Digital Therapeutics: Exploring the Possibilities of Digital Intervention for Myopia

Artificial intelligence and digital solutions for myopia

Myopia as an uncorrected visual impairment is recognized as a global public health issue with an increasing burden on health-care systems. Moreover, high myopia increases one's risk of developing pathologic myopia, which can lead to irreversible visual impairment. Thus, increased resources are needed for the early identification of complications, timely intervention to prevent myopia progression, and treatment of complications. Emerging artificial intelligence (AI) and digital technologies may have the potential to tackle these unmet needs through automated detection for screening and risk stratification, individualized prediction, and prognostication of myopia progression. AI applications in myopia for children and adults have been developed for the detection, diagnosis, and prediction of progression. Novel AI technologies, including multimodal AI, explainable AI, federated learning, automated machine learning, and blockchain, may further improve prediction performance, safety, accessibility, and also circumvent concerns of explainability. Digital technology advancements include digital therapeutics, self-monitoring devices, virtual reality or augmented reality technology, and wearable devices - which provide possible avenues for monitoring myopia progression and control. However, there are challenges in the implementation of these technologies, which include requirements for specific infrastructure and resources, demonstrating clinically acceptable performance and safety of data management. Nonetheless, this remains an evolving field with the potential to address the growing global burden of myopia.

Effect of Atropine Eye Drops Combined with VR-Based Binocular Visual Function Balance Training for Prevention and Control of Juvenile Myopia

Purpose

This study mainly analyzes the efficacy of 0.01% atropine eye drops (low-dose atropine (LDA)) combined with virtual reality (VR)-based binocular visual function (BVF) balance training in the prevention and control of juvenile myopia.

Methods

One hundred and thirty-six juvenile myopia patients admitted between November 2018 to November 2021 were selected, including 76 cases (research group) receiving LDA + VR-based BVF balance training and 60 cases (control group) treated by LDA intervention alone. Visual acuity (VA; naked vision), ocular parameters (pupil diameter (PD), axial length (AXL), and diopter), intraocular pressure (IOP), accommodation facility, clinical efficacy, and incidence of adverse reactions were observed, compared, and analyzed in both groups.

Results

After analysis, it was found that the research group showed significantly higher naked vision and PD while statistically lower D after intervention than the corresponding preinterventional parameters than the control group. While AXL showed no statistical difference between the groups and within groups. The IOP also differed insignificantly between groups, but the post-treatment accommodation facility was better in the research group compared with the baseline (before treatment) and control group. In terms of curative effects, an obviously higher total effective rate was determined in the research group. In addition, the two groups showed no significant difference in the incidence of adverse reactions.

Conclusions

LDA + VR-based BVF balance training deserves clinical popularization, as it can prevent and control myopia among teenagers, with better adjusting effects on eye function and certain safety.