Evidence map›Paper›PMID 27525056›Full record

ReviewWorld journal of diabetes2016

Early detection of diabetic kidney disease: Present limitations and future perspectives.

Chih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of diabetes, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

47 citing papers in PubMed, 79 citations in OpenAlex.

  1. Observational
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  7. Review
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  9. Article
  10. Observational
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  18. Review
  19. Article
  20. Exosomes in Diabetic Kidney Disease.Kidney diseases (Basel, Switzerland) · 2023
    Review
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

3 authors at 1 institution in 1 country.

Chih-Hung LinChih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.
Yi-Cheng ChangChih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.
Lee-Ming ChuangChih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.
National Taiwan University Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is one of the most common diabetic complications, as well as the leading cause of chronic kidney disease and end-stage renal disease around the world. To prevent the dreadful consequence, development of new assays for diagnostic of DKD has always been the priority in the research field of diabetic complications. At present, urinary albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are the standard methods for assessing glomerular damage and renal function changes in clinical practice. However, due to diverse tissue involvement in different individuals, the so-called "non-albuminuric renal impairment" is not uncommon, especially in patients with type 2 diabetes. On the other hand, the precision of creatinine-based GFR estimates is limited in hyperfiltration status. These facts make albuminuria and eGFR less reliable indicators for early-stage DKD. In recent years, considerable progress has been made in the understanding of the pathogenesis of DKD, along with the elucidation of its genetic profiles and phenotypic expression of different molecules. With the help of ever-evolving technologies, it has gradually become plausible to apply the thriving information in clinical practice. The strength and weakness of several novel biomarkers, genomic, proteomic and metabolomic signatures in assisting the early diagnosis of DKD will be discussed in this article.

Indexed as

BiomarkersDiabetic kidney diseaseEarly diagnosisGenomics

Identifiers

PMID27525056
PMCPMC4958689
OpenAlexW2494850740

What OpenQuestion holds

Textmetadata
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.