scholarly journals Metabolic Syndrome and Insulin Resistance as Risk Factors for Development of Chronic Kidney Disease and Rapid Decline in Renal Function in Elderly

2012 ◽  
Vol 97 (4) ◽  
pp. 1268-1276 ◽  
Author(s):  
Hui-Teng Cheng ◽  
Jenq-Wen Huang ◽  
Chih-Kang Chiang ◽  
Chung-Jen Yen ◽  
Kuan-Yu Hung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Chronic Kidney Disease ◽  
Renal Function ◽  
Kidney Disease ◽  
Rapid Decline

scholarly journals Metabolic Constellations, Clusters, and Renal Function: Findings from the 2013–2018 National Health and Nutrition Examination Surveys

Life ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 904
Author(s):  
Kathleen E. Adair ◽  
Kelly R. Ylitalo ◽  
Jeffrey S. Forsse ◽  
LesLee K. Funderburk ◽  
Rodney G. Bowden
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Chronic Kidney Disease ◽  
Renal Function ◽  
Waist Circumference ◽  
Kidney Disease ◽  
National Health ◽  
Health And Nutrition ◽  
Low Hdl ◽  
The Relationship

Metabolic syndrome (MetS) is associated with decreased renal function and chronic kidney disease (CKD). To date, no research regarding the sixteen possible constellations resulting in the diagnosis of MetS has been elucidated. The purpose of this study is to report renal function in sixteen metabolic constellations grouped into four metabolic clusters. Individuals (n = 2767; representing 86,652,073 individuals) from the 2013–2018 National Health and Nutrition Examination Surveys who met the criteria for MetS were included. Sixteen possible constellations of three or more risk factors were analyzed for renal function. Four metabolic clusters representing MetS with hyperglycemia (Cluster I), MetS with hypertension (Cluster II), MetS with hyperglycemia and hypertension (Cluster III), or MetS with normoglycemia and normotension (Cluster IV) were assessed for renal function and CKD status. Cluster III had the highest odds of CKD (OR = 2.57, 95% CL = 1.79, 3.68). Clusters II and III had the lowest renal function and were not different from one another (87.82 and 87.28 mL/min/1.73 m2, p = 0.71). The constellation with the lowest renal function consisted of hypertension, high triglycerides, and a large waist circumference (82.86 mL/min/1.73 m2), whereas the constellation with the highest renal function consisted of hyperglycemia, low HDL, and a large waist circumference (107.46 mL/min/1.73 m2). The sixteen constellations of MetS do not have the same effects on renal function. More research is needed to understand the relationship between the various iterations of MetS and renal function.

Increasing Body Mass Index Predicts Rapid Decline in Renal Function: A 5 Year Retrospective Study

2018 ◽  
Vol 50 (07) ◽  
pp. 556-561 ◽  
Author(s):  
Xiaojing Ma ◽  
Chengyin Zhang ◽  
Hong Su ◽  
Xiaojie Gong ◽  
Xianglei Kong
Keyword(s):  
Body Mass Index ◽  
Chronic Kidney Disease ◽  
Renal Function ◽  
Retrospective Study ◽  
Kidney Disease ◽  
Body Mass ◽  
Adult Population ◽  
Rapid Decline ◽  
Logistic Regression Models ◽  
Baseline Bmi

AbstractWhile obesity is a recognized risk factor for chronic kidney disease, it remains unclear whether change in body mass index (ΔBMI ) is independently associated with decline in renal function (evaluated by the change in estimated glomerular filtration rate, ΔeGFR) over time. Accordingly, to help clarify this we conducted a retrospective study to measure the association of ΔBMI with decline in renal function in Chinese adult population. A total of 4007 adults (aged 45.3±13.7 years, 68.6% male) without chronic kidney disease at baseline were enrolled between 2008 and 2013. Logistic regression models were applied to explore the relationships between baseline BMI and ΔBMI, and rapid decline in renal function (defined as the lowest quartile of ΔeGFR ). During 5 years of follow-up, the ΔBMI and ΔeGFR were 0.47±1.6 (kg/m2) and –3.0±8.8 (ml/min/1.73 m2), respectively. After adjusted for potential confounders, ΔBMI (per 1 kg/m2 increase) was independently associated with the rapid decline in renal function [with a fully adjusted OR of 1.12 (95% CI, 1.05 to 1.20). By contrast, the baseline BMI was not associated with rapid decline in renal function [OR=1.05 (95% CI, 0.98 to 1.13)]. The results were robust among 2948 hypertension-free and diabetes-free participants, the adjusted ORs of ΔBMI and baseline BMI were 1.14 (95% CI, 1.05 to 1.23) and 1.0 (95% CI, 0.96 to 1.04) for rapid decline in renal function, respectively. The study revealed that increasing ΔBMI predicts rapid decline in renal function.

The obese patient (metabolic syndrome)

2015 ◽  
Author(s):  
Maarit Korkeila ◽  
Bengt Lindholm ◽  
Peter Stenvinkel
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Overweight And Obesity ◽  
Blood Cholesterol ◽  
Long Term Effects ◽  
Reverse Epidemiology ◽  
Increased Risk

Overweight and obesity cause pathophysiological changes in renal function and increase the risk for chronic kidney disease in otherwise healthy subjects. This should not be a surprise as the risk factors for metabolic syndrome largely overlap with those for chronic kidney disease. Intentional weight loss has beneficial effects on risk factors, but long term effects are less clear. Bariatric surgery does seem to achieve rapid benefits on blood pressure and proteinuria as well as on other aspects of metabolic syndrome, but its long term implications for kidney function are less clear cut as there may be an increased risk of nephrolithiasis, and possibly AKI and other complications.Obesity in haemodialysis patients is one of those paradoxical examples of reverse epidemiology where a factor associated with negative outcomes in the general population is associated with better outcomes in dialysis patients. The same is true for high blood cholesterol values. Interpretation is complicated by complex competing outcomes and confounders.

scholarly journals METABOLIC SYNDROME - AN EMERGING RISK FACTOR FOR CHRONIC KIDNEY DISEASE

2018 ◽  
Vol 11 (6) ◽  
pp. 212
Author(s):  
Ashwini Shenai ◽  
Savitha G
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Body Mass Index ◽  
Chronic Kidney Disease ◽  
Risk Factor ◽  
Kidney Disease ◽  
Serum Creatinine ◽  
Healthy Individuals ◽  
Serum Urea ◽  
The Mean

Objective: Metabolic syndrome (MetS) is a common health problem worldwide. According to third national health and nutrition examination survey criteria, about 47 million people have MetS. It is defined as having three or more of the following five risk factors including abdominal obesity, increased triglyceride levels, low-density lipoprotein cholesterol level, elevated blood pressure, and elevated fasting glucose levels. These components of MetS are major risk factors for the development of chronic kidney disease (CKD) also. CKD is a major public problem and it is a major risk factor for the development of cardiovascular disease. Hence, the aim of the current study was to evaluate the association between MetS and CKD.Methods: A total of 50 patients reporting to Saveetha Dental College and Hospitals were enrolled into the study which includes 25 patients with MetS and 25 healthy individuals. 5 mL of venous blood was collected and centrifuged. Then, it is analyzed for fasting blood sugar (FBS), serum triglycerides, serum urea, and creatinine using the standard kit method. The data obtained were subjected to statistical analysis using the SPSS software.Results: The mean body mass index, FBS, serum creatinine, and triglyceride levels were higher in MetS patients in comparison to healthy individuals. The mean body mass index (BMI), FBS, serum urea, serum creatinine, and triglyceride levels in the control group and MetS group were 27.75±3.67, 84.8±12.5, 17.52±5.2, 0.91±0.17, and 96.5±60.13 and 35.14±4.25, 108.8±34.69, 21.4±5.9, 1.0±0.14, and 239.76±51.21, respectively. There was a significant difference in the mean BMI, FBS, urea, creatinine, and triglyceride levels of the above group.Conclusion: Serum urea and creatinine levels were significantly higher in MetS individuals. Hence, MetS could be a one of the risk factors for the development of CKD.

scholarly journals Clustering Heatmap for Visualizing and Exploring Complex and High-dimensional Data Related to Chronic Kidney Disease

2020 ◽  
Vol 9 (2) ◽  
pp. 403 ◽  
Author(s):  
Cheng-Sheng Yu ◽  
Chang-Hsien Lin ◽  
Yu-Jiun Lin ◽  
Shiyng-Yu Lin ◽  
Sen-Te Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Care ◽  
Chronic Kidney Disease ◽  
High Risk ◽  
Kidney Disease ◽  
Complex Disease ◽  
Early Recognition ◽  
Adverse Outcomes ◽  
Rapid Decline ◽  
Rapid Progression

Background: Preventive medicine and primary health care are essential for patients with chronic kidney disease (CKD) because the symptoms of CKD may not appear until the renal function is severely compromised. Early identification of the risk factors of CKD is critical for preventing kidney damage and adverse outcomes. Early recognition of rapid progression to advanced CKD in certain high-risk populations is vital. Methods: This is a retrospective cohort study, the population screened and the site where the study has been performed. Multivariate statistical analysis was used to assess the prediction of CKD as many potential risk factors are involved. The clustering heatmap and random forest provides an interactive visualization for the classification of patients with different CKD stages. Results: uric acid, blood urea nitrogen, waist circumference, serum glutamic oxaloacetic transaminase, and hemoglobin A1c (HbA1c) were significantly associated with CKD. CKD was highly associated with obesity, hyperglycemia, and liver function. Hypertension and HbA1c were in the same cluster with a similar pattern, whereas high-density lipoprotein cholesterol had an opposite pattern, which was also verified using heatmap. Early staged CKD patients who are grouped into the same cluster as advanced staged CKD patients could be at high risk for rapid decline of kidney function and should be closely monitored. Conclusions: The clustering heatmap provided a new predictive model of health care management for patients at high risk of rapid CKD progression. This model could help physicians make an accurate diagnosis of this progressive and complex disease.

scholarly journals Urinary Retinol-Binding Protein: Relationship to Renal Function and Cardiovascular Risk Factors in Chronic Kidney Disease

PLoS ONE ◽  
2016 ◽  
Vol 11 (9) ◽  
pp. e0162782 ◽  
Author(s):  
Maria Alice Muniz Domingos ◽  
Silvia Regina Moreira ◽  
Luz Gomez ◽  
Alessandra Goulart ◽  
Paulo Andrade Lotufo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Renal Function ◽  
Cardiovascular Risk ◽  
Kidney Disease ◽  
Cardiovascular Risk Factors ◽  
Binding Protein ◽  
Retinol Binding Protein

scholarly journals The Metabolic Syndrome and Risk of Chronic Kidney Disease: Pathophysiology and Intervention Strategies

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Heather A. LaGuardia ◽  
L. Lee Hamm ◽  
Jing Chen
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Metabolic Syndrome ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Intervention Strategies ◽  
Elevated Blood ◽  
The Metabolic Syndrome ◽  
Prevalence Of Obesity ◽  
Complications And Mortality

Metabolic syndrome is characterized by a clustering of cardiovascular risk factors, including abdominal obesity, elevated blood pressure and glucose concentrations, and dyslipidemia. The presence of this clinical entity is becoming more pervasive throughout the globe as the prevalence of obesity increases worldwide. Moreover, there is increased recognition of the complications and mortality related to this syndrome. This paper looks to examine the link between metabolic syndrome and the development of chronic kidney disease.

Sign in / Sign up

Export Citation Format

Share Document