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Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

Population-based data investigating generational differences in the risk of incident cardiovascular disease (CVD) and its risk determinants are rare. We examined the 6-year incidence of CVD and its risk factors in first- and second-generation ethnic Indians living in Singapore. 1749 participants (mean age [SD]: 55.5 [8.8] years; 47.5% male) from a population-based, longitudinal study of Indian adults were included for incident CVD outcome. Incident CVD was defined as self-reported myocardial infarction, angina pectoris or stroke which developed between baseline and follow-up. CVD-related risk factors included incident diabetes, hypertension, hyperlipidemia, obesity and chronic kidney disease (CKD). For incident CVD outcome, of the 1749 participants, 406 (23.2%) and 1343 (76.8%) were first and second-generation Indians, respectively. Of these, 73 (4.1%) reported incident CVD. In multivariable models, second-generation individuals had increased risk of developing CVD (RR = 2.04; 95% CI 1.04, 3.99; p = 0.038), hyperlipidemia (RR = 1.27; 95% CI 1.06, 1.53; p = 0.011), and CKD (RR = 1.92; 95% CI 1.22, 3.04; p = 0.005), compared to first-generation Indians. Second-generation Indians have increased risk of developing CVD and its associated risk factors such as hyperlipidemia and CKD compared to first-generation immigrants, independent of traditional CVD risk factors. More stratified and tailored CVD prevention strategies on second and subsequent generations of Indian immigrants in Singapore are warranted.

We evaluated the rate and risk factors associated with falls and recurrent falls in a multi-ethnic Asian population. 10,009 participants aged ≥40 years (mean[SD] age = 58.9[10.4] years) underwent clinical examinations and completed interviewer-administered questionnaires. Participants who self-reported at least one fall or ≥2 falls in past 12 months were defined as fallers and recurrent fallers, respectively. Age-standardized rates for falls and recurrent falls were 13.8% (95%CI, 13.1-14.6%) and 4.6% (95%CI, 4.2-5.1%), respectively. Multivariable analyses showed older age (OR = 1.20; 95%CI, 1.11-1.30), female gender (OR = 1.79; 95%CI, 1.54-2.07), diabetes (OR = 1.22; 95%CI, 1.07-1.40), cardiovascular disease (CVD, OR = 1.37; 95%CI, 1.14-1.65), ≥3 systemic comorbidities (OR = 1.35; 95%CI, 1.09-1.67), lower European Quality of Life-5 Dimensions (EQ-5D) score (OR = 1.36; 95%CI, 1.29-1.44), alcohol consumption (OR = 1.41, 95%CI, 1.11-1.78) and presenting visual impairment (VI, OR = 1.23; 95%CI, 1.02-1.47) were associated with falls. For recurrent falls, female gender (OR = 2.27; 95%CI, 1.75-2.94), diabetes (OR = 1.28; 95%CI, 1.03-1.61), CVD (OR = 2.00; 95%CI, 1.53-2.62), ≥3 systemic comorbidities (OR = 1.69; 95%CI, 1.19-2.39), lower EQ-5D score (OR = 1.47; 95%CI, 1.35-1.59), living in 1-2 room public flat (OR = 1.57; 95%CI, 1.05-2.33), monthly income <2000 Singapore Dollar (OR = 1.62; 95%CI, 1.13-2.31), alcohol consumption (OR = 1.81, 95%CI, 1.23-2.66) and presenting VI (OR = 1.34; 95%CI, 1.01-1.79) were significant risk factors. These findings will be useful for the formulation of fall prevention programs.