Evidence map›Paper›PMID 31807796›Full record

ArticleDiabetologia2020

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

Marco Colombo, Stuart J McGurnaghan, Samira Bell, Finlay MacKenzie, Alan W Patrick, John R Petrie, John A McKnight, Sandra MacRury, Jamie Traynor, Wendy Metcalfe and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Marco ColomboUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Stuart J McGurnaghanMRC Institute of Genetic and Molecular Medicine, The University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK.
Samira BellRenal Unit, Ninewells Hospital, Dundee, UK.
Finlay MacKenzieBirmingham Quality/UK NEQAS, University Hospitals NHS Foundation Trust, Birmingham, UK.
Alan W PatrickRoyal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK.
John R PetrieInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
John A McKnightWestern General Hospital, NHS Lothian, Edinburgh, UK.
Sandra MacRuryDepartment of Diabetes and Cardiovascular Science, University of Highlands and Islands, Inverness, UK.
Jamie TraynorNHS Greater Glasgow and Clyde, Glasgow Renal and Transplant Unit, Queen Elizabeth University Hospital, Glasgow, UK.
Wendy MetcalfeRoyal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK.
Paul M McKeigueUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Helen M ColhounMRC Institute of Genetic and Molecular Medicine, The University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK. helen.colhoun@igmm.ed.ac.uk.ORCID 0000-0002-8345-3288
Scottish Diabetes Research Network (SDRN) Type 1 Bioresource Investigators and the Scottish Renal Registry

Funding

Breakthrough T1D 1-SRA-2016-334-Q-RChief Scientist Office ETM/47Diabetes UK 10/0004010
6 · The paper itself

Abstract

aims/hypothesisThe 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.

methodsWe 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.

resultsMedian 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

conclusionsThese 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.

Indexed as

AdultAgedCohort StudiesDiabetes Mellitus, Type 1Diabetic NephropathiesDisease ProgressionFemaleGlomerular Filtration RateHumansKidney Failure, ChronicKidney Function TestsMaleMiddle AgedPredictive Value of TestsPrevalencePrognosisClinical scienceEpidemiologyNephropathy

Identifiers

PMID31807796
PMCPMC6997248

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.