Tools and methods for cataract recognition in low-resource settings: A narrative review

Area of Science:

• Ophthalmology
• Public Health
• Medical Technology

Background:

• Cataracts are a primary cause of blindness globally, particularly in low-resource populations with limited eye care access.
• Understanding initial operable cataract detection in low-resource settings is crucial but less explored than surgical outcomes.

Purpose of the Study:

• To conduct a comprehensive literature review on existing and emerging cataract screening methods in low- and middle-income countries (LMICs).
• To evaluate the efficacy and cost-efficiency of novel cataract detection methods compared to conventional approaches.

Main Methods:

• Systematic literature search using keywords: "cataract detection, diagnosis, assessment, and evaluation in low- and middle- income countries".
• Inclusion of 62 articles (reviews, meta-analyses, original research) from 1,825 identified.
• Data extraction on efficacy and cost-efficiency of 12 novel screening methods for low-income settings.

Main Results:

• Eight novel methods involved low-cost devices like ophthalmoscopes and retinal cameras.
• Seven studies demonstrated the effectiveness of using non-ophthalmologist staff for screening.
• Eight studies reported high cataract detection accuracy using tele-ophthalmology and artificial intelligence (AI).

Conclusions:

• A multifaceted strategy combining low-cost, portable devices, local healthcare workers, and AI/telehealth can increase cataract diagnosis rates in LMICs.
• These integrated approaches can help address the disparity between cataract diagnosis and surgical intervention.
• Enhanced research infrastructure is necessary to support and evaluate innovations in cataract screening.