Publications by authors named "Sabanayagam Charumathi"

Objectives: To determine the association between telomere length (TL) and age-related macular degeneration (AMD) and examine the potential variations with sex and ethnicity.

Methods: Population-based, cross-sectional study. A total of 52,083 participants from the UK Biobank were included.

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Background: The American Heart Association recently published guidelines on how to clinically identify and categorize individuals with cardiovascular-kidney-metabolic (CKM) syndrome. The extent to which CKM syndrome prevalence and prognosis differ by sex remains unknown. This study aimed to examine the impact of sex on trends in prevalence over 30 years and the long-term prognosis of CKM syndrome in the United States.

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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.

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  • The study investigates how plasma metabolites are linked to the progression of chronic kidney disease in individuals with type 2 diabetes, focusing on kidney function decline measured by eGFR slope.
  • Researchers analyzed data from over 5,000 people, identifying specific elevated levels of lipids and amino acids that influence kidney function, both positively and negatively.
  • The findings suggest that metabolite abnormalities, particularly related to fatty acids, may indicate issues with fat breakdown and are connected to the risk of worsening kidney health in diabetic patients.
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Cardiovascular disease (CVD) is the leading cause of death in Asians. We aimed to examine the validity and reliability of self-reported (SR) CVD in 6762 Chinese, Malay, and Indian adults aged 40-80 years who attended the baseline (November 2004) and 6-year follow-up visit (2011-2017) of a population-based cohort study in Singapore. CVD was defined based on the presence of existing (prevalent) or new onset (incident) cases of acute myocardial infarction (AMI) or stroke.

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  • 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).
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  • 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.
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  • The study develops a new biological ageing marker called RetiPhenoAge using deep learning algorithms that analyze retinal images to predict phenotypic age, surpassing traditional chronological age evaluations.
  • Researchers trained a convolutional neural network on retinal photographs from the UK Biobank to identify patterns linked to various health biomarkers and assess the marker’s effectiveness in predicting morbidity and mortality across three independent cohorts.
  • The study also compares RetiPhenoAge with other ageing markers and investigates its relationship with systemic health conditions and genetic factors, employing various statistical models to evaluate risks associated with mortality and illness.
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Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition.

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Purpose: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score.

Methods: Singapore Corneal Transplant Registry patients (n = 1687) who underwent DALK (n = 524) or PK (n = 1163) for optical indications (excluding endothelial diseases) were followed up for 10 years. Variable importance scores from random survival forests were used to identify variables associated with graft survival.

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  • 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.
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Purpose: To evaluate the dynamic transitions in diabetic retinopathy (DR) severity over time and associated risk factors in an Asian population with diabetes.

Design: Longitudinal cohort study METHODS: We analyzed data from 9481 adults in the Singapore Integrated Diabetic Retinopathy Screening Program (2010-2015) with linkage to death registry. A multistate Markov model adjusted for age, sex, systolic blood pressure (SBP), diabetes duration, HbA1c, and body mass index (BMI) was applied to estimate annual transition probabilities between four DR states (no, mild, moderate, and severe/proliferative) and death, and the mean sojourn time in each state.

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Background: To determine the prevalence, risk factors; and impact on patient health and economic outcomes across the laterality spectrum of multiple sensory impairment (MSI) in a multi-ethnic older Asian population.

Methods: In this population-based study of Singaporeans aged ≥ 60 years, MSI was defined as concomitant vision (visual acuity > 0.3 logMAR), hearing (pure-tone air conduction average > 25 dB), and olfactory (score < 12 on the Sniffin' Sticks test) impairments across the spectrum of laterality (any, unilateral, combination [of unilateral and bilateral], and bilateral).

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Background: Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes.

Objective: This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors.

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Background: The Diabetic Retinopathy Extended Screening Study (DRESS) aims to develop and validate a new DR/diabetic macular edema (DME) risk stratification model in patients with Type 2 diabetes (DM) to identify low-risk groups who can be safely assigned to biennial or triennial screening intervals. We describe the study methodology, participants' baseline characteristics, and preliminary DR progression rates at the first annual follow-up.

Methods: DRESS is a 3-year ongoing longitudinal study of patients with T2DM and no or mild non-proliferative DR (NPDR, non-referable) who underwent teleophthalmic screening under the Singapore integrated Diabetic Retinopathy Programme (SiDRP) at four SingHealth Polyclinics.

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Article Synopsis
  • Type 2 diabetes (T2D) is a complex disease influenced by various genetic factors and molecular mechanisms that vary by cell type and ancestry.
  • In a large study involving over 2.5 million individuals, researchers identified 1,289 significant genetic associations linked to T2D, including 145 new loci not previously reported.
  • The study categorized T2D signals into eight distinct clusters based on their connections to cardiometabolic traits and showed that these genetic profiles are linked to vascular complications, emphasizing the role of obesity-related processes across different ancestry groups.
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Background: The prevalence of chronic kidney disease (CKD) is high. Identification of cases with CKD or at high risk of developing it is important to tailor early interventions. The objective of this study was to identify blood metabolites associated with prevalent and incident severe CKD, and to quantify the corresponding improvement in CKD detection and prediction.

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  • X-chromosomal genetic variants can provide important information about differences in human traits and diseases between sexes.
  • A large-scale study analyzed kidney-related traits in nearly 909,000 individuals, finding 23 genetic loci linked to uric acid levels and estimated glomerular filtration rate (eGFR), including four new genes that may play a role in kidney function.
  • The research also discovered five novel sex-specific interactions, with variations showing different effects in males and females, and highlighted genes that are responsive to androgens (male hormones), indicating a complex relationship between sex and kidney-related genetics.
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  • Cardiovascular disease (CVD) is more common in individuals with chronic kidney disease (CKD), and retinal vessel measurements could help predict CVD risk.
  • A study involving 860 participants with CKD used a deep learning system to analyze retinal photographs and track CVD incidents over nearly a decade.
  • Results showed that both kidney function and retinal vessel narrowing are significant predictors of CVD, suggesting that these measurements can enhance risk prediction for CKD patients.
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  • Educational attainment is linked to cardiovascular health, and a large genomic study examined how it interacts with cholesterol and triglyceride levels in nearly 226,315 individuals across five population groups.
  • The study identified 18 new genetic variations related to lipid levels—nine for low-density lipoprotein (LDL), seven for high-density lipoprotein (HDL), and two for triglycerides (TG)—some of which interact with educational attainment.
  • Researchers also found five gene targets that potentially interact with FDA-approved drugs, suggesting a connection between genetics and drug responses related to lipid metabolism and overall health.
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Purpose: To examine the 6-year incidence of visual impairment (VI) and identify risk factors associated with VI in a multiethnic Asian population.

Design: Prospective, population-based, cohort study.

Participants: Adults aged ≥ 40 years were recruited from the Singapore Epidemiology of Eye Diseases cohort study at baseline.

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Introduction: Our study aimed to examine the relationship between cardiovascular diseases (CVD) with peripapillary retinal fiber layer (RNFL) and macular ganglion cell-inner plexiform layer (GCIPL) thickness profiles in a large multi-ethnic Asian population study.

Methods: 6,024 Asian subjects were analyzed in this study. All participants underwent standardized examinations, including spectral domain OCT imaging (Cirrus HD-OCT; Carl Zeiss Meditec).

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Introduction: The concomitant impact of visual impairment (VI) and cognitive impairment (CI) on health-related quality of life (HRQoL) in older adults is unclear. We aimed to determine the synergistic effect of baseline VI and CI on HRQoL decline at 6 years in multiethnic Asians.

Methods: We included Chinese, Malay, and Indian adults aged ≥60 years who participated in baseline (2004-2011) and 6-year (2011-2017) follow-up visits of the Singapore Epidemiology of Eye Diseases Study, a population-based cohort study in Singapore.

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Background And Objectives: To determine the impact of hearing impairment (HI) on health indicators in a multiethnic Singaporean population of older adults.

Research Design And Methods: In this cross-sectional, population-based study, pure-tone averages of air-conduction thresholds at 500 Hz, 1,000 Hz, 2,000 Hz, and 4,000 Hz were calculated for each ear. Eight categories of HI were defined ranging from: 1: No HI to 8: Bilateral severe HI.

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Purpose: To evaluate the relationships between chronic kidney disease (CKD) with retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness profiles of eyes in Asian and White populations.

Design: Cross-sectional analysis.

Participants: A total of 5066 Asian participants (1367 Malays, 1772 Indians, and 1927 Chinese) from the Singapore Epidemiology of Eye Diseases Study (SEED) were included, consisting of 9594 eyes for peripapillary RNFL analysis and 8661 eyes for GCIPL analysis.

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