A Risk Score System for Myopia Symptom Warning

Myopia progression risk assessment score (MPRAS): a promising new tool for risk stratification

Timely identification of individuals "at-risk" for myopia progression is the leading requisite for myopia practice as it aids in the decision of appropriate management. This study aimed to develop 'myopia progression risk assessment score' (MPRAS) based on multiple risk factors (10) to determine whether a myope is "at-risk" or "low-risk" for myopia progression. Two risk-score models (model-1: non-weightage, model-2: weightage) were developed. Ability of MPRAS to diagnose individual "at-risk" for myopia progression was compared against decision of five clinicians in 149 myopes, aged 6-29 years. Using model-1 (no-weightage), further 7 sub-models were created with varying number of risk factors in decreasing step-wise manner (1a: 10 factors to 1g: 4 factors). In random eye analysis for model-1, the highest Youden's J-index (0.63-0.65) led to the MPRAS cut-off score of 41.50-43.50 for 5 clinicians with a sensitivity ranging from 78 to 85% and specificity ranging from 79 to 87%. For this cut-off score, the mean area under the curve (AUC) between clinicians and the MPRAS model ranged from 0.89 to 0.90. Model-2 (weighted for few risk-factors) provided similar sensitivity, specificity, and AUC. Sub-model analysis revealed greater AUC with high sensitivity (89%) and specificity (94%) in model-1g that has 4 risk factors compared to other sub-models (1a-1f). All the MPRAS models showed good agreement with the clinician's decision in identifying individuals "at-risk" for myopia progression.

Research trends and hotspots in the relationship between outdoor activities and myopia: A bibliometric analysis based on the web of science database from 2006 to 2021

Objectives

This study aimed to explore the current status, hotspots, and emerging research trends regarding the relationship between outdoor activities and myopia.

Methods

Publications on the relationship between outdoor activities and myopia from 2006 to 2021 were collected from the Web of Science Core Collection database. CiteSpace (version 6.1.R2) was used to performed a bibliometric analysis, and R software (version 4.1.0) was used to visualize the trends and hot map of publications.

Results

A total of 640 publications were collected and analyzed in the present study. China was the major contributor (n = 204), followed by the United States of America (n = 181) and Australia (n = 137). The United States of America had the most extensive foreign cooperation (centrality = 0.25), followed by Australia (centrality = 0.20). The National University of Singapore contributed the largest number of publications (n = 48), followed by Sun Yat-Sen University (n = 41) and the Australian National University (n = 41). Among institutions, Cardiff University in the United Kingdom had the most extensive foreign cooperation (centrality = 0.12), followed by the National University of Singapore (centrality = 0.11). Saw S from Singapore had the largest number of publications (n = 39), followed by Morgan I from Australia (n = 27) and Jonas J from Germany (n = 23). Investigative ophthalmology & visual science is the most important journal to study the relationship between outdoor activities and myopia. "Global Prevalence of Myopia and High Myopia and Temporal Trends from 2000 through 2050" published by Holden BA was the most cited paper in this field with 177 citations. Co-occurrence and burst analyses of keywords showed that research trends and hotspots in this field focused mainly on "risk," "prevention" and "school".

Conclusions

The influence of outdoor activities on myopia remains a concern. In the future, deeper cooperation between countries or institutions is required to explore the effects of outdoor activities on myopia. Outdoor activities for the prevention of myopia and reduction of the risk of myopia among school students may be the focus of future research.

Myopia prediction: a systematic review

Myopia is a leading cause of visual impairment and has raised significant international concern in recent decades with rapidly increasing prevalence and incidence worldwide. Accurate prediction of future myopia risk could help identify high-risk children for early targeted intervention to delay myopia onset or slow myopia progression. Researchers have built and assessed various myopia prediction models based on different datasets, including baseline refraction or biometric data, lifestyle data, genetic data, and data integration. Here, we summarize all related work published in the past 30 years and provide a comprehensive review of myopia prediction methods, datasets, and performance, which could serve as a useful reference and valuable guideline for future research.