Multivariate Regression Analysis to Predict Postoperative Refractive Astigmatism in Cataract Surgery.

Area of Science:

• Ophthalmology
• Refractive Surgery
• Biomedical Engineering

Background:

• Cataract surgery aims to restore vision, but residual astigmatism can impair outcomes.
• Accurate prediction of postoperative refractive astigmatism is crucial for successful astigmatism correction during cataract surgery.

Purpose of the Study:

• To determine the correlation between preoperative patient and ocular parameters and postoperative refractive astigmatism.
• To identify the most significant predictors of refractive astigmatism following cataract surgery.

Main Methods:

• Prospective study of 100 patients undergoing cataract surgery with a 2.4 mm clear corneal incision.
• Measurement of refractive astigmatism and total corneal astigmatism using autokerato/refractometer and Scheimpflug camera.
• Power vector analysis (J0 and J45) and multivariate linear regression to assess preoperative parameters' impact on postoperative refractive astigmatism.

Main Results:

• Total corneal astigmatism (J0 and J45) and age were significant predictors of postoperative refractive astigmatism (J0).
• Lens thickness was also a significant predictor for the oblique component (J45) of postoperative refractive astigmatism.
• Standard partial regression coefficients indicated strong contributions from total corneal astigmatism components.

Conclusions:

• Preoperative total corneal astigmatism is the primary predictor of postoperative refractive astigmatism in cataract surgery.
• Age and lens thickness also play roles, particularly in specific astigmatism components.
• These findings aid in optimizing astigmatism management during cataract surgery.