Development and validation of cataract risk calculator: An assessment and consent tool for surgeons and patients

Deus Bigirimana, Ben Au, Brad Guo, Ebrar Al Yasery, Tess Ryan, In Young Chung, Rachel Jui-Chi Li1,, Alp Atik, Catherine Green, Anton Van Heerden

Meeting:  2022 RANZCO


Date:      -

Session Title: FREE PAPERS – Cataract/Cornea/Refractive

Session Time:      -

Purpose: Various scoring systems to stratify pre- operative risk of complications during cataract surgery, including the New Zealand Cataract Risk Stratification, have been described. Their application in case selection has been shown to successfully reduce complication rates. However, the effect of the co-existence of more than one risk factor in an individual patient on the risk of complications has not been assessed. The aim of this study was to develop and validate a web-based predictive model for patient-individualised cataract risk estimation.

Methods: Data from 2011 eyes that underwent surgery between September 2019 and February 2020 were analysed. Patient demographics and ophthalmic risk factors were recorded. Logistic regression models were developed to predict cataract surgery complications based on pre-operative risk factors. Subsequent validation was performed by retrospectively calculating the probabilities of complications and comparison with the incidence of complications from 574 eyes operated between January and February 2021 at the same institution.

Results: The risk factors that were included in the model were: age, pseudoexfoliation, small pupil, dense cataract, tamsulosin use, zonular dehiscence and anterior chamber depth (measured by biometry). There was no significant difference between predicted and observed rates of any complication (7.2% vs 8.2%) or PCT (1.78% vs 1.57%), p
> 0.05. Predicted scores correlated strongly with the New Zealand Cataract Risk Stratification scores (R = 0.78, p < 0.05). Conclusion: This novel web-based calculator provides estimated individual risk of surgical complications. Its application includes enhanced informed consent, risk – based case allocation, particularly for trainee surgeons and facilitates the inclusion of complexity of case-mix when interpreting audit data.