Frontiers in Bioengineering and Biotechnology (Feb 2022)
Prognostic Nomograms Predicting Risk of Keratoconus in Very Asymmetric Ectasia: Combined Corneal Tomographic and Biomechanical Assessments
Abstract
Purpose: The aim of the study was to develop and validate a prognostic nomogram for subclinical keratoconus diagnosis using corneal tomographic and biomechanical integration assessments.Design: This is a retrospective case–control study.Methods:Setting: The study was carried out in a hospital setting. Patients: The study included patients with very asymmetric ectasia (VAE) and normal controls. Patients with VAE had defined clinical ectasia in one eye and normal topography (VAE-NT) in the fellow eye, and VAE-NT eyes were selected for analysis. VAE-NT was defined as stratified stage 0 using the ABCD keratoconus grading system. The normal control group was selected from corneal refractive surgery candidates at our clinic, and the right eye was enrolled. Observation Procedures: Scheimpflug-based corneal tomography (Pentacam) and corneal biomechanical assessment (Corvis ST) were performed. Main Outcome Measures: We performed multiple logistic regression analysis and constructed a simple nomogram via the stepwise method. The receiver operating characteristic (ROC) curve and discrimination and calibration of prognostic nomogram were performed by 500 bootstrap resamplings to assess the determination and clinical value, respectively.Results: A total of 59 VAE-NT and 142 normal eyes were enrolled. For differentiating normal and VAE-NT eyes, the values of specificity, sensitivity, and area under the ROC (AUROC) were 0.725, 0.610, and 0.713 for tomographic parameters, 0.886, 0.632, and 0.811 for biomechanical parameters, and 0.871, 0.754, and 0.849 for combined parameters, respectively. Combined parameters showed better predictability than separated tomographic or biomechanical parameters.Conclusion: Our nomogram developed with combined tomographic and biomechanical parameters demonstrated a plausible, capable, and widely implementable tool to predict risk of keratoconus. The identification of at-risk patients can provide advanced strategies to epitomize ectasia susceptibility.
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