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Published in: Diabetologia 3/2020

Open Access 01-03-2020 | Albuminuria | Article

Predicting renal disease progression in a large contemporary cohort with type 1 diabetes mellitus

Authors: Marco Colombo, Stuart J. McGurnaghan, Samira Bell, Finlay MacKenzie, Alan W. Patrick, John R. Petrie, John A. McKnight, Sandra MacRury, Jamie Traynor, Wendy Metcalfe, Paul M. McKeigue, Helen M. Colhoun, on behalf of the Scottish Diabetes Research Network (SDRN) Type 1 Bioresource Investigators and the Scottish Renal Registry

Published in: Diabetologia | Issue 3/2020

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Abstract

Aims/hypothesis

The aim of this study was to provide data from a contemporary population-representative cohort on rates and predictors of renal decline in type 1 diabetes.

Methods

We used data from a cohort of 5777 people with type 1 diabetes aged 16 and older, diagnosed before the age of 50, and representative of the adult population with type 1 diabetes in Scotland (Scottish Diabetes Research Network Type 1 Bioresource; SDRNT1BIO). We measured serum creatinine and urinary albumin/creatinine ratio (ACR) at recruitment and linked the data to the national electronic healthcare records.

Results

Median age was 44.1 years and diabetes duration 20.9 years. The prevalence of CKD stages G1, G2, G3 and G4 and end-stage renal disease (ESRD) was 64.0%, 29.3%, 5.4%, 0.6%, 0.7%, respectively. Micro/macroalbuminuria prevalence was 8.6% and 3.0%, respectively. The incidence rate of ESRD was 2.5 (95% CI 1.9, 3.2) per 1000 person-years. The majority (59%) of those with chronic kidney disease stages G3–G5 did not have albuminuria on the day of recruitment or previously. Over 11.6 years of observation, the median annual decline in eGFR was modest at −1.3 ml min−1 [1.73 m]−2 year−1 (interquartile range [IQR]: −2.2, −0.4). However, 14% experienced a more significant loss of at least 3 ml min−1 [1.73 m]−2. These decliners had more cardiovascular disease (OR 1.9, p = 5 × 10−5) and retinopathy (OR 1.3 p = 0.02). Adding HbA1c, prior cardiovascular disease, recent mean eGFR and prior trajectory of eGFR to a model with age, sex, diabetes duration, current eGFR and ACR maximised the prediction of final eGFR (r2 increment from 0.698 to 0.745, p < 10−16). Attempting to model nonlinearity in eGFR decline or to detect latent classes of decliners did not improve prediction.

Conclusions

These data show much lower levels of kidney disease than historical estimates. However, early identification of those destined to experience significant decline in eGFR remains challenging.
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Literature
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go back to reference KDIGO Work Group (2013) KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int Suppl 3:1–150CrossRef KDIGO Work Group (2013) KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int Suppl 3:1–150CrossRef
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go back to reference Shah BV, Levey AS (1992) Spontaneous changes in the rate of decline in reciprocal serum creatinine: errors in predicting the progression of renal disease from extrapolation of the slope. J Am Soc Nephrol 2(7):1186–1191PubMed Shah BV, Levey AS (1992) Spontaneous changes in the rate of decline in reciprocal serum creatinine: errors in predicting the progression of renal disease from extrapolation of the slope. J Am Soc Nephrol 2(7):1186–1191PubMed
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Metadata
Title
Predicting renal disease progression in a large contemporary cohort with type 1 diabetes mellitus
Authors
Marco Colombo
Stuart J. McGurnaghan
Samira Bell
Finlay MacKenzie
Alan W. Patrick
John R. Petrie
John A. McKnight
Sandra MacRury
Jamie Traynor
Wendy Metcalfe
Paul M. McKeigue
Helen M. Colhoun
on behalf of the Scottish Diabetes Research Network (SDRN) Type 1 Bioresource Investigators and the Scottish Renal Registry
Publication date
01-03-2020
Publisher
Springer Berlin Heidelberg
Published in
Diabetologia / Issue 3/2020
Print ISSN: 0012-186X
Electronic ISSN: 1432-0428
DOI
https://doi.org/10.1007/s00125-019-05052-z

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