Evidence map›Paper›PMID 23781310›Full record

ArticleEndocrine connections2012

IGFBP2 is a biomarker for predicting longitudinal deterioration in renal function in type 2 diabetes.

Ram P Narayanan, Bo Fu, Adrian H Heald, Kirk W Siddals, Robert L Oliver, Julie E Hudson, Antony Payton, Simon G Anderson, Anne White, William E R Ollier and 1 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Endocrine connections, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

24 citing papers in PubMed, 31 citations in OpenAlex.

  1. The insulin-like growth factor system and the progression of renal complications of type 2 diabetes.Diabetic medicine : a journal of the British Diabetic Association · 2026
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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Ram P NarayananVascular Research Group The University of Manchester Manchester, M13 9PT UK.
Bo Fu
Adrian H Heald
Kirk W Siddals
Robert L Oliver
Julie E Hudson
Antony Payton
Simon G Anderson
Anne White
William E R Ollier
J Martin Gibson
Pulmonary Vascular Research Institute · GBCardiovascular Medical Group · USUniversity of Manchester · GBUniversity of Salford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveInsulin-like growth factors are implicated in the development of diabetic nephropathy. IGF-binding protein 2 (IGFBP2) and IGF2 are expressed in the kidney, but their associations with diabetic nephropathy are unclear. We therefore tested the hypothesis that circulating levels of IGF2 and IGFBP2 predict longitudinal renal function in individuals with type 2 diabetes. DESIGN AND

methodsIGFBP2 and IGF2 measurements were performed in 436 individuals (263 males) with type 2 diabetes. Linear mixed-effect regression analysis was used to model the relationship between plasma IGFBP2 concentration and longitudinal changes in estimated glomerular filtration rate (eGFR) over an 8-year period. Analyses were also performed for IGF1, IGF2, IGFBP1 and IGFBP3 concentrations as predictors of longitudinal renal outcomes.

resultsHigh IGFBP2 concentration at baseline was associated with a decreased eGFR over an 8-year period (β=-0.02, (95% confidence interval -0.03 to -0.01), P<0.001). High IGFBP1, IGFBP2 and IGFBP3 were also associated with low baseline eGFR concentration.

conclusionThis study demonstrates that IGFBP2 is a predictor of longitudinal deterioration of renal function in type 2 diabetes.

Indexed as

IGFBP2longitudinal trendsreal-world datarenal function

Identifiers

PMID23781310
PMCPMC3681324
OpenAlexW2152330133

What OpenQuestion holds

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LicenceCC BY
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.