scholarly journals External validation of prognostic models for chronic kidney disease among type 2 diabetes

2022 ◽  
Author(s):  
Sigit Ari Saputro ◽  
Anuchate Pattanateepapon ◽  
Oraluck Pattanaprateep ◽  
Wichai Aekplakorn ◽  
Gareth J. McKay ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
External Validation ◽  
Model Performance ◽  
Nationwide Survey ◽  
Prognostic Models ◽  
Diabetic Patients ◽  
Clinical Factors

Abstract Background Various prognostic models have been derived to predict chronic kidney disease (CKD) development in type 2 diabetes (T2D). However, their generalisability and predictive performance in different populations remain largely unvalidated. This study aimed to externally validate several prognostic models of CKD in a T2D Thai cohort. Methods A nationwide survey was linked with hospital databases to create a prospective cohort of patients with diabetes (n = 3416). We undertook a systematic review to identify prognostic models and traditional metrics (i.e., discrimination and calibration) to compare model performance for CKD prediction. We updated prognostic models by including additional clinical parameters to optimise model performance in the Thai setting. Results Six relevant previously published models were identified. At baseline, C-statistics ranged from 0.585 (0.565–0.605) to 0.786 (0.765–0.806) for CKD and 0.657 (0.610–0.703) to 0.760 (0.705–0.816) for end-stage renal disease (ESRD). All original CKD models showed fair calibration with Observed/Expected (O/E) ratios ranging from 0.999 (0.975–1.024) to 1.009 (0.929–1.090). Hosmer–Lemeshow tests indicated a good fit for all models. The addition of routine clinical factors (i.e., glucose level and oral diabetes medications) enhanced model prediction by improved C-statistics of Low’s of 0.114 for CKD and Elley’s of 0.025 for ESRD. Conclusions All models showed moderate discrimination and fair calibration. Updating models to include routine clinical factors substantially enhanced their accuracy. Low’s (developed in Singapore) and Elley’s model (developed in New Zealand), outperformed the other models evaluated. These models can assist clinicians to improve the risk-stratification of diabetic patients for CKD and/or ESRD in the regions settings are similar to Thailand. Graphical abstract

scholarly journals Guidelines adherence in the prevention and management of chronic kidney disease in patients with diabetes mellitus on the background of recent European recommendations – a registry-based analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Peter Bramlage ◽  
Stefanie Lanzinger ◽  
Sascha R. Tittel ◽  
Eva Hess ◽  
Simon Fahrner ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Clinical Practice ◽  
Kidney Disease ◽  
Analysis Data ◽  
Disease Diagnosis ◽  
Diabetic Patients ◽  
European Society Of Cardiology

Abstract Background Recent European Society of Cardiology (ESC)/European Association for the Study of Diabetes (EASD) guidelines provide recommendations for detecting and treating chronic kidney disease (CKD) in diabetic patients. We compared clinical practice with guidelines to determine areas for improvement. Methods German database analysis of 675,628 patients with type 1 or type 2 diabetes, with 134,395 included in this analysis. Data were compared with ESC/EASD recommendations. Results This analysis included 17,649 and 116,747 patients with type 1 and type 2 diabetes, respectively. The analysis showed that 44.1 and 49.1 % patients with type 1 and type 2 diabetes, respectively, were annually screened for CKD. Despite anti-diabetic treatment, only 27.2 % patients with type 1 and 43.5 % patients with type 2 achieved a target HbA1c of < 7.0 %. Use of sodium-glucose transport protein 2 inhibitors (1.5 % type 1/8.7 % type 2 diabetes) and glucagon-like peptide-1 receptor agonists (0.6 % type 1/5.2 % type 2 diabetes) was limited. Hypertension was controlled according to guidelines in 41.1 and 67.7 % patients aged 18–65 years with type 1 and 2 diabetes, respectively, (62.4 vs. 68.4 % in patients > 65 years). Renin angiotensin aldosterone inhibitors were used in 24.0 and 40.9 % patients with type 1 diabetes (micro- vs. macroalbuminuria) and 39.9 and 47.7 %, respectively, in type 2 diabetes. Conclusions Data indicate there is room for improvement in caring for diabetic patients with respect to renal disease diagnosis and treatment. While specific and potentially clinically justified reasons for non-compliance exist, the data may serve well for a critical appraisal of clinical practice decisions.

scholarly journals The Effect of Renal Dysfunction on Circulating Sclerostin Level in Patients with Type 2 Diabetes

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Se Hwa Kim ◽  
Soo Young Yoon ◽  
Sung-Kil Lim ◽  
Yumie Rhee
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Renal Function ◽  
Kidney Disease ◽  
Renal Dysfunction ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Cross Sectional ◽  
Sclerostin Level

Objective. Sclerostin is a Wnt inhibitor produced specifically by osteocytes. However, it is not currently clear whether renal dysfunction has an effect on circulating sclerostin level in patients with type 2 diabetes. The aim of the study was to evaluate this relationship. Design and Patients. We conducted a cross-sectional observational study of 302 type 2 diabetic patients with or without chronic kidney disease. Serum sclerostin level was analyzed by ELISA, and renal function was assessed by estimated glomerular filtration rate (eGFR) using chronic kidney disease epidemiology collaboration (CKD-EPI) equation. Results. There was a strong correlation between sclerostin level with renal function presented as serum creatinine (r=0.745, P<0.001) and eGFR (r=-0.590, P<0.001). Serum sclerostin level was significantly higher in patients with CKD-G3 stage than those with CKD-G1/2 stages after adjusting for age, sex, and BMI (P=0.011). Patients with CKD-G4/5 stages had dramatically increased level of circulating sclerostin. Multiple regression analyses found that age, sex, and eGFR were independent determining factors for circulating sclerostin level. Conclusion. Our data showed that serum sclerostin levels start to increase in diabetic patients with CKD-G3 stage. Further studies are needed to establish the potential role of elevated sclerostin in diabetic patients with CKD.

scholarly journals External Validation of a Tool Predicting 7-Year Risk of Developing Cardiovascular Disease, Type 2 Diabetes or Chronic Kidney Disease

2017 ◽  
Vol 33 (2) ◽  
pp. 182-188 ◽  
Author(s):  
Simone P. Rauh ◽  
Femke Rutters ◽  
Amber A. W. A. van der Heijden ◽  
Thomas Luimes ◽  
Marjan Alssema ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
External Validation ◽  
Disease Type

scholarly journals Emergence of T cell immunosenescence in diabetic chronic kidney disease

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Yen-Ling Chiu ◽  
Wan-Chuan Tsai ◽  
Ruo-Wei Hung ◽  
I-Yu Chen ◽  
Kai-Hsiang Shu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Renal Failure ◽  
T Cells ◽  
Renal Function ◽  
T Cell ◽  
Kidney Disease ◽  
Glucose Control ◽  
Diabetic Patients

Abstract Background Type 2 diabetes is an important challenge given the worldwide epidemic and is the most important cause of end-stage renal disease (ESRD) in developed countries. It is known that patients with ESRD and advanced renal failure suffer from immunosenescence and premature T cell aging, but whether such changes develop in patients with less severe chronic kidney disease (CKD) is unclear. Method 523 adult patients with type 2 diabetes were recruited for this study. Demographic data and clinical information were obtained from medical chart review. Immunosenescence, or aging of the immune system was assessed by staining freshly-obtained peripheral blood with immunophenotyping panels and analyzing cells using multicolor flow cytometry. Result Consistent with previously observed in the general population, both T and monocyte immunosenescence in diabetic patients positively correlate with age. When compared to diabetic patients with preserved renal function (estimated glomerular filtration rate > 60 ml/min), patients with impaired renal function exhibit a significant decrease of total CD3+ and CD4+ T cells, but not CD8+ T cell and monocyte numbers. Immunosenescence was observed in patients with CKD stage 3 and in patients with more severe renal failure, especially of CD8+ T cells. However, immunosenescence was not associated with level of proteinuria level or glucose control. In age, sex and glucose level-adjusted regression models, stage 3 CKD patients exhibited significantly elevated percentages of CD28−, CD127−, and CD57+ cells among CD8+ T cells when compared to patients with preserved renal function. In contrast, no change was detected in monocyte subpopulations as renal function declined. In addition, higher body mass index (BMI) is associated with enhanced immunosenescence irrespective of CKD status. Conclusion The extent of immunosenescence is not significantly associated with proteinuria or glucose control in type 2 diabetic patients. T cells, especially the CD8+ subsets, exhibit aggravated characteristics of immunosenescence during renal function decline as early as stage 3 CKD. In addition, inflammation increases since stage 3 CKD and higher BMI drives the accumulation of CD8+CD57+ T cells. Our study indicates that therapeutic approaches such as weight loss may be used to prevent the emergence of immunosenescence in diabetes before stage 3 CKD.

scholarly journals Analysis of Chronic Kidney Disease – Asociated Glycemic Variability in Patients with Type 2 Diabetes Using Continuous Glucose Monitoring System

2013 ◽  
Vol 20 (3) ◽  
pp. 315-322 ◽  
Author(s):  
Cristina Văduva ◽  
Simona Popa ◽  
Maria Moţa ◽  
Eugen Moţa
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Glycemic Control ◽  
Predictive Value ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Diabetic Patients ◽  
Metabolic Imbalance

Abstract Background and Aims. In diabetic patients, chronic kidney disease (CKD) requires special attention due to the multitude of factors that determine glycemic variability. We aimed to assess glycemic variability in patients with CKD and type 2 diabetes mellitus (T2DM) using a continuous glucose monitoring system (CGMS) and identify the predictive value of inter-day and intra-day glycemic variability indices for metabolic imbalance. Material and method. We included 20 diabetic patients (10 CKD patients/10 patients without CKD) and 10 healthy volunteers. Anthropometric parameters, glycated hemoglobin (HbA1c), and glycemic variability indices on CGMS readings were registered. Results. CKD diabetic patients presented significantly higher inter-day and intra-day glycemic variability compared to the diabetic patients without CKD. HbA1c was not significantly different between diabetic subjects with/without CKD. ROC curves indicated that just some CGMS parameters had higher predictive value for metabolic imbalance (HbA1c≥6.5%) but only the percentage of time with glucose values>180 mg/dl (p=0.024) was an independent predictor for HbA1c≥6.5%. Conclusions. Subjects with CKD and T2DM had poor glycemic control and significantly higher glycemic variability comparative to those without CKD, and especially to healthy volunteers. Assessment of glycemic variability indices is more accurate than HbA1c for the quantification of glycemic control in CKD diabetic patients

scholarly journals Performance of prediction models for nephropathy in people with type 2 diabetes: systematic review and external validation study

BMJ ◽  
2021 ◽  
pp. n2134
Author(s):  
Roderick C Slieker ◽  
Amber A W A van der Heijden ◽  
Moneeza K Siddiqui ◽  
Marlous Langendoen-Gort ◽  
Giel Nijpels ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
General Population ◽  
Diabetic Kidney Disease ◽  
Prediction Models ◽  
External Validation ◽  
Diabetic Kidney

Abstract Objectives To identify and assess the quality and accuracy of prognostic models for nephropathy and to validate these models in external cohorts of people with type 2 diabetes. Design Systematic review and external validation. Data sources PubMed and Embase. Eligibility criteria Studies describing the development of a model to predict the risk of nephropathy, applicable to people with type 2 diabetes. Methods Screening, data extraction, and risk of bias assessment were done in duplicate. Eligible models were externally validated in the Hoorn Diabetes Care System (DCS) cohort (n=11 450) for the same outcomes for which they were developed. Risks of nephropathy were calculated and compared with observed risk over 2, 5, and 10 years of follow-up. Model performance was assessed based on intercept adjusted calibration and discrimination (Harrell’s C statistic). Results 41 studies included in the systematic review reported 64 models, 46 of which were developed in a population with diabetes and 18 in the general population including diabetes as a predictor. The predicted outcomes included albuminuria, diabetic kidney disease, chronic kidney disease (general population), and end stage renal disease. The reported apparent discrimination of the 46 models varied considerably across the different predicted outcomes, from 0.60 (95% confidence interval 0.56 to 0.64) to 0.99 (not available) for the models developed in a diabetes population and from 0.59 (not available) to 0.96 (0.95 to 0.97) for the models developed in the general population. Calibration was reported in 31 of the 41 studies, and the models were generally well calibrated. 21 of the 64 retrieved models were externally validated in the Hoorn DCS cohort for predicting risk of albuminuria, diabetic kidney disease, and chronic kidney disease, with considerable variation in performance across prediction horizons and models. For all three outcomes, however, at least two models had C statistics >0.8, indicating excellent discrimination. In a secondary external validation in GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland), models developed for diabetic kidney disease outperformed those for chronic kidney disease. Models were generally well calibrated across all three prediction horizons. Conclusions This study identified multiple prediction models to predict albuminuria, diabetic kidney disease, chronic kidney disease, and end stage renal disease. In the external validation, discrimination and calibration for albuminuria, diabetic kidney disease, and chronic kidney disease varied considerably across prediction horizons and models. For each outcome, however, specific models showed good discrimination and calibration across the three prediction horizons, with clinically accessible predictors, making them applicable in a clinical setting. Systematic review registration PROSPERO CRD42020192831.

No effect of vitamin D supplementation on metabolic parameters but on lipids in patients with type 2 diabetes and chronic kidney disease

2020 ◽  
pp. 1-10
Author(s):  
Jiwoon Kim ◽  
Ji Sun Nam ◽  
Heejung Kim ◽  
Hye Sun Lee ◽  
Jung Eun Lee
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Vitamin D ◽  
Kidney Disease ◽  
Vitamin D Supplementation ◽  
Lipid Profiles ◽  
Metabolic Parameters ◽  
Injection Group ◽  
Different Doses

Abstract. Background/Aims: Trials on the effects of cholecalciferol supplementation in type 2 diabetes with chronic kidney disease patients were underexplored. Therefore, the aim of this study was to investigate the effects of two different doses of vitamin D supplementation on serum 25-hydroxyvitamin D [25(OH)D] concentrations and metabolic parameters in vitamin D-deficient Korean diabetes patients with chronic kidney disease. Methods: 92 patients completed this study: the placebo group (A, n = 33), the oral cholecalciferol 1,000 IU/day group (B, n = 34), or the single 200,000 IU injection group (C, n = 25, equivalent to 2,000 IU/day). 52% of the patients had less than 60 mL/min/1.73m2 of glomerular filtration rates. Laboratory test and pulse wave velocity were performed before and after supplementation. Results: After 12 weeks, serum 25(OH)D concentrations of the patients who received vitamin D supplementation were significantly increased (A, -2.4 ± 1.2 ng/mL vs. B, 10.7 ± 1.2 ng/mL vs. C, 14.6 ± 1.7 ng/mL; p < 0.001). In addition, the lipid profiles in the vitamin D injection group (C) showed a significant decrease in triglyceride and a rise in HDL cholesterol. However, the other parameters showed no differences. Conclusions: Our data indicated that two different doses and routes of vitamin D administration significantly and safely increased serum 25(OH)D concentrations in vitamin D-deficient diabetes patients with comorbid chronic kidney disease. In the group that received the higher vitamin D dose, the lipid profiles showed significant improvement, but there were no beneficial effects on other metabolic parameters.

Sign in / Sign up

Export Citation Format

Share Document