Abstract 154: Diabetic Retinopathy and Risk of Stroke: A Secondary Analysis of Accord

Wong, K. C.; Peterson, Cecilia; Rock, Theodore; Aitken, Kinga; Cruz, Michael Dela; Majersik, Jennifer J.; DeHavenon, Adam

doi:10.1161/str.51.suppl_1.154

Cited by 7 publications

(10 citation statements)

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“…Subgroup analysis for the type of diabetes yielded a pooled HR of 1.29 and 95% CI: 1.10; 1.50 in T2DM ( 21 ). In a secondary analysis of patients enrolled in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Eye Study in an adjusted Cox regression model, DR was independently associated with incident stroke (HR:1.52, 95% CI:1.05; 2.20) ( 22 ). Another prospective cohort study with 1,617 middle-aged people with diabetes observed that during a follow-up of 7.8 years, DR was associated with an increased risk of ischemic stroke (HR: 2.34, 95% CI: 1.13; 4.86) ( 24 ).…”

Section: Discussionmentioning

confidence: 99%

“…We have extensive evidence that associates DR with other micro-and macrovascular complications of diabetes. Recently, it was reported that DR is associated with subclinical atherosclerosis (10)(11)(12)(13)(14), macrovascular comorbidities such as coronary disease (15)(16)(17)(18)(19)(20) and cerebrovascular accident (21)(22)(23)(24)(25)(26). Of interest, some studies have reported an association between cognitive impairment and the incidence of dementia [risk ratio (RR), 1.3; 95% confidence interval (CI), 1.27-1.58] (27,28), and the relation between DR and neurodegeneration diseases such as Parkinson's disease has been proposed but remains unclear (29).…”

Section: Introductionmentioning

confidence: 99%

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Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes

et al. 2022

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This study aimed to evaluate the predictive value of diabetic retinopathy (DR) and its stages with the incidence of major cardiovascular events and all-cause mortality in type 2 diabetes mellitus (T2DM) persons in our large primary healthcare database from Catalonia (Spain). A retrospective cohort study with pseudo-anonymized routinely collected health data from SIDIAP was conducted from 2008 to 2016. We calculated incidence rates of major cardiovascular events [coronary heart disease (CHD), stroke, or both—macrovascular events] and all-cause mortality for subjects with and without DR and for different stages of DR. The proportional hazards regression analysis was done to assess the probability of occurrence between DR and the study events. About 22,402 T2DM subjects with DR were identified in the database and 196,983 subjects without DR. During the follow-up period among the subjects with DR, we observed the highest incidence of all-cause mortally. In the second place were the macrovascular events among the subjects with DR. In the multivariable analysis, fully adjusted for DR, sex, age, body mass index (BMI), tobacco, duration of T2DM, an antiplatelet or antihypertensive drug, and HbA1c, we observed that subjects with any stage of DR had higher risks for all of the study events, except for stroke. We observed the highest probability of all-cause death events (adjusted hazard ratios, AHRs: 1.34, 95% CI: 1.28; 1.41). In conclusion, our results show that DR is related to CHD, macrovascular events, and all-cause mortality among persons with T2DM.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes

et al. 2022

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“…For example, a high frequency of circulatory signpost codes are predictive of congestive heart failure. A medium frequency of eye/adnexa signpost codes are predictive of diabetic retinopathy, stroke, and vascular dementia, all shown in the literature to be associated with ocular symptoms (Ho et al, 2009;Hwang et al, 2021;Wong et al, 2020). An application for how individual-level DETECT trajectories can be leveraged to ask temporal questions about order or quality of disease precursors at a population level is shown in Fig.…”

Section: Real-world Data Trajectory Analysismentioning

confidence: 99%

DETECT: Feature extraction method for disease trajectory modeling

Singhal

Guare

Morse

et al. 2022

Preprint

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Modeling with longitudinal electronic health record (EHR) data proves challenging given the high dimensionality, redundancy, and noise captured in EHR. In order to improve precision medicine strategies and identify predictors of disease risk in advance, evaluating meaningful patient disease trajectories is essential. In this study, we develop the algorithm DiseasE Trajectory fEature extraCTion (DETECT) for feature extraction and trajectory generation in high-throughput temporal EHR data. This algorithm can 1) simulate longitudinal individual-level EHR data, specified to user parameters of scale, complexity, and noise and 2) use a convergent relative risk framework to test intermediate codes occurring between a specified index code(s) and outcome code(s) to determine if they are predictive features of the outcome. We benchmarked our method on simulated data and generated real-world disease trajectories using DETECT in a cohort of 145,575 individuals diagnosed with hypertension in Penn Medicine EHR for severe cardiometabolic outcomes.

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“…However, accruing evidence suggest that other factors such as diabetes-related microvascular complications might play a role [ 4 – 7 ]. Indeed, diabetic retinopathy was found to be associated with higher risk of stroke in people with type 2 diabetes [ 8 ]. The impact on stroke of microvascular disease in other vascular territories (such as the kidney) in individuals with type 2 diabetes has received less attention [ 9 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

Diabetic kidney disease and risk of incident stroke among adults with type 2 diabetes

Kazé

Jaar

Fonarow

et al. 2022

BMC Med

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Background Data on the relations between kidney function abnormalities and stroke in type 2 diabetes are limited. We evaluated the associations of kidney function abnormalities and chronic kidney disease (CKD) stages with incident stroke in a large sample of adults with type 2 diabetes. Methods Participants with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study without history of stroke at baseline were included. Urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) were assessed at baseline. CKD categories were defined according to the KDIGO (Kidney Disease: Improving Global Outcomes) guidelines. Cox proportional hazards regression models were used to compute hazard ratios (HR) and 95% confidence intervals (CI) for stroke in relation to measures of kidney function and CKD categories. Results A total of 9170 participants (mean age 62.8 [SD: 6.6] years, 38.2% women, 62.9% white) were included. Over a median follow-up of 4.9 years (interquartile range: 4.0–5.7), 156 participants developed a stroke (incidence rate 3.6/1000 person-years [95% CI 3.0–4.2]). After adjusting for relevant confounders, higher UACR and lower eGFR were each associated with increased risk of stroke. Compared to UACR < 30 mg/g, moderate albuminuria and severe albuminuria were associated with increasing hazards for stroke (HR 1.61 [95% CI 1.12–2.32] and 2.29 [95% CI 1.39–3.80], respectively). Compared to eGFR of ≥ 60 mL/min/1.73 m2, decreased eGFR (eGFR < 60 mL/min/1.73 m2) was associated with higher risk of stroke (HR 1.50, 95% CI 0.98–2.29). Compared to no CKD, worsening CKD stage was associated with an increasing risk of stroke (HRs of 1.76 [95% CI 1.10–2.83] for CKD G1, 1.77 [95% CI 1.13–2.75] for CKD G2, and 2.03 [95% CI 1.27–3.24] for CKD G3). Conclusions In a large sample of adults with type 2 diabetes, increasing albuminuria and worsening stages of early CKD were independently associated with higher risk of incident stroke. Trial registration ClinicalTrials.gov. Identifier: NCT00000620.

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Abstract 154: Diabetic Retinopathy and Risk of Stroke: A Secondary Analysis of Accord

Cited by 7 publications

References 0 publications

Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes

Diabetic retinopathy as a predictor of cardiovascular morbidity and mortality in subjects with type 2 diabetes

DETECT: Feature extraction method for disease trajectory modeling

Diabetic kidney disease and risk of incident stroke among adults with type 2 diabetes

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