Associations Between Diabetic Retinopathy and Parkinson's Disease: Results From the Catalonian Primary Care Cohort Study

Variations in Electronic Health Record-Based Definitions of Diabetic Retinopathy Cohorts: A Literature Review and Quantitative Analysis

Purpose

Use of the electronic health record (EHR) has motivated the need for data standardization. A gap in knowledge exists regarding variations in existing terminologies for defining diabetic retinopathy (DR) cohorts. This study aimed to review the literature and analyze variations regarding codified definitions of DR.

Design

Literature review and quantitative analysis.

Subjects

Published manuscripts.

Methods

Four graders reviewed PubMed and Google Scholar for peer-reviewed studies. Studies were included if they used codified definitions of DR (e.g., billing codes). Data elements such as author names, publication year, purpose, data set type, and DR definitions were manually extracted. Each study was reviewed by ≥ 2 authors to validate inclusion eligibility. Quantitative analyses of the codified definitions were then performed to characterize the variation between DR cohort definitions.

Main Outcome Measures

Number of studies included and numeric counts of billing codes used to define codified cohorts.

Results

In total, 43 studies met the inclusion criteria. Half of the included studies used datasets based on structured EHR data (i.e., data registries, institutional EHR review), and half used claims data. All but 1 of the studies used billing codes such as the International Classification of Diseases 9th or 10th edition (ICD-9 or ICD-10), either alone or in addition to another terminology for defining disease. Of the 27 included studies that used ICD-9 and the 20 studies that used ICD-10 codes, the most common codes used pertained to the full spectrum of DR severity. Diabetic retinopathy complications (e.g., vitreous hemorrhage) were also used to define some DR cohorts.

Conclusions

Substantial variations exist among codified definitions for DR cohorts within retrospective studies. Variable definitions may limit generalizability and reproducibility of retrospective studies. More work is needed to standardize disease cohorts.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Analysis of the Relationship Between Parkinson's Disease and Diabetic Retinopathy Based on Bioinformatics Methods

The objective of the study was to explore the relationship and potential mechanism between Parkinson's disease (PD) and diabetic retinopathy (DR) using bioinformatics methods. We first examined the causal relationship between PD and DR by Mendelian randomization (MR) analysis. The datasets of PD and DR patients from the Gene Expression Omnibus database were used to identify differentially expressed genes (DEGs). Then, we performed the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and immune infiltration analysis. We also constructed a protein-protein interaction network and receiver operating characteristic (ROC) curve. Finally, an online website was used for drug prediction. The MR analysis demonstrated a causal relationship between DR and PD (odds ratio [OR] = 0.86; 95% confidence interval [CI] 0.79-0.93; p = 3.24E - 04), in which DR acted as a protective factor against PD. There were 81 DEGs identified from the PD and DR datasets, of which 29 genes had protein interaction relationships, and enrichment analysis showed that these genes were mainly related to immune pathways. As indicated by immune cell infiltration analysis, the expression of immune cells between PD and the control group was significantly different. ROC curve results showed five genes had diagnostic value, and several potential chemical compounds were predicted to target the genes. Our findings demonstrate a reduced risk of PD in patients with DR. We also found that PD and DR are closely related in terms of inflammation, which provides clues for further exploring the common mechanisms and interaction of these two diseases.

Diabetic microvascular disease in non-classical beds: the hidden impact beyond the retina, the kidney, and the peripheral nerves

Diabetes microangiopathy, a hallmark complication of diabetes, is characterised by structural and functional abnormalities within the intricate network of microvessels beyond well-known and documented target organs, i.e., the retina, kidney, and peripheral nerves. Indeed, an intact microvascular bed is crucial for preserving each organ's specific functions and achieving physiological balance to meet their respective metabolic demands. Therefore, diabetes-related microvascular dysfunction leads to widespread multiorgan consequences in still-overlooked non-traditional target organs such as the brain, the lung, the bone tissue, the skin, the arterial wall, the heart, or the musculoskeletal system. All these organs are vulnerable to the physiopathological mechanisms that cause microvascular damage in diabetes (i.e., hyperglycaemia-induced oxidative stress, inflammation, and endothelial dysfunction) and collectively contribute to abnormalities in the microvessels' structure and function, compromising blood flow and tissue perfusion. However, the microcirculatory networks differ between organs due to variations in haemodynamic, vascular architecture, and affected cells, resulting in a spectrum of clinical presentations. The aim of this review is to focus on the multifaceted nature of microvascular impairment in diabetes through available evidence of specific consequences in often overlooked organs. A better understanding of diabetes microangiopathy in non-target organs provides a broader perspective on the systemic nature of the disease, underscoring the importance of recognising the comprehensive range of complications beyond the classic target sites.

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

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.