Evidence map›Paper›PMID 27181363›Full record

ReviewJournal of diabetes investigation2017

Clinical predictive factors in diabetic kidney disease progression.

Nicholas J Radcliffe, Jas-Mine Seah, Michele Clarke, Richard J MacIsaac, George Jerums, Elif I Ekinci

Abstract readReview
In one paragraph

Review in Journal of diabetes investigation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 5 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

113 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pharmaceutical biology · 2020
    Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

53 more citing papers are in PubMed but not listed here.

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

6 authors.

Nicholas J RadcliffeAustin Clinical School, Melbourne, Victoria, Australia.
Jas-Mine SeahAustin Health Endocrine Center, Melbourne, Victoria, Australia.
Michele ClarkeThe University of Melbourne, Melbourne, Victoria, Australia.
Richard J MacIsaacThe University of Melbourne, Melbourne, Victoria, Australia.
George JerumsThe University of Melbourne, Melbourne, Victoria, Australia.
Elif I EkinciThe University of Melbourne, Melbourne, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) represents a major component of the health burden associated with type 1 and type 2 diabetes. Recent advances have produced an explosion of 'novel' assay-based risk markers for DKD, though clinical use remains restricted. Although many patients with progressive DKD follow a classical albuminuria-based pathway, non-albuminuric DKD progression is now well recognized. In general, the following clinical and biochemical characteristics have been associated with progressive DKD in both type 1 and type 2 diabetes: increased hemoglobin A1c, systolic blood pressure, albuminuria grade, early glomerular filtration rate decline, duration of diabetes, age (including pubertal onset) and serum uric acid; the presence of concomitant microvascular complications; and positive family history. The same is true in type 2 diabetes for male sex category, in patients following an albuminuric pathway to DKD, and also true for the presence of increased pulse wave velocity. The following baseline clinical characteristics have been proposed as risk factors for DKD progression, but with further research required to assess the nature of any relationship: dyslipidemia (including low-density lipoprotein, total and high-density lipoprotein cholesterol); elevated body mass index; smoking status; hyperfiltration; decreases in vitamin D, hemoglobin and uric acid excretion (all known consequences of advanced DKD); and patient test result visit-to-visit variability (hemoglobin A1c, blood pressure and high-density lipoprotein cholesterol). The development of multifactorial 'renal risk equations' for type 2 diabetes has the potential to simplify the task of DKD prognostication; however, there are currently none for type 1 diabetes-specific populations. Significant progress has been made in the prediction of DKD progression using readily available clinical data, though further work is required to elicit the role of several variables, and to consolidate data to facilitate clinical implementation.

Indexed as

Disease ProgressionAge FactorsBiomarkersDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Diabetic NephropathiesFemaleHumansMaleRisk FactorsSex FactorsBiomarkersDiabetic kidney diseaseDiabetic nephropathyRisk factors

Identifiers

PMID27181363
PMCPMC5217935

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.