scholarly journals A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes. Diabetes Care 2021;44:901–907

Diabetes Care ◽  
2021 ◽  
pp. dci210010
Author(s):  
Dorte Vistisen ◽  
Gregers S. Andersen ◽  
Adam Hulman ◽  
Stuart J. McGurnaghan ◽  
Helen M. Colhoun ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
Diabetes Care ◽  
End Stage Kidney Disease ◽  
End Stage

scholarly journals A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes. Diabetes Care 2021;44:901–907

Diabetes Care ◽  
2021 ◽  
pp. dc210364
Author(s):  
Helena Bleken Østergaard ◽  
Joep van der Leeuw ◽  
Frank L.J. Visseren ◽  
Jan Westerink
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
Diabetes Care ◽  
End Stage Kidney Disease ◽  
End Stage

scholarly journals A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes

2021 ◽  
Author(s):  
Dorte Vistisen ◽  
Gregers S. Andersen ◽  
Adam Hulman ◽  
Stuart J. McGurnaghan ◽  
Helen M. Colhoun ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
Clinical Decision Making ◽  
External Validation ◽  
End Stage Kidney Disease ◽  
Risk Of Death ◽  
Increased Risk ◽  
End Stage

<b>OBJECTIVE </b> <p>End-stage kidney disease (ESKD) is a life-threatening complication of diabetes which can be prevented or delayed by intervention. Hence, early detection of persons at increased risk is essential.</p> <p> </p> <p><b>RESEARCH DESIGN AND METHODS </b></p> <p>From a population-based cohort of 5,460 clinically diagnosed Danish adults with type 1 diabetes followed 2001-2016, we developed a prediction model for ESKD accounting for the competing risk of death. Poisson regression analysis was used to estimate the model based on information routinely collected from clinical examinations. The effect of including an extended set of predictors (lipids, alcohol intake etc.) was further evaluated, and potential interactions identified in a survival tree analysis were tested. The final model was externally validated in 9,175 adults from Denmark and Scotland.</p> <p> </p> <p><b>RESULTS</b> </p> <p>During a median follow-up of 10.4 years (interquartile limits: 5.1;14.7), 303 (5.5%) of the participants (mean (SD) age 42.3 (16.5) years) developed ESKD and 764 (14.0%) died without having developed ESKD. The final ESKD prediction model included age, male sex, diabetes duration, estimated glomerular filtration rate, micro- and macroalbuminuria, systolic blood pressure, HbA<sub>1c</sub>, smoking and previous cardiovascular disease. Discrimination was excellent for 5-year risk of ESKD event with a C-statistic of 0.888 (95%CI: 0.849;0.927) in the derivation cohort and confirmed at 0.865 (0.811;0.919) and 0.961 (0.940;0.981) in the external validation cohorts from Denmark and Scotland. </p> <p> </p> <p><b>CONCLUSIONS</b> </p> <p>We have derived and validated a novel, high-performing ESKD prediction model for risk stratification in the adult type 1 diabetes population. This model may improve clinical decision making and potentially guide early intervention.</p>

scholarly journals A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes

2021 ◽  
Author(s):  
Dorte Vistisen ◽  
Gregers S. Andersen ◽  
Adam Hulman ◽  
Stuart J. McGurnaghan ◽  
Helen M. Colhoun ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
Clinical Decision Making ◽  
External Validation ◽  
End Stage Kidney Disease ◽  
Risk Of Death ◽  
Increased Risk ◽  
End Stage

<b>OBJECTIVE </b> <p>End-stage kidney disease (ESKD) is a life-threatening complication of diabetes which can be prevented or delayed by intervention. Hence, early detection of persons at increased risk is essential.</p> <p> </p> <p><b>RESEARCH DESIGN AND METHODS </b></p> <p>From a population-based cohort of 5,460 clinically diagnosed Danish adults with type 1 diabetes followed 2001-2016, we developed a prediction model for ESKD accounting for the competing risk of death. Poisson regression analysis was used to estimate the model based on information routinely collected from clinical examinations. The effect of including an extended set of predictors (lipids, alcohol intake etc.) was further evaluated, and potential interactions identified in a survival tree analysis were tested. The final model was externally validated in 9,175 adults from Denmark and Scotland.</p> <p> </p> <p><b>RESULTS</b> </p> <p>During a median follow-up of 10.4 years (interquartile limits: 5.1;14.7), 303 (5.5%) of the participants (mean (SD) age 42.3 (16.5) years) developed ESKD and 764 (14.0%) died without having developed ESKD. The final ESKD prediction model included age, male sex, diabetes duration, estimated glomerular filtration rate, micro- and macroalbuminuria, systolic blood pressure, HbA<sub>1c</sub>, smoking and previous cardiovascular disease. Discrimination was excellent for 5-year risk of ESKD event with a C-statistic of 0.888 (95%CI: 0.849;0.927) in the derivation cohort and confirmed at 0.865 (0.811;0.919) and 0.961 (0.940;0.981) in the external validation cohorts from Denmark and Scotland. </p> <p> </p> <p><b>CONCLUSIONS</b> </p> <p>We have derived and validated a novel, high-performing ESKD prediction model for risk stratification in the adult type 1 diabetes population. This model may improve clinical decision making and potentially guide early intervention.</p>

scholarly journals A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes

Diabetes Care ◽  
2021 ◽  
pp. dc202586
Author(s):  
Dorte Vistisen ◽  
Gregers S. Andersen ◽  
Adam Hulman ◽  
Stuart J. McGurnaghan ◽  
Helen M. Colhoun ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Prediction Model ◽  
End Stage Kidney Disease ◽  
End Stage

1615-P: Predicting End-Stage Kidney Disease in Type 1 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1615-P
Author(s):  
DORTE VISTISEN ◽  
GREGERS S. ANDERSEN ◽  
ADAM HULMAN ◽  
STUART MCGURNAGHAN ◽  
HELEN M. COLHOUN ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Kidney Disease ◽  
End Stage Kidney Disease ◽  
End Stage

Association of Coding Variants in Hydroxysteroid 17-beta Dehydrogenase 14 (HSD17B14) with Reduced Progression to End Stage Kidney Disease in Type 1 Diabetes

2021 ◽  
pp. ASN.2020101457
Author(s):  
Josyf Mychaleckyj ◽  
Erkka Valo ◽  
Takaharu Ichimura ◽  
Tarunveer Ahluwalia ◽  
Christian Dina ◽  
...  
Keyword(s):  
Gene Expression ◽  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Rare Variants ◽  
Disease Stage ◽  
End Stage Kidney Disease ◽  
Gene And Protein Expression ◽  
End Stage ◽  
Coding Variants

Background: Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of end stage kidney disease (ESKD) in individuals with type 1 diabetes at advanced kidney disease stage. Methods: Gene-based exome array analysis of 15,449 genes in 5 large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time-to-ESKD, testing the top gene in a 6th cohort (N=2,372/1,115 events all cohorts) and replicating in two retrospective case-control studies (N=1,072 cases, 752 controls). Deep resequencing of the top associated gene in 5 cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. Results: Protein coding variants in the hydroxysteroid 17-beta dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (N=4,196; p-value=3.3x10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other chronic kidney disease-associated renal pathologies. Conclusions: HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

scholarly journals Declining trends of diabetic nephropathy, retinopathy and neuropathy with improving diabetes care indicators in Japanese patients with type 2 and type 1 diabetes (JDDM 46)

2018 ◽  
Vol 6 (1) ◽  
pp. e000521 ◽  
Author(s):  
Hiroki Yokoyama ◽  
Shin-ichi Araki ◽  
Koichi Kawai ◽  
Katsuya Yamazaki ◽  
Osamu Tomonaga ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Chronic Kidney Disease ◽  
Type 1 Diabetes ◽  
Kidney Disease ◽  
Diabetes Care ◽  
Microvascular Complications ◽  
Treatment Target ◽  
Younger Patients

ObjectiveWe examined changes in prevalence of diabetic microvascular/macrovascular complications and diabetes care indicators for adults in Japan with type 2 and type 1 diabetes over one decade.Research design and methodsTwo independent cohorts were recruited with the same inclusion criteria in 2004 (cohort 1: 3319 with type 2 and 286 with type 1 diabetes) and in 2014 (cohort 2: 3932 with type 2 and 308 with type 1 diabetes). Prevalence of complications and care indicators including achieving treatment targets for glycemia, blood pressure, lipid control, body mass index (BMI), and smoking were compared. In addition, patients in cohort 1 were re-examined in 2014 and their data were compared with the baseline data of each cohort.ResultsIn type 2 diabetes, the prevalence of nephropathy, retinopathy, neuropathy, chronic kidney disease, current smoking and stroke significantly decreased, with improvements in achieving treatment target rates in cohort 2 two as compared with cohort 1. In type 1 diabetes, the prevalence of nephropathy, retinopathy, chronic kidney disease, and hemoglobin A1Cvalues significantly decreased. Decreases in prevalence of microvascular complications in type 2 diabetes were similarly found in each age-matched and sex-matched group, whereas younger patients exhibited marked increase in BMI and lower treatment target achieving rates compared with elderly patients. Regarding normoalbuminuric renal impairment, only a slight increase in the prevalence was observed both in type 2 and type 1 diabetes. In cohort 1, re-examined in 2014, care indicators were significantly improved from 2004, while complications increased with getting 10 years older.ConclusionsWe observed declining trends of diabetic microvascular complications with improvement in diabetes care indicators in type 2 and type 1 diabetes. Younger patients with type 2 diabetes exhibited marked increase in BMI and lower rates of achieving treatment targets compared with elderly patients, which remains a concern.

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