (T:ACA) (β=-0.277) were predictors of the vault size (adjusted-R2 = 0.39, P

Abstract Purpose To develop and validate a new multivariable prediction model to estimate risk of abnormal vault after EVO Implantable Collamer Lens (EVO-ICL) implantation using the preoperative parameters. Methods This retrospective study comprised 282 eyes of 143patients who underwent EVO-ICL surgery between May 2021 and April 2022. We measured preoperative parameters before surgery and vaults in 1 week after the operation using swept-source optical coherence tomography (SS-OCT). Risk factors for abnormal vault were determined by univariate and multivariate logistic regression analyses, and a nomogram was developed to forecast the risk of abnormal vault after EVO-ICL implantation. We assessed the performance of nomogram in terms of discrimination and calibration, including concordance index (C-index), receiver operating characteristic curve (ROC), area under the ROC curve (AUC), and decision curve analysis (DCA). Bootstrap resampling was used as an internal verification method. Results The logistic regression analysis revealed the independent risk factors for abnormal vault were white-to-white(WTW), anterior chamber angle(ACA), pupil size, and ICL-size, all of them were used to establish a nomogram based on multivariate logistic regression to predict the risk of abnormal vault. The C-indexes and AUC were 0.669 (95%CI, 0.605, 0.733). The calibration curves of the nomogram showed relatively small bias from the reference line, implicating an acceptable degree of confidence. The DCA indicates the potential clinical significance of the nomogram. Conclusions We developed a new multivariable prediction model to estimate risk of abnormal vault. The model shows good prediction effect and can provide assistance for clinical decision of ICL size.