BACKGROUND

Diabetic retinopathy (DR) remains to be the leading cause of blindness worldwide. Traditionally, risk factors such as diabetes duration, HbA1c levels, hypertension and dyslipidemia have been closely linked to the development of this condition. However, recent research suggests that these factors account for only a portion of DR cases. Emerging studies highlight additional potential risk factors including diabetic nephropathy, insulin use, and body mass index -though data on these factors remain limited and at times contradictory. While there have been a few local studies exploring some of these variables, none have comprehensively examined how these factors collectively influence the occurrence and severity of diabetic retinopathy. This study aims to asses both the factors associated with presence and occurrence of diabetic retinopathy.

METHODOLOGY

This analytical cross-sectional study included patients with diabetes (n=201, aged 18 years and older) who underwent fundus photography at The Medical City Ortigas between January 1, 2022, and December 31, 2022. Data collection involved a thorough review of patient records, which provided demographic information and details on potential risk factors. The presence and severity of diabetic retinopathy (DR) were assessed based on fundus photography results, as interpreted by ophthalmologists. To evaluate the statistical significance of the association between risk factors and DR status, logistic regression analysis was done

RESULTS

Duration of diabetes (odds ratio [OR] 1.07; 95% CI, 1.01-1.13 per year increase), HBA1c (OR 1.4; 95% CI, 1.1-1.86),
fasting blood sugar (OR 1.4; 95% CI, 0.977-0.998), hypercholesterolemia (OR 5.02; 95% CI 1.67-16.44) and presence of
nephropathy (OR 3.39; 95% CI 1.49-8) were correlated with diabetic retinopathy.

CONCLUSION

The presence of diabetic retinopathy was significantly associated with several clinical factors. Each additional year of diabetes mellitus duration was associated with a 1.07-fold increase in the likelihood of DR. Additionally, each 1% increase in HbA1c was linked to a 1.40-fold increase in DR risk. The presence of diabetic nephropathy and hypercholesterolemia were also strong predictors, associated with a 3.39-fold and 5-fold increase in the likelihood of DR, respectively. Glycemic control, dyslipidemia and nephropathy appear to be associated with more severe forms of diabetic retinopathy. Clinicians handling diabetes patients with this patient profile should be wary of this diabetes complication.

Human ; Male ; Female ; Adolescent: 13-18 Yrs Old ; Young Adult: 19-24 Yrs Old ; Adult: 25-44 Yrs Old ; Diabetic Retinopathy ; Hospitals ; Risk ; Risk Factors ; Tertiary Care Centers

OBJECTIVES

In Asia, younger individuals (below age 45) are diagnosed to have type 2 diabetes with increased rates of obesity defined by lower BMI yet with greater visceral adiposity (waist circumference and waisthip ratios). The prevalence data on type 1 diabetes is not well established, considered to be low, but is seen to be increasing as well. This changing phenotype therefore, presents a clinical dilemma in terms of correctly classifying diabetes and deciding on the consequent appropriate treatment. Distinguishing type 1 from type 2 diabetes has become more difficult with type 2 diabetes dramatically increasing in young adults and children. This study aims to define the characteristics of diabetes among young adults in the Philippines to provide a basis for appropriate management amidst changes in diabetes phenotypes seen globally.

METHODS

In this cross-sectional analytic study, we characterized the demographic, metabolic, and autoimmune features of diabetes among young adult Filipinos aged 18 to 45 years old consulting at a tertiary referral center in Manila, Philippines. Baseline serum A1c, FBS, 75-g oral glucose tolerance test, insulin, serum C-peptide, insulin autoantibodies, leptin, adiponectin, lipid profile, and thyroid function tests were obtained from the participants and analyzed. The homeostasis model assessment (HOMA) was used to estimate the insulin sensitivity.

RESULTS

A total of 348 patients with diabetes were included, with females comprising two-thirds of the participants. The mean age at diagnosis of diabetes was 35.9±7.22 years. The mean BMI was 28.12 kg/m2, with median waist to hip ratio (WHR) of 0·93. Metabolic syndrome was found in 60% of participants and 67.82% were obese by body mass index. The mean A1c was 9.07±2.52%. Good glucose control (A1c less than 7.0%) was seen in 23% of participants  while nearly half (48%) had HbA1c which was >9.0%. The median levels of fasting insulin and C-peptide were 12.62 (range 1.33–90.42) mIU/L and 0.78 ng/mL (range 0–16.2), respectively. 

Included participants were diagnosed with diabetes within a year and as such, majority did not have any micro- or macrovascular complications. The most common diabetes complication was sensory neuropathy detected by monofilament testing, which was found in 28% of participants, followed by non-proliferative diabetic retinopathy in 13%. A history of previous diabetic ketoacidosis was found in 10 patients (2.87%). Glutamic acid decarboxylase (GAD) and insulin auto-antibodies were found in 3.2% and 19.3% of participants, respectively. Approximately half (51.73%) of the participants were insulin resistant by HOMA-IR.

CONCLUSION

In contrast with Caucasians and other Asians, diabetes among young Filipino adults is associated with lower BMI but with a similarly high visceral adiposity as shown by an elevated WHR. Metabolic syndrome with insulin resistance as defined by a variety of indices is predominant. Type 1 diabetes with autoantibodies occur in only a small fraction of this population. Data derived from this work can provide a framework for cluster analysis towards personalized management specific to this population.

Human ; Acids ; Adiponectin ; Adiposity ; Adult ; Aged ; Antibodies ; Asia ; Asian ; Asian Continental Ancestry Group ; Autoantibodies ; Body Mass Index ; C-peptide ; Carboxy-lyases ; Child ; Cluster Analysis ; Demography ; Diabetes Complications ; Diabetes Mellitus ; Diabetes Mellitus, Type 1 ; Diabetes Mellitus, Type 2 ; Diabetic Ketoacidosis ; Diabetic Retinopathy ; Diagnosis ; Fasting ; Female ; Glucose ; Glucose Tolerance Test ; Glutamate Decarboxylase ; Glutamic Acid ; Insulin ; Insulin Resistance ; Ketosis ; Leptin ; Lipids ; Metabolic Syndrome ; Obesity ; Patients ; Peptides ; Phenotype ; Philippines ; Population ; Prevalence ; Serum ; Therapeutics ; Thyroid Gland ; Thyroid Function Tests ; Young Adult

OBJECTIVE

To evaluate cone- and rod-specific nonperfusion indices (CPI, RPI) on ultrawide field fluorescein angiography (UWF-FA) and their correlation with diabetic retinopathy (DR) severity and center-involving diabetic macular edema (ciDME).

METHODS

Sixty-nine eyes of 43 patients with diabetes underwent UWF color photography (UWF-CP), UWF-FA, and macular optical coherence tomography (OCT). DR severity was graded by a masked reader on UWF-CP. UWFFA images were segmented into posterior pole (≤10 mm from fovea), mid-periphery (10–15 mm) and far periphery (>15 mm), and into the macula, within ETDRS fields and extended peripheral fields. Ischemic areas were quantified using ImageJ to calculate nonperfusion index (NPI), CPI, and RPI. ciDME was determined on OCT. Correlations were analyzed using Pearson coefficients (r).

RESULTS

DR severity correlated significantly with global NPI (r = 0.56, p < 0.0001) and across all retinal zones (r = 0.35– 0.57). Both CPI (global: r = 0.56, p < 0.0001; zones: r = 0.42–0.59) and RPI (global: r = 0.55, p < 0.0001; zones: r = 0.40–0.59) showed similar associations. ciDME presence was also correlated with NPI (global: r = 0.40, p = 0.0014; zones: r = 0.42–0.54), CPI (global: r = 0.47, p = 0.0001; zones: r = 0.32–0.55), and RPI (global: r = 0.46, p = 0.0002; zones: r = 0.33–0.54).

CONCLUSIONS

Cone- and rod-related retinal nonperfusion strongly correlate with DR severity and ciDME. UWF-FA may help identify high-risk eyes and guide surveillance of ischemia-related progression. Further studies are needed to define ischemic thresholds predictive of vision-threatening complications.

Human ; Diabetic Retinopathy ; Photoreceptor Cells, Vertebrate ; Rods And Cones ; Fluorescein Angiography ; Macular Edema ; Retinaldehyde

Introduction: Diabetic retinopathy (DRP) is the most common microvascular complication of diabetes, affecting approximately 30% of patients with type 2 diabetes and over half of those with type 1 diabetes. It remains a leading cause of preventable blindness among adults worldwide. Early stages are frequently asymptomatic, making regular diabetic eye screening essential to detect sight-threatening changes before irreversible vision loss occurs. In Malaysia, where diabetes prevalence has reached 15.6% among adults (NHMS 2023), the effective implementation of annual retinal screening is crucial. Malaysian National Clinical Practice Guidelines recommend an annual retinal screening among type 2 diabetes mellitus (T2DM) patients. This clinical audit evaluated adherence to DRP screening. Methodology: A retrospective clinical audit was conducted at Pusat Perubatan Angkatan Tentera (PPAT), Kem Sungai Besi, to evaluate compliance with national DR screening standards among adults with T2DM. Thirty eligible patient records were reviewed. Three key indicators were assessed: (1) documentation of visual acuity at diagnosis, (2) annual fundoscopy, and (3) referral for fundus photography within the preceding 12 months. Performance was benchmarked against the 80% standard. Data were analyzed descriptively. Results: The median age group was 55–59 years, with equal gender distribution. Screening adherence was substantially below target: visual acuity assessment at diagnosis, 23.3%; annual fundoscopy, 26.7%; and fundus imaging referral, 36.7%. All screening indicators were below the recommended standard. Conclusion This audit reveals a significant implementation gap between national guidelines and routine practice. Structured workflow integration and documentation reinforcement strategies need to be emphasized. Additional measures include strengthening patient education and reinforcing guideline-based practice through regular CME sessions. However, a re-audit has not yet been conducted at the time of clinical audit reporting. An ongoing evaluation will be essential to determine the effectiveness and sustainability of these interventions in reducing preventable diabetic vision loss at PPAT Sungai Besi.
Humans ; iabetes Mellitus, Type 2 ; Diabetic Retinopathy ; Clinical Audit

Diabetic retinopathy, a prevalent and vision-threatening microvascular complication of diabetes mellitus, is the leading cause of blindness among middle-aged and elderly individuals. Natural diterpenoids isolated from Siegesbeckia pubescens demonstrate potent anti-inflammatory properties. This study aimed to identify novel bioactive diterpenoids from S. pubescens and investigate their effects on oxidative stress and inflammatory responses in diabetic retinopathy, both in vitro and in vivo. Three new ent-pimarane-type diterpenoids (1-3) and six known compounds (4-9) were isolated from the aerial parts of S. pubescens. Their structures were elucidated through spectroscopic data interpretation, and absolute configurations were determined by comparing calculated and experimental electronic circular dichroism (ECD) spectra. Among these compounds, 14β,16-epoxy-ent-3β,15α,19-trihydroxypimar-7-ene (5) exhibited the most potent protective effect against high glucose and interleukin-1β (IL-1β)-stimulated human retinal endothelial cells. Mechanistically, compound 5 promoted endothelial cell survival while ameliorating oxidative stress and inflammatory response in diabetic retinopathy, both in vivo and in vitro. These findings not only suggest that diterpenoids such as compound 5 are important anti-inflammatory constituents in S. pubescens, but also indicate that compound 5 may serve as a lead compound for preventing or treating vascular complications associated with diabetic retinopathy.
Diabetic Retinopathy/metabolism* ; Humans ; Oxidative Stress/drug effects* ; Animals ; Diterpenes, Kaurane/administration & dosage* ; Asteraceae/chemistry* ; Male ; Endothelial Cells/drug effects* ; Abietanes/administration & dosage* ; Molecular Structure ; Mice ; Anti-Inflammatory Agents/chemistry* ; Plant Extracts/chemistry* ; Mice, Inbred C57BL

OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method. METHODS: WES was performed to identify potential single nucleotide polymorphism (SNP) or mutation sites in a DR pedigree comprising 10 members. A prediction model was established and validated in a cohort of 420 type 2 diabetic patients based on both genetic and demographic features. The contribution of each feature was assessed using Shapley Additive explanation analysis. The efficacies of the models with and without SNP were compared. RESULTS: WES revealed that seven SNPs/mutations ( rs116911833 in TRIM7, 1997T>C in LRBA, 1643T>C in PRMT10, rs117858678 in C9orf152, rs201922794 in CLDN25, rs146694895 in SH3GLB2, and rs201407189 in FANCC) were associated with DR. Notably, the model including rs146694895 and rs201407189 achieved better performance in predicting DR (accuracy: 80.2%; sensitivity: 83.3%; specificity: 76.7%; area under the receiver operating characteristic curve [AUC]: 80.0%) than the model without these SNPs (accuracy: 79.4%; sensitivity: 80.3%; specificity: 78.3%; AUC: 79.3%). CONCLUSION Novel SNP sites associated with DR were identified in the DR pedigree. Inclusion of rs146694895 and rs201407189 significantly enhanced the performance of the ML-based DR prediction model.
Diabetic Retinopathy/diagnosis* ; Humans ; Machine Learning ; Male ; Female ; Polymorphism, Single Nucleotide ; Middle Aged ; Exome Sequencing ; Aged ; Adult ; Pedigree ; Diabetes Mellitus, Type 2/complications* ; Genetic Predisposition to Disease ; Mutation

Diabetic retinopathy is a common blinding complication in diabetic patients. Compared with conventional fundus color photography, fundus fluorescein angiography can dynamically display retinal vessel permeability changes, offering unique advantages in detecting early small lesions such as microaneurysms. However, existing intelligent diagnostic research on diabetic retinopathy images primarily focuses on fundus color photography, with relatively insufficient research on complex lesion recognition in fluorescein angiography images. This study proposed an adaptive multi-label classification model (D-LAM) to improve the recognition accuracy of small lesions by constructing a category-adaptive mapping module, a label-specific decoding module, and an innovative loss function. Experimental results on a self-built dataset demonstrated that the model achieved a mean average precision of 96.27%, a category F1-score of 91.21%, and an overall F1-score of 94.58%, with particularly outstanding performance in recognizing small lesions such as microaneurysms (AP = 1.00), significantly outperforming existing methods. The research provides reliable technical support for clinical diagnosis of diabetic retinopathy based on fluorescein angiography.
Diabetic Retinopathy/diagnostic imaging* ; Humans ; Fluorescein Angiography ; Microaneurysm/diagnostic imaging* ; Retinal Vessels ; Algorithms

OBJECTIVE

To compare the frequency and severity of color vision defects between diabetes mellitus (DM) patients without retinopathy and those with mild non-proliferative diabetic retinopathy (NPDR), and to evaluate the relationship between these color vision defects and capillary blood glucose (CBG) levels.

METHODS

This was a cross-sectional, hospital-based study conducted over a seven-month period at the Ophthalmology Outpatient Department of Cardinal Santos Medical Center. Thirty-five (35) DM patients (70 eyes) aged 50 to 75 years with best-corrected visual acuity of ≥20/50 and no more than mild NPDR were included. Patients with moderate or severe NPDR, macular edema, optic nerve pathology, or significant cataracts were excluded. All participants underwent visual acuity testing, fundus examination, and color vision assessment using the Ishihara pseudoisochromatic plates and Farnsworth D-15 tests conducted under standardized lighting conditions. CBG was measured using the finger-prick method. Main outcome measures included the proportion and type of color vision defects, their association with DR classification, and CBG levels. Statistical analyses included descriptive statistics, the Fisher exact test, the Mann-Whitney U test for the Farnsworth D-15 Color Confusion Index (CCI), and Spearman correlation between CBG and CCI.

RESULTS

Tritan-type defects were the most common, accounting for 36.2%. Color vision defects were observed in 91.3% (64 eyes) of patients with no DR, while defects were seen in all eyes (100%) with mild NPDR (5 eyes). However, this difference was not statistically significant (p = 1.000). There was no significant correlation between CBG levels and color vision scores. Mean CCI scores were similar between groups (p = 0.394), indicating no substantial difference in defect severity.

CONCLUSIONS

Color vision defects may be more prevalent in early NPDR compared to no DR, but this difference was not significant in this sample. No correlation was found between CBG levels and color vision performance. Color vision testing may serve as a useful adjunctive screening tool for early diabetic retinal changes; however, further studies with larger sample sizes are necessary.

Human ; Color Vision Defects ; Diabetic Retinopathy

This case study describes Mrs. CS, a 57-year-old grandmother with a 3-year history of Type 2 Diabetes Mellitus (T2DM), who came from a diabetic family and presented with blurry vision and fatigue. She was also diagnosed as hypertensive last year. She reported discontinuing all prescribed medications for five months, relying instead on decoctions of the Philippine serpentina plant (Andrographis paniculata) and the insulin plant (Chamaecostus cuspidatus) for blood pressure and glycemic control due to budget constraints. An HbA1c test revealed hyperglycemia (7.5%). This case highlights the critical public health challenge of medication non-adherence in T2DM patients, particularly those influenced by traditional herbal remedies. It emphasizes the significant risks of relying on unproven therapies, the resulting poor glycemic control, and the potential for severe microvascular complications like diabetic retinopathy. The report emphasizes the urgent need for comprehensive patient and family education regarding evidence-based T2DM management, the dangers of unsupervised medication cessation, and the importance of professional medical consultation to integrate any complementary therapies safely.

Human ; Female ; Middle Aged: 45-64 Yrs Old ; Diabetes Mellitus, Type 2 ; Andrographis Paniculata ; Diabetic Retinopathy

OBJECTIVE

To assess the diagnostic accuracy of point-of-care screening using Medios™ Artificial Intelligence (AI) in the diagnosis of diabetic retinopathy (DR).

METHODS

This is a multi-center, cross-sectional, instrument validation study among adult Filipinos with Type 2 diabetes seen at Endocrine specialty clinics from May to November 2021. Retinal images were captured by a minimally trained nurse using the Remedio Fundus on Phone (FOP). Images were interpreted separately by the Medios™ AI and three retina specialists. The primary outcome measure is the accuracy of Medios™™ AI in diagnosing DR compared to retina specialists’ findings using sensitivity and specificity, predictive values, and likelihood ratios.

RESULTS

A total of 182 subjects with Type 2 diabetes were included in the study. The sensitivity and specificity of the Medios™ AI in diagnosing any DR were 73.68% (95%CI, 57.99-85.03) and 83.74% (95%CI, 79.35-87.35), respectively, compared with the retinal specialists’ findings using the same images. The positive and negative predictive values were 34.57% (95%CI, 25.12-45.41) and 96.47% (95%CI, 93.62-98.07). The positive and negative likelihood ratios were 4.53 (95%CI, 4.26 4.82) and 0.31 (95%CI, 0.26-0.38). The overall diagnostic accuracy of Medios™ AI in detecting DR was 82.69% (95%CI, 78.47-86.23).

CONCLUSION

The Medios™ AI system showed acceptable diagnostic accuracy when used as a point-of-care screening tool in detecting DR among patients with Type 2 diabetes seen at Endocrine specialty clinics. This technology can be a useful screening tool for endocrinologists as it is relatively inexpensive, safe, and easily performed. It can also shorten the lead time from screening to referral and intervention.

Human ; Diabetes Mellitus ; Diabetic Retinopathy