Evidence map›Paper›PMID 23801726›Full record

ArticleDiabetes care2013

Derivation and validation of a renal risk score for people with type 2 diabetes.

C Raina Elley, Tom Robinson, Simon A Moyes, Tim Kenealy, John Collins, Elizabeth Robinson, Brandon Orr-Walker, Paul L Drury

Open access · hybridAbstract read
In one paragraph

Article in Diabetes care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 7 pooled it
1.9field-weighted citation impact, top 14% of its field
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

52 citing papers in PubMed, 7 syntheses or guidelines pooled it, 87 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Trial
  9. Article
  10. Article
  11. Diabetic kidney disease, biomarkers, and finerenone.Diabetes, obesity & metabolism · 2026
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

C Raina ElleyCorresponding author: C. Raina Elley, c.elley@auckland.ac.nz.
Tom Robinson
Simon A Moyes
Tim Kenealy
John Collins
Elizabeth Robinson
Brandon Orr-Walker
Paul L Drury
University of Auckland · NZAuckland District Health Board · NZCounties Manukau District Health Board · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDiabetes has become the leading cause of end-stage renal disease (ESRD). Renal risk stratification could assist in earlier identification and targeted prevention. This study aimed to derive risk models to predict ESRD events in type 2 diabetes in primary care. RESEARCH DESIGN AND

methodsThe nationwide derivation cohort included adults with type 2 diabetes from the New Zealand Diabetes Cohort Study initially assessed during 2000-2006 and followed until December 2010, excluding those with pre-existing ESRD. The outcome was fatal or nonfatal ESRD event (peritoneal dialysis or hemodialysis for ESRD, renal transplantation, or death from ESRD). Risk models were developed using Cox proportional hazards models, and their performance was assessed in a separate validation cohort.

resultsThe derivation cohort included 25,736 individuals followed for up to 11 years (180,497 person-years; 86% followed for ≥5 years). At baseline, mean age was 62 years, median diabetes duration 5 years, and median HbA1c 7.2% (55 mmol/mol); 37% had albuminuria; and median estimated glomerular filtration rate (eGFR) was 77 mL/min/1.73 m2. There were 637 ESRD events (2.5%) during follow-up. Models that included sex, ethnicity, age, diabetes duration, albuminuria, serum creatinine, systolic blood pressure, HbA1c, smoking status, and previous cardiovascular disease status performed well with good discrimination and calibration in the derivation cohort and the validation cohort (n=5,877) (C-statistics 0.89-0.92), improving predictive performance compared with previous models.

conclusionsThese 5-year renal risk models performed very well in two large primary care populations with type 2 diabetes. More accurate risk stratification could facilitate earlier intervention than using eGFR and/or albuminuria alone.

Indexed as

Models, TheoreticalAgedDiabetes Mellitus, Type 2FemaleGlomerular Filtration RateGlycated HemoglobinHumansMaleMiddle AgedRisk FactorsGlycated Hemoglobin

Identifiers

PMID23801726
PMCPMC3781509
OpenAlexW2171244569

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.