Do we have enough ophthalmologists to manage vision-threatening diabetic retinopathy? A global perspective.
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ABSTRACT:
SUBMITTER: Teo ZL
PROVIDER: S-EPMC7314752 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background/aimsTo determine if anaemia and oxygen delivery-related co-morbidities (ODCs) affect progression from non-proliferative diabetic retinopathy (NPDR) to vision-threatening diabetic retinopathy (VTDR).MethodsThis is a retrospective cohort study using medical claims data from a large US insurer. Cohorts were created from all NPDR patients between 2002 and 2016. Primary exclusion criteria consisted of any previous diagnosis of proliferative diabetic retinopathy (PDR), diabetic macular oedema (DME) or treatment used in the care of VTDR. The main outcome was a new diagnosis of VTDR (DME or PDR), PDR, or DME. A time-dependent, multivariate Cox proportional hazard regression was used to determine the association between anaemia and other ODCs with NPDR progression.ResultsOf the total 69,982 NPDR patients included for analysis, 12,270, 2,162, and 10,322 progressed to VTDR, PDR and DME, respectively. Both mild and moderate/severe (mod/sev) anaemia were associated with an increased hazard for progression to VTDR (mild HR:1.10, 95% CI:1.04-1.16, p < 0.001; mod/sev HR:1.20, 95% CI:1.12-1.29, p < 0.001), PDR (mild HR:1.29, 95% CI:1.13-1.46, p < 0.001; mod/sev HR:1.43, 95% CI:1.21-1.69, p < 0.001), and DME (mild HR:1.06, 95% CI:1.00-1.13, p < 0.001; mod/sev HR:1.14, 95% CI:1.05-1.24, p < 0.001). ODCs such as chronic pulmonary disease and history of blood disorder/cancer were also significantly associated with an increased hazard for NPDR progression (HR > 1.00, p < 0.001 for all comparisons).ConclusionsAnaemia, independent of kidney disease, appears to play a significant role in progression from NPDR to VTDR, PDR, or DME. Concurrently, association of ODCs with NPDR progression lends support to the underlying mechanisms of anaemia in the pathogenesis of diabetic retinopathy.
| S-EPMC7182576 | biostudies-literature
Project description:ImportanceDiabetic retinopathy is the leading cause of blindness in working-age adults. Studies have suggested that statins may reduce the risk of developing diabetic retinopathy.ObjectiveTo investigate the association between statin therapy and the development of diabetic retinopathy in patients with diabetes and dyslipidemia.Design, setting, and participantsThis population-based cohort study, conducted among 37 894 Taiwanese patients between January 1, 1998, and December 31, 2013, used the National Health Insurance Research Database to identify patients with type 2 diabetes and dyslipidemia. Outcomes were compared between those taking statins and those not taking statins. Statistical analysis was performed from May 1 to 31, 2018.ExposureStatin therapy with a medication possession rate of 80% or more with no other lipid-lowering medications.Main outcomes and measuresAny stage of diabetic retinopathy and treatments for vision-threatening diabetic retinopathy.ResultsOf 1 648 305 patients with type 2 diabetes, 219 359 were eligible for analysis over the study period, including 199 760 patients taking statins and 19 599 patients not taking statins. After propensity score matching, there were 18 947 patients in the statin group (10 436 women and 8511 men; mean [SD] age, 61.5 [10.8] years) and 18 947 patients in the nonstatin group (10 430 women and 8517 men; mean [SD] age, 61.0 [11.0] years), with a mean follow-up of 7.6 years for the statin group and 7.3 years for the nonstatin group. During the study period, 2004 patients in the statin group (10.6%) and 2269 patients in the nonstatin group (12.0%) developed diabetic retinopathy. Patients in the statin group had a significantly lower rate of diabetic retinopathy (hazard ratio [HR], 0.86; 95% CI, 0.81-0.91), nonproliferative diabetic retinopathy (HR, 0.92; 95% CI, 0.86-0.99), proliferative diabetic retinopathy (HR, 0.64; 95% CI, 0.58-0.70), vitreous hemorrhage (HR, 0.62; 95% CI, 0.54-0.71), tractional retinal detachment (HR, 0.61; 95% CI, 0.47-0.79), and macular edema (HR, 0.60; 95% CI, 0.46-0.79) than the nonstatin group, as well as lower rates of interventions such as retinal laser treatment (HR, 0.71; 95% CI, 0.65-0.77), intravitreal injection (HR, 0.74; 95% CI, 0.61-0.89), and vitrectomy (HR, 0.58; 95% CI, 0.48-0.69), along with a smaller number of the interventions (retinal lasers: rate ratio, 0.61; 95% CI, 0.59-0.64; intravitreal injections: rate ratio, 0.68; 95% CI, 0.61-0.76; and vitrectomies: rate ratio, 0.54; 95% CI, 0.46-0.63). Statin therapy was also associated with lower risks of major adverse cardiovascular events (HR, 0.81; 95% CI, 0.77-0.85), new-onset diabetic neuropathy (HR, 0.85; 95% CI, 0.82-0.89), and new-onset diabetic foot ulcers (HR, 0.73; 95% CI, 0.68-0.78).Conclusions and relevanceStatin therapy was associated with a decreased risk of diabetic retinopathy and need for treatments for vision-threatening diabetic retinopathy in Taiwanese patients with type 2 diabetes and dyslipidemia.
| S-EPMC6459113 | biostudies-literature
Project description:PurposeThis study aims to assess the effect of statins on progression from nonproliferative diabetic retinopathy (NPDR) to vision-threatening diabetic retinopathy (VTDR), proliferative diabetic retinopathy (PDR) or diabetic macular edema (DME).MethodsTwo cohort studies using a U.S. medical claims database from 2002 to 2019 including NPDR patients 18 years or older. A risk factor analysis performed a time-updating cox regression model assessing statin usage. A second new-user active comparator design analysis replicating a previously published study. Main outcomes included a new diagnosis of VTDR (composite of either PDR or DME) or DME and PDR individually for the risk factor study and included additional outcomes of new DR, NPDR, vitreous hemorrhage (VH) and tractional retinal detachment (TRD) for the new user study.ResultsRisk factor analysis included 66 617 statin users with NPDR at baseline and 83 365 nonstatin users. Of these, 27 325 (18.2%) progressed to VTDR, 4086 (2.71%) progressed to PDR, and 22 750 (15.1%) progressed to DME. After multivariable analysis, no protective effect of statin use was found for progression to VTDR, PDR, or DME (HR = 1.01-3, p >0.33 for all comparisons). Replicated new user design analysis also showed no protective effect for statins on risk of development of DR (HR = 1.03, 95% CI: 0.99-1.07, p = 0.13), PDR (HR = 0.89, 95% CI: 0.79-1.02, p = 0.09), DME (HR = 0.94, 95% CI: 0.86-1.03, p = 0.21), VH (HR = 1.00, 95% CI: 0.86-1.16, p = 0.99), and TRD (HR = 1.11, 95% CI: 0.89-1.38, p = 0.36).ConclusionStatin use was found not to be protective for progression of DR regardless of study methodology. These results suggest that the specifics of the population studied rather than differing study methodology are important in assessing the effect of statins on DR progression.
| S-EPMC10210055 | biostudies-literature
Project description:AimsTo evaluate the performance of the RETeval device, a handheld instrument using flicker electroretinography (ERG) and pupillography on undilated subjects with diabetes, to detect vision-threatening diabetic retinopathy (VTDR).MethodsPerformance was measured using a cross-sectional, single armed, non-interventional, multi-site study with Early Treatment Diabetic Retinopathy Study 7-standard field, stereo, color fundus photography as the gold standard. The 468 subjects were randomized to a calibration phase (80%), whose ERG and pupillary waveforms were used to formulate an equation correlating with the presence of VTDR, and a validation phase (20%), used to independently validate that equation. The primary outcome was the prevalence-corrected area under the receiver operating characteristic (ROC) curve for the detection of VTDR.ResultsThe area under the ROC curve was 0.86 for VTDR. With a sensitivity of 83%, the specificity was 78% and the negative predictive value was 99%. The average testing time was 2.3 min.ConclusionsWith a VTDR prevalence similar to that in the U.S., the RETeval device will identify about 75% of the population as not having VTDR with 99% accuracy. The device is simple to use, does not require pupil dilation, and has a short testing time.
| S-EPMC4853922 | biostudies-literature
Project description:ImportanceDiabetic retinopathy (DR) may progress from nonproliferative DR (NPDR) to vision-threatening DR (VTDR). Studies have investigated fenofibrate use as a protective measure with conflicting results, and fenofibrate is not typically considered by ophthalmologists in the management of DR currently.ObjectiveTo assess the association between fenofibrate use and the progression from NPDR to VTDR, proliferative DR (PDR), or diabetic macular edema (DME).Design, setting, and participantsThis multicenter cohort study used medical claims data from a large US insurer. Cohorts were created from all patients with NPDR 18 years or older who had laboratory values from January 1, 2002, to June 30, 2019. Exclusion criteria consisted of any previous diagnosis of PDR, DME, proliferative vitreoretinopathy, or treatment used in the care of VTDR. Patients were also excluded if they had a diagnosis of VTDR within 2 years of insurance plan entry, regardless of when NPDR was first noted in the plan.ExposuresFenofibrate use.Main outcomes and measuresThe main outcomes were a new diagnosis of VTDR (a composite outcome of either PDR or DME) or DME and PDR individually. A time-updating model for all covariates was used in multivariate Cox proportional hazard regression to determine hazards of progressing to an outcome. Additional covariates included NPDR severity scale, systemic illnesses, demographics, kidney function (based on estimated glomerular filtration rate level), hemoglobin A1c, hemoglobin, and insulin use.ResultsA total of 5835 fenofibrate users with NPDR at baseline (mean [SD] age, 65.3 [10.4] years; 3564 [61.1%] male; 3024 [51.8%] White) and 144 417 fenofibrate nonusers (mean [SD] age, 65.7 [12.3] years; 73 587 [51.0%] male; 67 023 [46.4%] White) were included for analysis. Of these, 27 325 (18.2%) progressed to VTDR, 4086 (2.71%) progressed to PDR, and 22 750 (15.1%) progressed to DME. After controlling for all covariates, Cox model results showed fenofibrates to be associated with a decreased risk of VTDR (hazard ratio, 0.92 [95% CI, 0.87-0.98]; P = .01) and PDR (hazard ratio, 0.76 [95% CI, 0.64-0.90]; P = .001) but not DME (hazard ratio, 0.96 [95% CI, 0.90-1.03]; P = .27).Conclusions and relevanceIn this study, fenofibrate use was associated with a decreased risk of PDR and VTDR but not DME alone. These findings support the rationale for additional clinical trials to determine if these associations may be representative of a causal relationship between fenofibrate use and reduced risk of PDR or VTDR.
| S-EPMC8990357 | biostudies-literature
Project description:We sought to evaluate the performance of machine learning prediction models for identifying vision-threatening diabetic retinopathy (VTDR) in patients with type 2 diabetes mellitus using only medical data from data warehouse. This is a multicenter electronic medical records review study. Patients with type 2 diabetes screened for diabetic retinopathy and followed-up for 10 years were included from six referral hospitals sharing same electronic medical record system (n = 9,102). Patient demographics, laboratory results, visual acuities (VAs), and occurrence of VTDR were collected. Prediction models for VTDR were developed using machine learning models. F1 score, accuracy, specificity, and area under the receiver operating characteristic curve (AUC) were analyzed. Machine learning models revealed F1 score, accuracy, specificity, and AUC values of up 0.89, 0.89.0.95, and 0.96 during training. The trained models predicted the occurrence of VTDR at 10-year with F1 score, accuracy, and specificity up to 0.81, 0.70, and 0.66, respectively, on test set. Important predictors included baseline VA, duration of diabetes treatment, serum level of glycated hemoglobin and creatinine, estimated glomerular filtration rate and blood pressure. The models could predict the long-term occurrence of VTDR with fair performance. Although there might be limitation due to lack of funduscopic findings, prediction models trained using medical data can facilitate proper referral of subjects at high risk for VTDR to an ophthalmologist from primary care.
| S-EPMC9119940 | biostudies-literature
Project description:ImportanceDiabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; however, many patients do not receive their recommended annual diabetic eye examinations, primarily owing to limited access.ObjectiveTo evaluate the safety and accuracy of an artificial intelligence (AI) system (the EyeArt Automated DR Detection System, version 2.1.0) in detecting both more-than-mild diabetic retinopathy (mtmDR) and vision-threatening diabetic retinopathy (vtDR).Design, setting, and participantsA prospective multicenter cross-sectional diagnostic study was preregistered (NCT03112005) and conducted from April 17, 2017, to May 30, 2018. A total of 942 individuals aged 18 years or older who had diabetes gave consent to participate at 15 primary care and eye care facilities. Data analysis was performed from February 14 to July 10, 2019.InterventionsRetinal imaging for the autonomous AI system and Early Treatment Diabetic Retinopathy Study (ETDRS) reference standard determination.Main outcomes and measuresPrimary outcome measures included the sensitivity and specificity of the AI system in identifying participants' eyes with mtmDR and/or vtDR by 2-field undilated fundus photography vs a rigorous clinical reference standard comprising reading center grading of 4 wide-field dilated images using the ETDRS severity scale. Secondary outcome measures included the evaluation of imageability, dilated-if-needed analysis, enrichment correction analysis, worst-case imputation, and safety outcomes.ResultsOf 942 consenting individuals, 893 patients (1786 eyes) met the inclusion criteria and completed the study protocol. The population included 449 men (50.3%). Mean (SD) participant age was 53.9 (15.2) years (median, 56; range, 18-88 years), 655 were White (73.3%), and 206 had type 1 diabetes (23.1%). Sensitivity and specificity of the AI system were high in detecting mtmDR (sensitivity: 95.5%; 95% CI, 92.4%-98.5% and specificity: 85.0%; 95% CI, 82.6%-87.4%) and vtDR (sensitivity: 95.1%; 95% CI, 90.1%-100% and specificity: 89.0%; 95% CI, 87.0%-91.1%) without dilation. Imageability was high without dilation, with the AI system able to grade 87.4% (95% CI, 85.2%-89.6%) of the eyes with reading center grades. When eyes with ungradable results were dilated per the protocol, the imageability improved to 97.4% (95% CI, 96.4%-98.5%), with the sensitivity and specificity being similar. After correcting for enrichment, the mtmDR specificity increased to 87.8% (95% CI, 86.3%-89.5%) and the sensitivity remained similar; for vtDR, both sensitivity (97.0%; 95% CI, 91.2%-100%) and specificity (90.1%; 95% CI, 89.4%-91.5%) improved.Conclusions and relevanceThis prospective multicenter cross-sectional diagnostic study noted safety and accuracy with use of the EyeArt Automated DR Detection System in detecting both mtmDR and, for the first time, vtDR, without physician assistance. These findings suggest that improved access to accurate, reliable diabetic eye examinations may increase adherence to recommended annual screenings and allow for accelerated referral of patients identified as having vtDR.
| S-EPMC8593763 | biostudies-literature
Project description:PurposeTo evaluate the sensitivity and specificity of a portable non-mydriatic fundus camera to diagnose vision-threatening diabetic retinopathy (VTDR).Patients and methodsA prospective, single-site, comparative instrument validation study was undertaken at the Aravind Eye Care System. Overall, 155 subjects with and without diabetes were recruited. Images from 275 eyes were obtained with the (1) non-mydriatic Smartscope, (2) mydriatic Smartscope, and (3) mydriatic table-top camera of the macular, nasal, and superotemporal fields. A retina specialist performed a dilated fundus examination (DFE), (reference standard). Two masked retina specialists graded the images. Sensitivity and specificity to detect VTDR with the undilated Smartscope was calculated compared to DFE.ResultsGraders 1 and 2 had a sensitivity of 93% (95% confidence interval (CI): 87-97%) and 88% (95% CI: 81-93%) and a specificity of 84% (95% CI: 77-89%) and 90% (95% CI: 84-94%), respectively, in diagnosing VTDR with the undilated Smartscope compared to DFE. Compared with the dilated Topcon images, graders 1 and 2 had sensitivity of 88% (95% CI: 81-93%) and 82% (95% CI: 73-88%) and specificity of 99% (95% CI: 96-100%) and 99% (95% CI: 95-100%).ConclusionsRemote graders had high sensitivity and specificity in diagnosing VTDR with undilated Smartscope images, suggesting utility where portability is a necessity.
| S-EPMC5811716 | biostudies-literature
Project description:PurposeTo investigate the association between serum uric acid (SUA) levels and vision-threatening diabetic retinopathy (VTDR) in patients with type 2 diabetes.MethodsThis cross-sectional study evaluated 3481 patients with type 2 diabetes from four communities in China between 2016 and 2019. VTDR was defined as severe nonproliferative, proliferative diabetic retinopathy, or clinically significant macular edema evaluated by fundus photography and optical coherence tomography. Potential association between SUA and VTDR was examined using multivariable logistic regression. Sub-group analyses based on sex were constructed.ResultsA total of 305 participants had VTDR. Both higher SUA (odds ratio [OR], 1.22 per 100 µmol/L; 95% confidence interval [CI], 1.04-1.44; P = 0.013) and hyperuricemia (OR, 1.47; 95% CI, 1.07-2.04; P = 0.019) were positively associated with VTDR after adjustment for relevant covariates. Compared with those in the lowest SUA quartile, participants in the third (OR, 1.60; 95% CI, 1.07-2.39; P = 0.022) and fourth (OR, 2.05; 95% CI, 1.37-3.08; P = 0.001) sex-specific SUA quartiles showed a significantly increased risk of VTDR after adjustment. No sex-related difference was observed.ConclusionsHigher SUA levels were associated with an increased risk of VTDR in patients with type 2 diabetes in both sexes, although females seemed to be more sensitive to high SUA than males. Prospective cohort studies are needed to verify SUA as a biomarker for predicting the risk of VTDR. Whether decreased SUA levels could decrease the risk of VTDR also requires further investigation.
| S-EPMC8083112 | biostudies-literature
Project description:BackgroundAccumulating evidence has suggested a link between adipokines and diabetic retinopathy (DR). This study is aimed at investigating the risk factors for sight-threatening DR (STDR) and establishing a prognostic model for predicting STDR among a high-risk population of patients with type 2 diabetes mellitus (T2DM).MethodsPlasma concentrations of adipokines were determined by enzyme-linked immunosorbent assay. In the case-control set, principal component analysis (PCA) was performed to select optimal predictive cytokines for STDR, involving severe nonproliferative DR (NPDR) and proliferative DR. Support vector machine (SVM) was used to examine the possible combination of baseline plasma adipokines to discriminate the patients with mild NPDR who will later develop STDR. An individual prospective cohort with a follow-up period of 3 years was used for the external validation.ResultsIn both training and testing sets, involving 306 patients with T2DM, median levels of plasma adiponectin (APN), leptin, and fatty acid-binding protein 4 (FABP4) were significantly higher in the STDR group than those in mild NPDR. Except for adipsin, the other three adipokines, FABP4, APN, and leptin, were selected by PCA and integrated into SVM. The accuracy of the multivariate SVM classification model was acceptable in both the training set (AUC = 0.81, sensitivity = 71%, and specificity = 91%) and the testing set (AUC = 0.77, sensitivity = 61%, and specificity = 92%). 110 T2DM patients with mild NPDR, the high-risk population of STDR, were enrolled for external validation. Based on the SVM, the risk of each patient was calculated. More STDR occurred in the high-risk group than in the low-risk group, which were grouped by the median value of APN, FABP4, and leptin, respectively. The model was validated in an individual cohort using SVM with the AUC, sensitivity, and specificity reaching 0.77, 64%, and 91%, respectively.ConclusionsAdiponectin, leptin, and FABP4 were demonstrated to be associated with the severity of DR and maybe good predictors for STDR, suggesting that adipokines may play an important role in the pathophysiology of DR development.
| S-EPMC10620016 | biostudies-literature