Impact of DED on the Accuracy of Preoperative Keratometry Values in the Calculation of IOL Power for Cataract Surgery.

In this study, we are investigating the potential impact of dry eye disease (DED) on the accuracy of preoperative keratometry values used in intraocular lens (IOL) power calculations for cataract surgery. Precise keratometric measurements are essential for determining the appropriate IOL power to achieve optimal postoperative refractive outcomes. However, ocular surface irregularities associated with DED-such as tear film instability, corneal epithelial disruption, and increased surface variability-may compromise the repeatability and reliability of these measurements.

We aim to examine the correlation between the severity of dry eye and the variability or inaccuracy in keratometric readings obtained through standard biometry techniques. Patients undergoing cataract surgery are being prospectively evaluated and stratified based on dry eye status using established diagnostic criteria, including patient-reported symptom questionnaires (OSDI), tear break-up time (TBUT), corneal staining patterns (Oxford grading scale), Schirmer's test values, and Meibomian Gland Evaluation (Meibomian Quality Score). Preoperative keratometry data are collected using optical biometers, and repeated measurements are analyzed for variability. IOL power calculations are compared with postoperative refractive outcomes to assess clinical significance.

By identifying potential discrepancies linked to dry eye severity, we aim to determine whether preoperative DED management could meaningfully improve measurement precision and, consequently, visual outcomes. Preliminary observations suggest that untreated or suboptimally managed DED may lead to inconsistent keratometric values, which in turn could contribute to unexpected postoperative refractive errors.

Our ultimate goal is to provide evidence-based recommendations for preoperative screening and treatment protocols for DED in cataract surgery candidates. These findings could support the development of standardized guidelines that incorporate ocular surface optimization as an essential component of pre-surgical planning, thereby enhancing surgical precision and patient satisfaction.