Intraocular lens power calculation for humanitarian missions based on partial biometry

Area of Science:

• Ophthalmology
• Biomedical Engineering
• Optometry

Background:

• Cataract surgery requires accurate intraocular lens (IOL) power calculation.
• Biometric data, specifically corneal power (K) and axial length (AL), are crucial for IOL calculations.
• In developing regions, complete biometric data may be unavailable.

Purpose of the Study:

• To evaluate the utility of the correlation between K and AL for IOL power calculation when data are incomplete.
• To develop a formula for estimating K or AL using Deming regression analysis.
• To compare the accuracy of different IOL power calculation scenarios with incomplete biometric data.

Main Methods:

• A case series design was employed using retrospective data from adult cataract surgery charts.
• Deming regression analysis was used to derive a formula estimating K from AL (K = 74.56 - 1.317 × AL).
• IOL powers were calculated using hypothetical scenarios with estimated or mean population values for K or AL, and Mean Absolute Error (MAE) was calculated.

Main Results:

• The derived formula for estimating K from AL was K = 74.56 - 1.317 × AL.
• Estimating K using the formula with measured AL resulted in the lowest MAE (0.90 D) compared to other scenarios.
• When AL was unavailable, using the mean population IOL power (MAE 1.22 D) was more accurate than using mean population K with measured AL (1.55 D).

Conclusions:

• The established correlation between K and AL can significantly enhance IOL power calculation accuracy when K is unavailable.
• When AL is unavailable, relying on the mean population IOL power offers the most accurate refractive outcomes.
• These findings are particularly relevant for improving cataract surgery outcomes in resource-limited settings.