Artificial intelligence (AI) models have shown great accuracy in health screening. However, for real-world implementation, high accuracy may not guarantee cost-effectiveness. Improving AI’s sensitivity finds more high-risk patients but may raise medical costs while increasing specificity reduces unnecessary referrals but may weaken detection capability. To evaluate the trade-off between AI model performance and the long-running cost-effectiveness, we conducted a cost-effectiveness analysis in a nationwide diabetic retinopathy (DR) screening program in China, comprising 251,535 participants with diabetes over 30 years. We tested a validated AI model in 1100 different diagnostic performances (presented as sensitivity/specificity pairs) and modeled annual screening scenarios. The status quo was defined as the scenario with the most accurate AI performance. The incremental cost-effectiveness ratio (ICER) was calculated for other scenarios against the status quo as cost-effectiveness metrics. Compared to the status quo (sensitivity/specificity: 93.3%/87.7%), six scenarios were cost-saving and seven were cost-effective. To achieve cost-saving or cost-effective, the AI model should reach a minimum sensitivity of 88.2% and specificity of 80.4%. The most cost-effective AI model exhibited higher sensitivity (96.3%) and lower specificity (80.4%) than the status quo. In settings with higher DR prevalence and willingness-to-pay levels, the AI needed higher sensitivity for optimal cost-effectiveness. Urban regions and younger patient groups also required higher sensitivity in AI-based screening. In real-world DR screening, the most accurate AI model may not be the most cost-effective. Cost-effectiveness should be independently evaluated, which is most likely to be affected by the AI’s sensitivity.

Purpose: To describe the development and validation of a smartphone-based visual acuity (VA) test called Vision at home (V@home). Methods: Three study populations (elderly Chinese, adolescent Chinese, and Australian groups) underwent distance and near VA testing using standard Early Treatment Diabetic Retinopathy Study (ETDRS) charts and the V@home device; all VA tests used tumbling E optotypes. VA tests were repeated with one eye, selected randomly. Distance VA was measured monocularly at 2 m, and near VA was measured binocularly at 40 cm. Participants also completed a questionnaire about their satisfaction with the device. V@home VA (logMAR) was compared to VA for ETDRS charts at distance and near and test-retest reliability. Results: The mean difference between V@home and ETDRS distance VA across all groups ranged from −0.010 to −0.100 logMAR. Tolerant weighted kappa (TWK) agreement ranged from substantial (0.742) in the Australian group to almost perfect (0.950) in the adolescent Chinese group. There was high agreement of V@home with near ETDRS VA across all groups, with a mean difference of −0.092 to −0.042 logMAR and a TWK of 0.736 to 0.837. Test-retest reliability was also high (difference: −0.018 to 0.026) for both distance and near VA tests (95% limits of agreement: −0.289 to 0.258 for distance and −0.235 to 0.199 for near). The majority of participants were satisfied with V@home. Conclusions: V@home could accurately and reliably measure both distance and near VA and is well accepted by participants. Translational Relevance: The V@home system could potentially serve as a useful tool to improve eye care accessibility, especially in underdeveloped areas with limited eye care personnel and resources.

We investigate the impact of parental myopia on spherical equivalent (SE) progression and axial length (AL) elongation. Children and their parents were invited for annual examinations from 2006 (baseline). Cycloplegic autorefraction and AL were measured at each visit. Parental refractive status was determined using refraction data from their baseline visit. Children were classified into five groups: no myopic parents (non-non), only one moderately myopic parent (non-moderate), only one highly myopic parent (non-high), two moderately myopic parents (moderate-moderate), and one moderately myopic or more severe and one highly myopic parent (moderate-high/high-high). The relationship between progression of SE and AL with parental refractive status was estimated by linear mixed-effects models. Data from 2006 to 2017 were analyzed in the current study. A total of 1831 children were enrolled (mean age, 11 ± 2.7 years; mean standard error, -0.49 ± 2.16 diopters [D] at baseline. Myopia progressed faster for children with parental myopia (non-non group as reference, all P < 0.05), while AL elongation mirrored the change in SE (all P < 0.001 except for non-mod group P = 0.12). As for the age-specific change in SE and AL, children in the mod-high/high-high group presented with the fastest progression. Children with highly myopic parents were at higher risks of being highly myopic during adulthood (odds ratio = 13.98 and 25.71 for non-high and mod-high/high-high groups; both P < 0.001). SE progresses and AL elongates at a faster rate at an earlier age in children with parental myopia. Children with highly-myopic parents have higher risks of being highly myopic during adulthood.

Objectives To investigate the longitudinal changes in intraocular pressure (IOP) and its associations with refractive error and systemic determinants in a Chinese geriatric population. Design Prospective cohort study. Setting Guangzhou Government Servant Physical Check-up Center, Guangzhou, China. Participants 4413 government employees aged no less than 40 years (41.9% female) attending annual physical and eye examinations were included in this study. The inclusion criterion was having attended the 2010 follow-up examination. The exclusion criteria include glaucoma or intraocular surgery history, IOP >21 mm Hg at any visit or without available IOP data at all visits from 2010 to 2014. Primary and secondary outcome measures The outcome measure was IOP at each follow-up visit from 2010 to 2014. Mixed-effect model was used to assess the relationship between longitudinal changes in IOP and potential risk factors. Results For the 2653 participants who had available IOP data at both the 2010 and 2014 follow-up visits, the average change in IOP was an increase of 0.43 (95% CI 0.36 to 0.50) mm Hg. For the whole study population and in the optimised mixed model, there was a non-linear increase of IOP with age (P<0.001), with greater changes in younger subjects and in women (P<0.001 and P=0.002, respectively). Elevations in systolic blood pressure, diastolic blood pressure, body mass index (BMI) and fasting plasma glucose (FPG), as well as a myopic shift (all with P<0.001), during the follow-up were associated with an increasing trend of IOP, while serum lipids were found to be not significantly associated. Conclusions In this cohort of elderly Chinese adults, IOP increases non-linearly with ageing. People with increasing blood pressure, BMI, FPG and myopic progression are more likely to have IOP elevation over time.

Background: The physical process of axial length growth among children and its role in the occurrence of myopia remain insufficiently explored. In this study, we investigate the patterns of ocular axial growth among persistent myopia (PM) and persistent non-myopia (PNM) children aged 3 to 15 years. Methods: A group of 6353 children aged 3 to 15 years, selected from rural schools in China, were followed up annually for 2 years. Biometric measurements including axial length (AL) and spherical equivalent refraction (SER) were obtained. Body height was recorded. Children were divided into two groups: PM group defined as SER of −0.50 D or less; PNM group defined as −0.50 D < SER < +3.0 D during follow-up. Results: Annual AL growth was fairly consistent for PNM eyes of children aged 3 to 11 years and then reduced significantly (independent t test, p < 0.001) for children aged 12 years and older. This pattern of AL changes was similar for PM children, although the AL growth was greater among them. Among children aged 6 and older, body height change was concomitant to AL growth (p < 0.01) and SER myopic shift (p < 0.001) until reaching 12 years old (p = 0.308 and p = 0.679, respectively). Conclusions: Stature growth and AL growth are both remarkable and consistent and concomitant but start to attenuate when the children reach 10 to 12 years old among emmetropic children. This observation suggests that AL growth is driven by physical development until 12 years old, whereas its excessive growth is dominated by myopia development.