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Make in India: Normative data for automated perimetry.
Neeraj Israni1, Rwituja Thomas1, Shruti Kochar1
1Innovision Eye Care and Laser Center, Mumbai, Maharashtra; Oculoplastics Service, Vision Eye Centre, New Delhi, Delhi; Department of Ophthalmology, CHL Hospitals, Indore, Madhya Pradesh, India.
Indian Journal of Ophthalmology
|February 28, 2022
Summary
This study developed a new normative dataset for automated perimetry tailored to the Indian population. This localized data aims to improve the accuracy of visual field analysis for Indian patients.
Area of Science:
- Ophthalmology
- Medical Technology
Background:
- Existing automated perimetry normative data is largely non-Indian, potentially limiting accuracy for Indian populations.
- Developing a native normative dataset is crucial for precise visual field analysis in India.
Purpose of the Study:
- To establish normative data for automated perimetry specific to the Indian population across various age groups.
- To enhance understanding of normative values in automated perimetry for Indian individuals.
Main Methods:
- A cross-sectional study involving 6,586 healthy Indian participants (13,172 eyes) over three years.
- Visual fields were assessed using the 30-2 SITA FAST threshold algorithm on a Humphrey Field Analyzer (Model 745i).
- Normative data was calculated for age groups from 19 to 75 years, stratified by decade.
Main Results:
- Normative values were derived from healthy individuals with unaided or corrected 6/6 vision.
- The study established age-specific normative data for automated perimetry in the Indian population.
Conclusions:
- The creation of a native normative dataset offers significant value for automated perimetry.
- This localized dataset is expected to increase the accuracy of visual field analysis in Indian eyes.
