[Evaluation of the management and follow-up of diabetic patients in the prevention of diabetic retinopathy]. / Evaluación del manejo y seguimiento de los pacientes diabéticos en la prevención de la retinopatía diabética.

OBJECTIVE: Diabetes mellitus is a chronic disease with high morbidity and mortality, affecting 537 million adults worldwide. Spain is the second European country in prevalence, with 14.8% in the population aged twenty/seventy-nine years; with 11.6 cases per 1,000 people/year. Diabetic retinopathy (DR) is the fifth cause of vision loss worldwide and the seventh cause of blindness/visual impairment among members of the National Organization of the Blind in Spain (ONCE). Early detection of DR prevents blindness in diabetics and is conditioned by glycosylated hemoglobin. The aim of this paper was to analyze the management of diabetic patients in Aljarafe region (Seville) and identify opportunities for improvement in the coordination of their follow-up between the Primary Care physician and the ophthalmologist. METHODS: A retrospective observational study (2016-2019) was carried out, with patients registered in the diabetic census of the twenty-eight municipalities of Aljarafe. The primary care and hospital health history, and telemedicine program were consulted. About statistical analysis, for qualitative variables, totals and percentages were calculated; for quantitative variables, mean and standard deviation (if normally distributed) and median and quartiles (if non-normally distributed). RESULTS: There were 17,175 diabetics registered in Aljarafe (5.7% of the population); 14,440 patients (84.1%) had some determination of hemoglobin during the period, 9,228 (63.9%) had all of them in the appropriate range. Fundoscopic control was performed on 12,040 diabetics (70.1%), and of those who did not, 346 (10.6%) had all of them out of range. There were 1,878 (10.9%) patients without fundoscopic or metabolic control, 1,019 (54.3%) were women, 1,219 (64.9%) were under sixty-five years of age, 1,019 (54.3%) had severe comorbidity. CONCLUSIONS: Most patients have adequate screening, and more than half have determinations within range. However, a significant percentage with no glycated hemoglobin within range lack fundoscopic control, and another smaller group lack fundoscopic or metabolic control, with inter-municipal variability. We propose to improve communication channels between levels.

OBJECTIVE: La diabetes mellitus es una enfermedad crónica con alta morbimortalidad que afecta a 537 millones de adultos en el mundo. España es el segundo país europeo en prevalencia, con un 14,8% en población de veinte-setenta y nueve años, con 11,6 casos por cada 1.000 personas/año. La retinopatía diabética (RD) es la quinta causa de pérdida de visión a nivel mundial y la séptima causa de ceguera/discapacidad visual entre afiliados a la Organización Nacional de Ciegos de España (ONCE). La detección precoz de RD previene la ceguera en diabéticos y está condicionada por la hemoglobina glicosilada. El objetivo de este trabajo fue analizar el manejo de los pacientes diabéticos en la comarca del Aljarafe (Sevilla) e identificar oportunidades de mejora en la coordinación de su seguimiento entre el médico de Atención Primaria y el médico oftalmólogo. METHODS: Se realizó un estudio observacional retrospectivo (2016-2019) con los pacientes registrados en el censo de diabéticos de los veintiocho municipios del Aljarafe. Se consultó la historia de salud de Atención Primaria y Hospital, así como el programa de Telemedicina. En cuanto al análisis estadístico, para variables cualitativas se calcularon totales y porcentajes; para variables cuantitativas, media y distribución estándar (si distribución normal), y la mediana y cuartiles (distribución no normal). RESULTS: Se registraron 17.175 diabéticos en el Aljarafe (5,7% de población); 14.440 pacientes (84,1%) tenían alguna determinación de hemoglobina durante el periodo, 9.228 (63,9%) las tenían todas en rango adecuado. Tenían control fundoscópico 12.040 diabéticos (70,1%), y de los que no, 346 (10,6%) tenían todas fuera de rango. Hubo 1.878 (10,9%) pacientes sin control fundoscópico ni metabólico, 1.019 (54,3%) eran mujeres, 1.219 (64,9%) menores de sesenta y cinco años, 1.019 (54,3%) con comorbilidad grave. CONCLUSIONS: La mayoría de los pacientes presentan un cribado adecuado y, más de la mitad, determinaciones en rango. Sin embargo, un porcentaje relevante con ninguna hemoglobina glicosilada en rango carecen de control fundoscópico, y otro grupo menor está sin control fundoscópico ni metabólico, con variabilidad intermunicipios. Planteamos mejorar los circuitos de comunicación entre niveles.

The association in diabetic retinopathy and stroke finding from NHANES evidence.

PURPOSE: Diabetic retinopathy and stroke are both vascular pathologies, and this study intends to investigate the relationship between diabetic retinopathy and stroke. METHODS: The NHANES database was used to find the relationship between diabetic retinopathy and stroke with 1948 individuals aged 40 years or older. The sensitivity of the data was verified by multiple interpolation, further analysis was done by subgroup analyses, and possible links were investigated with mediation studies. RESULTS: Diabetes retinopathy was found to be closely associated with stroke, with the PDR group having a higher stroke incidence than the NPDR group. After controlling for covariates, there were still substantial differences in the risk of stroke among patients with NPDR and PDR. Overall, subgroup analysis revealed DR group showed an important distinction, compared to the non-DR (OR = 1.76, 95% CI 1.15-2.64). The results of the mediation research indicated that the connection between DR and stroke was mediated by the frailty index and hypertension. CONCLUSION: This study demonstrated a statistically significant correlation between DR and stroke, which persisted even after DR staging and was more prevalent in PDR patients than in NPDR patients. Stroke prevention may benefit from DR health management.

Prevalence and incidence of diabetic retinopathy in patients with diabetes of Latin America and the Caribbean: A systematic review and meta-analysis.

OBJECTIVES: This systematic review aimed to assess the prevalence and incidence of diabetic retinopathy in patients with diabetes of Latin America and the Caribbean. METHODS: We searched Web of Science (WoS)/Core Collection, WoS/MEDLINE, WoS/Scielo, Scopus, PubMed/Medline and Embase databases until January 16, 2023. We meta-analyzed prevalences according to type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). RESULTS: Forty-three prevalence studies (47 585 participants) and one incidence study (436 participants) were included. The overall prevalence of retinopathy in patients with T1DM was 40.6% (95% CI: 34.7 to 46.6; I2: 92.1%) and in T2DM was 37.3% (95% CI: 31.0 to 43.8; I2: 97.7), but the evidence is very uncertain (very low certainty of evidence). In meta-regression, we found that age (T1DM) and time in diabetes (T2DM) were factors associated with the prevalence. On the other hand, one study found a cumulative incidence of diabetic retinopathy of 39.6% at 9 years of follow-up. CONCLUSIONS: Two out of five patients with T1DM or T2DM may present diabetic retinopathy in Latin America and the Caribbean, but the evidence is very uncertain. This is a major public health problem, and policies and strategies for early detection and opportunely treatment should be proposed.

Extending the diabetic retinopathy screening intervals in Singapore: methodology and preliminary findings of a cohort study.

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. Patients with referable DR/DME (> mild NPDR) or ungradable fundus images were excluded. Sociodemographic, lifestyle, medical and clinical information was obtained from medical records and interviewer-administered questionnaires at baseline. These data are extracted from medical records at 12, 24 and 36 months post-enrollment. Baseline descriptive characteristics stratified by DR severity at baseline and rates of progression to referable DR at 12-month follow-up were calculated. RESULTS: Of 5,840 eligible patients, 78.3% (n = 4,570, median [interquartile range [IQR] age 61.0 [55-67] years; 54.7% male; 68.0% Chinese) completed the baseline assessment. At baseline, 97.4% and 2.6% had none and mild NPDR (worse eye), respectively. Most participants had hypertension (79.2%) and dyslipidemia (92.8%); and almost half were obese (43.4%, BMI ≥ 27.5 kg/m2). Participants without DR (vs mild DR) reported shorter DM duration, and had lower haemoglobin A1c, triglycerides and urine albumin/creatinine ratio (all p < 0.05). To date, we have extracted 41.8% (n = 1909) of the 12-month follow-up data. Of these, 99.7% (n = 1,904) did not progress to referable DR. Those who progressed to referable DR status (0.3%) had no DR at baseline. CONCLUSIONS: In our prospective study of patients with T2DM and non-referable DR attending polyclinics, we found extremely low annual DR progression rates. These preliminary results suggest that extending screening intervals beyond 12 months may be viable and safe for most participants, although our 3-year follow up data are needed to substantiate this claim and develop the risk stratification model to identify low-risk patients with T2DM who can be assigned biennial or triennial screening intervals.

Use of Diabetes Technologies and Retinopathy in Adults With Type 1 Diabetes.

Importance: Diabetic retinopathy (DR) is a complication of diabetes that can lead to vision loss. Outcomes of continuous glucose monitoring (CGM) and insulin pump use in DR are not well understood. Objective: To assess the use of CGM, insulin pump, or both, and DR and proliferative diabetic retinopathy (PDR) in adults with type 1 diabetes (T1D). Design, Setting, and Participants: A retrospective cohort study of adults with T1D in a tertiary diabetes center and ophthalmology center was conducted from 2013 to 2021, with data analysis performed from June 2022 to April 2023. Exposure: Use of diabetes technologies, including insulin pump, CGM, and both CGM and insulin pump. Main Outcomes and Measures: The primary outcome was development of DR or PDR. A secondary outcome was the progression of DR for patients in the longitudinal cohort. Multivariable logistic regression models assessed for development of DR and PDR and association with CGM and insulin pump use. Results: A total of 550 adults with T1D were included (median age, 40 [IQR, 28-54] years; 54.4% female; 24.5% Black or African American; and 68.4% White), with a median duration of diabetes of 20 (IQR, 10-30) years, and median hemoglobin A1c (HbA1c) of 7.8% (IQR, 7.0%-8.9%). Overall, 62.7% patients used CGM, 58.2% used an insulin pump, and 47.5% used both; 44% (244 of 550) of the participants had DR at any point during the study. On univariate analysis, CGM use was associated with lower odds of DR and PDR, and CGM with pump was associated with lower odds of PDR (all P < .05), compared with no CGM use. Multivariable logistic regression adjusting for age, sex, race and ethnicity, diabetes duration, microvascular and macrovascular complications, insurance type, and mean HbA1c, showed that CGM was associated with lower odds of DR (odds ratio [OR], 0.52; 95% CI, 0.32-0.84; P = .008) and PDR (OR, 0.42; 95% CI, 0.23-0.75; P = .004), compared with no CGM use. In the longitudinal analysis of participants without baseline PDR, 79 of 363 patients (21.8%) had progression of DR during the study. Conclusions and Relevance: In this cohort study of adults with T1D, CGM use was associated with lower odds of developing DR and PDR, even after adjusting for HbA1c. These findings suggest that CGM may be useful for diabetes management to mitigate risk for DR and PDR.

No causal association between serum vitamin D levels and diabetes retinopathy: A Mendelian randomization analysis.

BACKGROUND AND AIM: Diabetes retinopathy (DR) is a common microvascular complication of diabetes, and it is the main cause of global vision loss. The current observational research results show that the causal relationship between Vitamin D and DR is still controversial. Therefore, we conducted a Mendelian randomization study to determine the potential causal relationship between serum 25-hydroxyvitamin D 25(OH)D and DR. METHODS AND RESULTS: In this study, we selected aggregated data on serum 25(OH)D levels (GWAS ID: ebi-a-GCST90000615) and DR (GWAS ID: finn-b-DM_RETINOPATHY) from a large-scale GWAS database. Then use MR analysis to evaluate the possible causal relationship between them. We mainly use inverse variance weighted (IVW), supplemented by MR Egger and weighted median methods. Sensitivity analysis is also used to ensure the stability of the results, such as Cochran's Q-test, MR-PRESSO, MR-Egger interception test, and retention method. The MR analysis results showed that there was no significant causal relationship between 25(OH)D and DR (OR = 1.0128, 95%CI=(0.9593,1.0693), P = 0.6447); Similarly, there was no significant causal relationship between DR and serum 25 (OH) D levels (OR = 0.9900, 95% CI=(0.9758,1.0045), P = 0.1771). CONCLUSION: Our study found no significant causal relationship between serum 25(OH)D levels and DR, and vice versa. A larger sample size randomized controlled trial is needed to further reveal its potential causal relationship.

Determinants of non-diabetic kidney diseases in type 2 diabetic patients: Twenty years of single center experience.

BACKGROUND: Diabetic nephropathy is one of the most common complications associated with diabetes. However, non-diabetic kidney disease has been reported in patients with type 2 diabetes at varying incidence rates. The objective of our study is to investigate the occurrence, clinicopathological characteristics, and inflammatory markers linked to diabetic and non-diabetic nephropathy (NDN) in patients with type 2 diabetes mellitus (DM). Additionally, we aimed to explore the possibility of identifying non-diabetic pathology using different biopsy indications. MATERIALS AND METHODS: A total of 159 patients with type 2 DM who underwent renal biopsy at a tertiary care nephrology clinic between January 2000 and January 2022 were enrolled in the study. We collected comprehensive data, including patient demographics, co-morbidities, diabetes duration, renal biopsy indications and results, serological markers, renal function, diabetic retinopathy (DRP), full blood count, blood biochemistry, urinalysis, and inflammatory markers. Patients were categorized based on their biopsy indications, and their biopsy results were classified into three groups: isolated NDN, isolated diabetic nephropathy (DN), and mixed nephropathy with concurrent NDN. We evaluated the relationship between biopsy indications and accompanying pathologies and statistically assessed the likelihood of each biopsy indication detecting non-diabetic renal pathology. Additionally, differences in other data, including demographic and laboratory results and medical histories, among the three groups were investigated. RESULTS: The most frequent indication of renal biopsy was atypical presentations of nephrotic syndrome or nephrotic range proteinuria (ANS/ANP) in 25.1% of patients. Other indications included unexplained renal failure (URF) in 22.6%, atypical presentations of non-nephrotic range proteinuria (ANNP) in 18.2%, acute kidney injury or rapidly progressive kidney dysfunction (AKI/RPKD) in 16.9%, microscopic hematuria in 15.7%, URF with ANNP in 11.3%, and severe nephrotic range proteinuria (SNP) in 9.4%. Renal biopsy revealed isolated NDN in 64.8%, DN in 25.1%, and mixed nephropathy in 10.1% of patients. Primary glomerular diseases were the main non-diabetic renal pathology, predominantly focal segmental glomerulosclerosis (FSGS) (36.4%) followed by MN (10.6%) and IgA nephropathy (7.5%). In comparison with the isolated DN and mixed nephropathy groups, patients in the isolated NDN group had significantly shorter diabetes duration, fewer DRP, as well as lower serum creatinine and neutrophil-to-lymphocyte ratio (NLR). Multivariate logistic regression analysis revealed that presence of hematuria (OR 4.40; 95% CI 1.34 - 14.46, p = 0.014), acute nephrotic range proteinuria (OR 11.93; 95% CI 1.56 - 90.77, p = 0.017), and AKI/APKD (OR 41.08; 95% CI 3.40 - 495.39, p = 0.003) were strong predictors of NDN. Lower NLR (OR 0.77; 95% CI 0.60 - 0.98, p = 0.035), shorter duration of diabetes (OR 0.90; 95% CI 0.84 - 0.97, p = 0.010), and absence of DRP (OR 0.35; 95% CI 0.12 - 0.98, p = 0.046) were also found to be independent indicators of NDN. Receiver operating characteristic curve (ROC) analysis revealed a cut-off value of ≤ 3.01 for NLR (sensitivity of 63.1%, specificity of 63.5%) with regards to predicting non-diabetic renal pathology (p = 0.006). CONCLUSION: Renal biopsy findings in patients with type 2 DM highlight that the prevalence of NDN may be higher than assumed, as presented mainly in the form of primary glomerular disease. The presence of AKI/RPKD, hematuria, and ANS/ANP serves as a reliable indicator of non-diabetic renal pathology. In more ambiguous situations, factors such as a shorter duration of diabetes, absence of DRP, and a lower NLR value may assist clinicians in biopsy decision.

National prevalence of vision impairment and blindness and associated risk factors in adults aged 40 years and older with known or undiagnosed diabetes: results from the SMART-India cross-sectional study.

BACKGROUND: National estimates of the prevalence of vision impairment and blindness in people with diabetes are required to inform resource allocation. People with diabetes are more susceptible to conditions such as diabetic retinopathy that can impair vision; however, these are often missed in national studies. This study aims to determine the prevalence and risk factors of vision impairment and blindness in people with diabetes in India. METHODS: Data from the SMART-India study, a cross-sectional survey with national coverage of 42 147 Indian adults aged 40 years and older, collected using a complex sampling design, were used to obtain nationally representative estimates for the prevalence of vision impairment and blindness in people with diabetes in India. Vulnerable adults (primarily those who did not have capacity to provide consent); pregnant and breastfeeding women; anyone deemed too ill to be screened; those who did not provide consent; and people with type 1 diabetes, gestational diabetes, or secondary diabetes were excluded from the study. Vision impairment was defined as presenting visual acuity of 0·4 logMAR or higher and blindness as presenting a visual acuity of 1·0 logMAR or higher in the better-seeing eye. Demographic, anthropometric, and laboratory data along with geographic distribution were analysed in all participants with available data. Non-mydriatic retinal images were used to grade diabetic retinopathy, and risk factors were also assessed. FINDINGS: A total of 7910 people with diabetes were included in the analysis, of whom 5689 had known diabetes and 2221 were undiagnosed. 4387 (55·5%) of 7909 participants with available sex data were female and 3522 (44·5%) participants were male. The estimated national prevalence of vision impairment was 21·1% (95% CI 15·7-27·7) and blindness 2·4% (1·7-3·4). A higher prevalence of any vision impairment (29·2% vs 19·6%; p=0·016) and blindness (6·7% vs 1·6%; p<0·0001) was observed in those with ungradable images. In known diabetes, diabetic retinopathy (adjusted odds ratio [aOR] 3·06 [95% CI 1·25-7·51]), vision-threatening diabetic retinopathy (aOR 7·21 [3·52-14·75]), and diabetic macular oedema (aOR 5·41 [2·20-13·33]) were associated with blindness in adjusted analysis. Common sociodemographic risk factors for vision impairment and blindness include older age, lower educational attainment, and unemployment. INTERPRETATION: Based on the estimated 101 million people with diabetes in 2021 and the interpretation of the data from this study, approximately 21 million people with diabetes have vision impairment in India, of whom 2·4 million are blind. Higher prevalence is observed in those from lower socio-economic strata and policy makers should focus on these groups to reduce inequalities in health care. FUNDING: Global Challenge Research Fund of United Kingdom Research and Innovation through the Medical Research Council.

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites.

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. METHODS: We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A1c, systolic blood pressure, and BMI. RESULTS: Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A1c, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR). CONCLUSIONS: This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.

Early change of retinal nerve fiber layer in children with type 1 diabetes mellitus in northern China.

OBJECTIVES: This study aimed to identify discrepancies in the retinal nerve fiber layer (RNFL) between type 1 diabetes mellitus (T1DM) children without retinopathy and healthy subjects in northern China. METHODS: This was a cross-sectional hospital-based study carried out from Jan 2019 until Jul 2021 at the department of pediatrics in Tianjin medical university general hospital. Children with T1DM but no retinal disease were screened. RNFL thickness was obtained via spectral domain optical coherence tomography. Disease duration, HbA1c, 25-hydroxyvitamin D level, insulin regimen, and diet control status were also collected. RESULTS: A total of 20 children with T1DM and 20 matched health participants were enrolled. The mean age in the T1DM group was 10.3 ± 2.8 years, and the median duration of diabetes was 1 (range 1-3) year. Children with T1DM had thinner average RNFL than control subjects (105 ± 6 vs. 110 ± 11 µm, p=0.008), especially in temporal and nasal parts. There was a significant negative association between HbA1c levels and the RNFL thickness in the T1DM group (B (95 % confidence interval): -4.313 (-7.055 to -1.571); p=0.005). CONCLUSIONS: In our study, the decreased thickness of RNFL was negatively associated with elevated HbA1c in children with early stages of T1DM.

Social Risk Groups in Patients With Diabetes With Differing Eye Care Utilization and Vision Outcomes.

Purpose: To evaluate whether latent class analysis on social determinants of health (SDoH) data can identify social risk groups that differ by adverse SDoH and vision outcomes in patients with diabetes. Methods: This was a prospective cohort study of adults ≥18 years with diabetes who completed a SDoH survey. Latent class analysis was used to cluster patients into social risk groups. The association of social risk group and severity of diabetic retinopathy, history of lapses in diabetic retinopathy care, and visual acuity was evaluated. Results: A total of 1006 participants were included. The three social risk groups differed by sociodemographic characteristics. The average age was 65, 60, and 54 in Groups 1, 2, and 3 respectively. Most (51%) patients in group 1 were non-Hispanic White, 66% in group 2 were non-Hispanic Black, and 80% in group 3 were Hispanic. Group 1 had the lowest burden of adverse SDoH per person (average 3.6), group 2 had 8.2, and group 3 had 10.5. In general, group 1 lacked diabetic retinopathy knowledge, group 2 had financial insecurity and difficulties with transportation, and group 3 had financial insecurity and did not have health insurance. Social risk group was associated with a history of lapses in diabetic retinopathy care, and presenting with worse vision. Conclusions and Translational Relevance: We identified distinct social risk groups among patients seeking care for diabetic retinopathy that differed by social needs, eye care utilization, and vision. Identifying these groups and their specific needs can help guide interventions to effectively address adverse SDoH and improve eye care utilization and vision outcomes among patients with diabetes.

Socioeconomic Deprivation and the Risk of Sight-Threatening Diabetic Retinopathy: A Population-Based Cohort Study in the U.K.

OBJECTIVE: To evaluate the associations between socioeconomic deprivation and sight-threatening diabetic retinopathy (STDR) in individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: Data from 175,628 individuals with diabetes in the Health Improvement Network were used to assess the risk of STDR across Townsend Deprivation Index quantiles using Cox proportional hazard regression. RESULTS: Among individuals with T1D, the risk of STDR was three times higher (adjusted hazard ratio [aHR] 2.67, 95% CI 1.05-7.78) in the most deprived quintile compared with the least deprived quintile. In T2D, the most deprived quintile had a 28% higher risk (aHR 1.28; 95% CI 1.15-1.43) than the least deprived quintile. CONCLUSIONS: Increasing socioeconomic deprivation is associated with a higher risk of developing STDR in people with diabetes. This underscores persistent health disparities linked to poverty, even within a country offering free universal health care. Further research is needed to address health equity concerns in socioeconomically deprived regions.

Association of Diabetic Retinopathy with Midlife Hepatic Steatosis Diagnosed by Elastography and Hepatic Steatosis Index in Type 2 Diabetes in an Indian Population.

Aims: People with type 2 diabetes mellitus are at increased risk of developing hepatic steatosis. We determined the prevalence of hepatic steatosis in middle-aged patients with and without diabetic retinopathy (DR) in an Indian population. We feel this information is critical, with trends of increasing chronic liver disease-related mortality at younger ages. Method: Institution-based analytical cross-sectional study with 114 middle-aged type 2 diabetes patients; 57 in each group with <15 years of duration of DM and without excessive drinking. Hepatic steatosis was determined by the hepatic steatosis index (HSI), hepatic ultrasonography (USG), and elastography. Result: The HSI in DR (37.9 ± 3.9) was more (P = 0.012) than in without diabetic retinopathy (NODR) (36.3 ± 3.3). There was no difference between two groups in liver span (P = 0.829) or in the prevalence of fatty liver (P = 0.562) as determined by conventional USG. Elastography value (kPa) was more (P = 0.001) in DR (6.51 ± 1.85) than in NODR (5.14 ± 1.60). On elastography, 50.9% in DR had a likelihood ratio (Metavir score for a stiffness value) for stage 2 Metavir score. In DR, 11.8% of those missed by USG had a likelihood ratio for ≥ stage 2 Metavir score on elastography. The presence of DR was independently correlated with kPa value (P < 0.001). Conclusion: A significantly higher prevalence of hepatic steatosis was observed in DR in this population. DR can be a useful biomarker for early hepatic screening in midlife, particularly with hepatic elastography, so that timely diagnosis of hepatic steatosis can be made.

Interpretable prediction model for assessing diabetes complication risks in Chinese sufferers.

AIMS: With growing concerns over complications in diabetes sufferers, this study sought to develop an interpretable machine learning model to offer enhanced diagnostic and treatment recommendations. METHODS: We assessed coronary heart disease, diabetic nephropathy, diabetic retinopathy, and fatty liver disease using logistic regression, decision tree, random forest, and CatBoost algorithms. The SHAP algorithm was employed to elucidate the model's predictions, offering a more in-depth understanding of influential features. RESULTS: The CatBoost model notably outperformed other algorithms in AUC, achieving an average AUC of 90.47 % for the four complications. Through SHAP analysis and visualization, we provided clear and actionable insights into risk factors, enabling better complication risk assessment. CONCLUSIONS: We introduced an innovative, interpretable complication risk model for people with diabetes. This not only offers a potent tool for healthcare professionals but also empowers sufferers with clearer self-assessment capabilities, encouraging earlier preventive actions. Further studies will underscore the model's clinical applicability.

Exposure to volatile organic compounds is a risk factor for diabetes retinopathy: a cross-sectional study.

Introduction: A few past experimental studies have indicated that exposure to volatile organic compounds (VOCs) might be a potential risk factor for diabetes retinopathy (DR). However, these findings lack substantial support from extensive epidemiological research. This large-scale cross-sectional study aimed to examine whether exposure to low levels of VOCs in the general population is associated with diabetes mellitus (DM) and DR. Methods: The analytical data was from the National Health and Nutrition Examination Survey (NHANES) dataset (2011-2018). To minimize the potential impact of gender and age on the findings, propensity score matching was utilized to align the data selection. Relationships between blood VOCs and DM and DR were assessed in a sample of 2,932 adults using the logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) models and Weighted Quantile Sum (WQS) were conducted for mixture exposure analysis. Results: The result shows VOCs were positive associated with DM and DR in US adults, as assessed by WQS model, and the calculated odd ratios (ORs) [95% confidence interval (C.I)] were 53.91(34.11 ~ 85.22) and 7.38(3.65 ~ 14.92), respectively. Among the components of VOCs, 1,2-Dibromoethane, Carbon Tetrachloride and 2,5-Dimethylfuran were positive related with the DR, and ORs (95%C.I) were 2.91(2.29 ~ 3.70), 2.86(2.25 ~ 3.65) and 2.19(1.79 ~ 2.94), respectively. BKMR model shows that there was a dose-response relationship between combined VOCs and DR, although the relationship was non-linearly. Conclusion: This study suggested that exposure to VOCs may increase the risk of DR, which had important public health implications.

The relationship between diabetic retinopathy and diabetic nephropathy in type 2 diabetes.

Context: Diabetic retinopathy (DR) and diabetic nephropathy (DN), are major microvascular complications of diabetes. DR is an important predictor of DN, but the relationship between the severity of DR and the pathological severity of diabetic glomerulopathy remains unclear. Objective: To investigate the relationship between severity of diabetic retinopathy (DR) and histological changes and clinical indicators of diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). Methods: Patients with T2DM (n=272) who underwent a renal biopsy were eligible. Severity of DR was classified as non-diabetic retinopathy, non-proliferative retinopathy, and proliferative retinopathy (PDR). Relationship between DN and DR and the diagnostic efficacy of DR for DN were explored. Results: DN had a higher prevalence of DR (86.4%) and DR was more severe. The sensitivity and specificity of DR in DN were 86.4% and 78.8%, while PDR was 26.4% and 98.5%, respectively. In DN patients, the severity of glomerular lesions (p=0.001) and prevalence of KW nodules (p<0.001) significantly increased with increasing severity of DR. The presence of KW nodules, lower hemoglobin levels, and younger age were independent risk factors associated with more severe DR in patients with DN. Conclusion: DR was a good predictor of DN. In DN patients, the severity of DR was associated with glomerular injury, and presence of KW nodules, lower hemoglobin levels and younger age were independent risk factors associated with more severe DR. Trial registration: ClinicalTrails.gov, NCT03865914.

Healthcare Resource Utilization and Costs in an At-Risk Population With Diabetic Retinopathy.

Purpose: Several investigators have suggested the cost-effectiveness of earlier screening, management of risk factors, and early treatment for diabetic retinopathy (DR). We aimed to evaluate the extent of health care utilization and cost of delayed care by insurance type in a vulnerable patient population. Methods: A retrospective analysis of patients with DR was conducted using electronic medical record (EMR) data from January 2014 to December 2020 at Denver Health Medical Center, a safety net institution. Patients were classified by disease severity and insurance status. DR-specific costs were assessed via Current Procedural Terminology (CPT) codes over a 24-month follow-up period. Results: Among the 313 patients, a higher proportion of non-English speaking patients were uninsured. Rates of proliferative DR at presentation differed across insurance groups (62% of uninsured, 42% of discount plan, and 33% of Medicare/Medicaid, P = 0.016). There was a significant difference in the total median cost between discount plan patients ($1258, interquartile range [IQR] = $0 - $5901) and both Medicare patients ($751, IQR = $0, $7148, P = 0.037) and Medicaid patients ($593, IQR = $0 - $6299, P = 0.025). Conclusions: There were higher rates of proliferative DR at presentation among the uninsured and discount plan patients and greater total median cost in discount plan patients compared to Medicare or Medicaid. These findings prioritize mitigating gaps in insurance coverage and barriers to preventative care among vulnerable populations. Translational Relevance: Advanced diabetic disease and increased downstream health care utilization and cost vary across insurance type, suggesting improved access to preventative care is needed in these specific at-risk populations.

Association of Visceral Obesity Indices With Incident Diabetic Retinopathy in Patients With Diabetes: Prospective Cohort Study.

BACKGROUND: Visceral adipose tissue plays an active role in the pathogenesis of type 2 diabetes and vascular dysfunction. The lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese VAI (CVAI) have been proposed as simple and validated surrogate indices for measuring visceral adipose tissue. However, the evidence from prospective studies on the associations between these novel indices of visceral obesity and diabetic retinopathy (DR) remains scant. OBJECTIVE: This study aimed to investigate the longitudinal associations of LAP, VAI, and CVAI with incident DR in Chinese patients with diabetes. METHODS: This was a prospective cohort study conducted in Guangzhou in southern China. We collected baseline data between November 2017 and July 2020, while on-site follow-up visits were conducted annually until January 2022. The study participants consisted of 1403 patients with a clinical diagnosis of diabetes, referred from primary care, who were free of DR at baseline. The LAP, VAI, and CVAI levels were calculated by sex-specific equations based on anthropometric and biochemical parameters. DR was assessed using 7-field color stereoscopic fundus photographs and graded according to the modified Airlie House Classification scheme. Time-dependent Cox proportional hazard models were constructed to estimate the hazard ratios with 95% CIs. Restricted cubic spline curves were fitted to examine the dose-response relationship between the 3 indices of visceral obesity and new-onset DR. Subgroup analyses were performed to investigate the potential effect modifiers. RESULTS: The mean age of study participants was 64.5 (SD 7.6) years, and over half (816/1403, 58.2%) were female. During a median follow-up of 2.13 years, 406 DR events were observed. A 1-SD increment in LAP, VAI, or CVAI was consistently associated with increased risk for new-onset DR, with a multivariable­adjusted hazard ratio of 1.24 (95% CI 1.09-1.41; P=.001), 1.22 (95% CI 1.09-1.36; P<.001), and 1.48 (95% CI 1.19-1.85; P=.001), respectively. Similar patterns were observed across tertiles in LAP (P for trend=.001), VAI (P for trend<.001), and CVAI (P for trend=.009). Patients in the highest tertile of LAP, VAI, and CVAI had an 84%, 86%, and 82% higher hazard of DR, respectively, compared to those in the lowest tertile. A nonlinear dose-response relationship with incident DR was noted for LAP and VAI (both P for nonlinearity<.05), but not for CVAI (P for nonlinearity=.51). We did not detect the presence of effect modification by age, sex, duration of diabetes, BMI, or comorbidity (all P for interaction>.10). CONCLUSIONS: Visceral obesity, as measured by LAP, VAI, or CVAI, is independently associated with increased risk for new-onset DR in Chinese patients with diabetes. Our findings may suggest the necessity of incorporating regular monitoring of visceral obesity indices into routine clinical practice to enhance population-based prevention for DR.

The use of social simulation modelling to understand adherence to diabetic retinopathy screening programs.

The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public health strategies that promote behavioral change. Our aim is to demonstrate that it is possible to simulate screening adherence behavior using computer simulations. Three versions of an agent-based model are presented using different methods to determine the agent's individual decision to adhere to screening: (a) logistic regression; (b) fuzzy logic components and (c) a combination of the previous. All versions were based on real data from 271,867 calls for diabetic retinopathy screening. The results obtained are statistically very close to the real ones, which allows us to conclude that despite having a high degree of abstraction from the real data, the simulations are very valid and useful as a tool to support decisions in health planning, while evaluating multiple scenarios and accounting for emergent behavior.