Publications by authors named "Tien Y Wong"
Background: To estimate the additive associations of cardiometabolic multimorbidity (CMM) and depression on long-term cognitive trajectory in multi-regional cohorts and validate the generalizability of the findings in varying clinical settings.
Method: Data harmonization was performed across 14 longitudinal cohort studies within the Cohort Studies of Memory in an International Consortium (COSMIC) group, spanning North America, South America, Europe, Africa, Asia, and Australia. Three external validation studies with distinct settings were employed to assess generalizability.
Introduction: Neovascular age-related macular degeneration is a global public-health concern, associated with a considerable burden to individuals, healthcare systems, and society. The objective of this study was to understand different perspectives on the challenges associated with the clinical management of neovascular age-related macular degeneration, which could elucidate measures to comprehensively improve clinical care and outcomes.
Methods: A survey was carried out of patients with neovascular age-related macular degeneration, their providers, and clinic staff in 77 clinics across 24 countries on six continents, from a diverse range of healthcare systems, settings, and reimbursement models.
Introduction: In contrast with patients receiving therapy for retinal disease during clinical trials, those treated in routine clinical practice experience various challenges (including administrative, clinic, social, and patient-related factors) that can often result in high patient and clinic burden, and contribute to suboptimal visual outcomes. The objective of this study was to understand the challenges associated with clinical management of diabetic macular edema from the perspectives of patients, healthcare providers, and clinic staff, and identify opportunities to improve eye care for people with diabetes.
Methods: We conducted a survey of patients with diabetic macular edema, providers, and clinic staff in 78 clinics across 24 countries on six continents, representing a diverse range of individuals, healthcare systems, settings, and reimbursement models.
Purpose: Epidemiological studies and clinical trials have reported inconsistent findings regarding the protective role of omega-3 fatty acids in age-related macular degeneration (AMD), we investigated their association in a prospective cohort and examined causality using Mendelian randomization (MR) analyses.
Design: Prospective cohort study and two-sample MR analyses.
Participants: We included individuals of European descent from UK Biobank with plasma omega-3 and docosahexaenoic acid (DHA) measurement.
We investigated whether the effect of lipid-lowering drugs (LLDs) on age-related macular degeneration (AMD) differs according to the main complement genetic variants in Singapore Epidemiology of Eye Diseases (SEED) ( = 5,579) and UK Biobank studies ( = 445,727). The effect of LLD was determined for each stratum of 20 complement genetic variants. In SEED, 484 individuals developed AMD and 216 showed progression over 6 years.
View Article and Find Full Text PDFPurpose: The purpose of this study was to investigate the effects of physical activity and inactivity on the microvasculature in children, as measured from retinal photographs.
Methods: All participants were from the Hong Kong Children Eye Study, a population-based cross-sectional study of children aged 6 to 8 years. They received comprehensive ophthalmic examinations and retinal photography.
Objective: Our objectives were to identify correlation patterns between complement and lipid pathways using a multiomics data integration approach and to determine how these interconnections affect age-related macular degeneration (AMD).
Design: Nested case-control study.
Subjects And Controls: The analyses were performed in a subset of the Singapore Indian Eye Study.
Current research and future strategies for the management of vision-threatening diabetic retinopathy.
Asia Pac J Ophthalmol (Phila)
October 2024
Article Synopsis
- Diabetic retinopathy (DR) is a serious eye complication caused by diabetes and is a leading cause of blindness, especially in working-age adults.
- The prevalence of DR is rising globally, particularly in low to middle-income countries, but much of the vision loss can be prevented with early detection and intervention.
- The review covers recent advancements in predicting DR using novel biomarkers, improving screening methods, and developing new treatment strategies to combat vision loss from conditions like diabetic macular oedema (DME).
Article Synopsis
- Scientists created a smart computer program called UWF-CKDS to help find out if someone has chronic kidney disease (CKD) using special images of the eyes.
- They tested this program with information from 23 hospitals in China and found that it worked really well.
- The program looks at tiny details in the eye that relate to kidney health, making it better than older methods at predicting CKD for many people.
Importance: Myopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings.
Objectives: To evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists.
Article Synopsis
- Genome-wide association studies have found numerous genetic loci linked to glycemic traits, but connecting these loci to specific genes and biological pathways remains a challenge.
- Researchers conducted meta-analyses of exome-array studies across four glycemic traits, analyzing data from over 144,000 participants, which led to the identification of coding variant associations in more than 60 genes.
- The study revealed significant pathways related to insulin secretion, zinc transport, and fatty acid metabolism, enhancing understanding of glycemic regulation and making data available for further research.
Background: China exited strict Zero-COVID policy with a surge in Omicron variant infections in December 2022. Given China's pandemic policy and population immunity, employing Baidu Index (BDI) to analyze the evolving disease landscape and estimate the nationwide pneumonia hospitalizations in the post Zero COVID period, validated by hospital data, holds informative potential for future outbreaks.
Methods: Retrospective observational analyses were conducted at the conclusion of the Zero-COVID policy, integrating internet search data alongside offline records.
Background: Housing has been associated with dementia risk and disability, but associations of housing with differential patterns of neuropsychiatric symptoms (NPS) among dementia-free older adults remain to be explored. The present study sought to explore the contribution of housing status on NPS and subsyndromes associated with cognitive dysfunction in community-dwelling dementia-free elderly in Singapore.
Methods: A total of 839 dementia-free elderly from the Epidemiology of Dementia in Singapore (EDIS) study aged ≥ 60 were enrolled in the current study.
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Current diagnostic modalities of AD generally focus on detecting the presence of amyloid β and tau protein in the brain (for example, positron emission tomography [PET] and cerebrospinal fluid testing), but these are limited by their high cost, invasiveness, and lack of expertise. Retinal imaging exhibits potential in AD screening and risk stratification, as the retina provides a platform for the optical visualization of the central nervous system in vivo, with vascular and neuronal changes that mirror brain pathology.
View Article and Find Full Text PDFLatest developments of generative artificial intelligence and applications in ophthalmology.
Asia Pac J Ophthalmol (Phila)
September 2024
The emergence of generative artificial intelligence (AI) has revolutionized various fields. In ophthalmology, generative AI has the potential to enhance efficiency, accuracy, personalization and innovation in clinical practice and medical research, through processing data, streamlining medical documentation, facilitating patient-doctor communication, aiding in clinical decision-making, and simulating clinical trials. This review focuses on the development and integration of generative AI models into clinical workflows and scientific research of ophthalmology.
View Article and Find Full Text PDFDeep Learning-Enabled Vasculometry Depicts Phased Lesion Patterns in High Myopia Progression.
Asia Pac J Ophthalmol (Phila)
September 2024
Article Synopsis
- - The study aimed to investigate the phases of retinal vascular changes in individuals with high myopia to better understand the underlying mechanisms of the condition's progression.
- - Researchers analyzed fundus photographs of 5,775 patients with high myopia using an intelligent image processing model to quantify various retinal vascular characteristics and compared results by age and gender.
- - Findings revealed significant differences in retinal vessel morphology between males and females, with a correlation identified between wider areas of peripapillary atrophy and reduced vascular parameters, indicating two phases of morphological change in the retinal vasculature.
Objective: Our objective was to determine the effects of lipids and complement proteins on early and intermediate age-related macular degeneration (AMD) stages using machine learning models by integrating metabolomics and proteomic data.
Design: Nested case-control study.
Subjects And Controls: The analyses were performed in a subset of the Singapore Indian Chinese Cohort (SICC) Eye Study.
Objective: The fragility index (FI) of a meta-analysis evaluates the extent that the statistical significance can be changed by modifying the event status of individuals from included trials. Understanding the FI improves the interpretation of the results of meta-analyses and can help to inform changes to clinical practice. This review determined the fragility of ophthalmology-related meta-analyses.
View Article and Find Full Text PDFArticle Synopsis
- The study develops and tests deep learning models to assess the quality of 3D macular scans from two optical coherence tomography devices, Cirrus and Spectralis.
- Researchers collected and analyzed 3D scans from over 3,800 patients, and utilized a specialized deep learning network to classify scans as gradable or ungradable.
- The models demonstrated high accuracy in internal validation and external testing, indicating they could effectively filter out low-quality scans and be integrated with disease detection systems for automated eye disease diagnosis.
Article Synopsis
- Primary diabetes care and diabetic retinopathy (DR) screening face challenges due to a lack of trained primary care physicians, especially in low-resource areas.
- The integrated image-language system, DeepDR-LLM, combines a language model and deep learning to help PCPs provide tailored diabetes management recommendations, showing comparable or better accuracy than PCPs in diagnosing DR.
- In a study, patients assisted by DeepDR-LLM demonstrated improved self-management and adherence to referral recommendations, indicating that the system enhances both care quality and patient outcomes.