Management of Hypertension in Diabetic Kidney Disease

Colbert, Gates B.; Elrggal, Mohamed E.; Gaddy, Anna; Madariaga, Hector M.; Lerma, Edgar V.

doi:10.3390/jcm12216868

Cited by 3 publications

References 61 publications

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Interpretable Machine Learning Model for Predicting and Risk Assessment of Diabetic Nephropathy (Preprint)

Wen,

Wan,

Ren

et al. 2024

Preprint

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UNSTRUCTURED Introduction: Diabetic Nephropathy (DN), severe complications of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease (ESRD). DN's pathogenesis involves high glucose levels, oxidative stress, inflammation, and fibrosis, resulting in kidney changes such as glomerular basement membrane thickening and glomerulosclerosis. The International Diabetes Federation projects that by 2045, 783 million people will have diabetes, with 30%-40% of them developing DN. Early detection and intervention are crucial for preserving renal function, improving quality of life, eliminating cardiovascular complications, and reducing healthcare costs. Methods: This study utilized machine learning (ML) techniques to develop and validate a predictive model for DN, focusing on both high predictive accuracy and model interpretability. Data from 1,000 Type-2 diabetes patients, including 444 with DN and 556 without, were analyzed. Various ML algorithms, including decision trees, random forests, Extra Trees, AdaBoost, XGBoost, and LightGBM, were employed. Multiple imputation was used for handling missing data, and the Synthetic Minority Over-sampling Technique (SMOTE) addressed data imbalance. Model performance was evaluated with metrics such as accuracy, precision, recall, F1 score, specificity, and area under the curve (AUC). Explainable Machine Learning (XML) techniques like LIME and SHAP were used to enhance model transparency and interpretability. Results: XGBoost and LightGBM demonstrated superior performance, with XGBoost achieving the highest accuracy of 86.87%, a precision of 88.90%, a recall of 84.40%, an F1 score of 86.44%, and a specificity of 89.12%. LIME and SHAP analyses provided insights into the contribution of individual features to the prediction outcomes, identifying serum creatinine, C-peptide, albumin, and lipoproteins as significant predictors. Conclusion: The developed ML model not only provides a robust predictive tool for early diagnosis and risk assessment of DN but also ensures transparency and interpretability, crucial for clinical integration. By enabling early intervention and personalized treatment strategies, this model has the potential to improve patient outcomes and optimize healthcare resource utilization.

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Interpretable Machine Learning Model for Predicting and Risk Assessment of Diabetic Nephropathy (Preprint)

Wen,

Wan,

Ren

et al. 2024

Preprint

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Oxidative Stress in Kidney Injury and Hypertension

Arendshorst,

Vendrov,

Kumar

et al. 2024

Antioxidants

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Hypertension (HTN) is a major contributor to kidney damage, leading to conditions such as nephrosclerosis and hypertensive nephropathy, significant causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD). HTN is also a risk factor for stroke and coronary heart disease. Oxidative stress, inflammation, and activation of the renin–angiotensin–aldosterone system (RAAS) play critical roles in causing kidney injury in HTN. Genetic and environmental factors influence the susceptibility to hypertensive renal damage, with African American populations having a higher tendency due to genetic variants. Managing blood pressure (BP) effectively with treatments targeting RAAS activation, oxidative stress, and inflammation is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD. Interactions between genetic and environmental factors impacting kidney function abnormalities are central to HTN development. Animal studies indicate that genetic factors significantly influence BP regulation. Anti-natriuretic mechanisms can reset the pressure–natriuresis relationship, requiring a higher BP to excrete sodium matched to intake. Activation of intrarenal angiotensin II receptors contributes to sodium retention and high BP. In HTN, the gut microbiome can affect BP by influencing energy metabolism and inflammatory pathways. Animal models, such as the spontaneously hypertensive rat and the chronic angiotensin II infusion model, mirror human essential hypertension and highlight the significance of the kidney in HTN pathogenesis. Overproduction of reactive oxygen species (ROS) plays a crucial role in the development and progression of HTN, impacting renal function and BP regulation. Targeting specific NADPH oxidase (NOX) isoforms to inhibit ROS production and enhance antioxidant mechanisms may improve renal structure and function while lowering blood pressure. Therapies like SGLT2 inhibitors and mineralocorticoid receptor antagonists have shown promise in reducing oxidative stress, inflammation, and RAAS activity, offering renal and antihypertensive protection in managing HTN and CKD. This review emphasizes the critical role of NOX in the development and progression of HTN, focusing on its impact on renal function and BP regulation. Effective BP management and targeting oxidative stress, inflammation, and RAAS activation, is crucial in preventing renal damage and the progression of HTN-related CKD and ESRD.

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Beyond Blood Sugar: Low Awareness of Kidney Disease among Type 2 Diabetes Mellitus Patients in Dalmatia—Insights from the First Open Public Call

Radić,

Vučković,

Đogaš

et al. 2024

Medicina

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Background and Objectives: Kidney disease (KD) is a common complication of diabetes mellitus (DM) associated with adverse outcomes of renal failure, cardiovascular disease, and mortality. The aim of this study was to determine the prevalence and awareness of the KD among the DM type 2 (T2DM) patients. Materials and Methods: This cross-sectional study was conducted at the University Hospital of Split between November and December of 2023 during an open call for DM patients. For each participant, blood and urine samples, along with relevant medical information, were collected, and adherence to the Mediterranean diet (MeDi) was assessed using the Mediterranean Diet Service Score (MDSS). Furthermore, blood pressure was measured, along with body composition and anthropometric parameters. Results: Of 252 T2DM patients with a median age of 67 years (IQR: 60–73), 130 (51.6%) were women. The median duration of T2DM was 10 years (IQR: 6–20). Despite the fact that 80.95% of total participants reported receiving dietary guidelines from any source, only 53.2% reported adhering to the suggested instructions, while according to the MDSS, only 7.2% adhered to the MeDi. The median body mass index was 27.6 kg/m2 (24.2–31), with 70.1% of participants overweight or obese. Only 6% of participants believed they had KD, but after blood and urine sample analysis, 31% were found to have KD. Conclusions: This study highlights a significant gap in awareness of KD, low adherence to MeDi, and a high prevalence of obesity among T2DM patients. Due to the increasing number of T2DM patients, it is crucial to improve healthy lifestyle education and make modifications within this group, as well as perform regular screening for KD and medical check-ups.

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Management of Hypertension in Diabetic Kidney Disease

Cited by 3 publications

References 61 publications

Interpretable Machine Learning Model for Predicting and Risk Assessment of Diabetic Nephropathy (Preprint)

Interpretable Machine Learning Model for Predicting and Risk Assessment of Diabetic Nephropathy (Preprint)

Oxidative Stress in Kidney Injury and Hypertension

Beyond Blood Sugar: Low Awareness of Kidney Disease among Type 2 Diabetes Mellitus Patients in Dalmatia—Insights from the First Open Public Call

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