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

Cataracts are a leading cause of global blindness, with many low-resource populations having poor access to eye care. While much is known regarding surgical access and outcomes, less is understood about the initial detection of operable cataracts in low-resource settings. We performed a comprehensive literature review on existing and emerging cataract screening methods in low- and middle-income countries (LMICs). The search keywords were "cataract detection, diagnosis, assessment, and evaluation in low- and middle- income countries". 1,825 articles were identified and 62 were selected for final inclusion comprising reviews, meta-analyses, and original research studies. Only 12 studies proposed new cataract screening methods for low-income settings. We extracted data on the efficacy and cost-efficiency of these novel methods and compared them to existing conventional cataract diagnosis methods. 8 out of 12 original research works developed novel devices or imaging modalities such as low-cost ophthalmoscopes and retinal cameras for cataract detection. 7 studies leveraged non-ophthalmologist staff to test their methods, suggesting a potential benefit of employing additional personnel for cataract screening. 8 studies utilized tele-ophthalmology and artificial intelligence (AI) platforms with high cataract detection accuracy. Overall, rates of cataract diagnosis in LMICs can be increased through a multifaceted strategy involving low-cost, portable devices operated by local healthcare workers and augmented by telehealth or AI approaches. Such efforts can aid in addressing the disparity between cataract diagnosis and surgical intervention in low-resource environments. However, improvements in research infrastructure are needed to support such efforts and the ability to thoroughly evaluate new innovations.