Evidence map›Paper›PMID 36271990›Full record

ReviewInternational urology and nephrology2023

Novel biomarkers for prognosticating diabetic kidney disease progression.

Shilna Muttickal Swaminathan, Indu Ramachandra Rao, Srinivas Vinayak Shenoy, Attur Ravindra Prabhu, Pooja Basthi Mohan, Dharshan Rangaswamy, Mohan V Bhojaraja, Shivashankara Kaniyoor Nagri, Shankar Prasad Nagaraju

Full text readReview
In one paragraph

Review in International urology and nephrology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–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

31 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Diabetic kidney disease, biomarkers, and finerenone.Diabetes, obesity & metabolism · 2026
    Review
  7. Review
  8. Article
  9. Article
  10. Urinary biomarkers of diabetic kidney disease.World journal of diabetes · 2026
    Review
  11. Review
  12. Article
  13. Review
  14. Observational
  15. Article
  16. Observational
  17. Observational
  18. Review
  19. Review
  20. 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

9 authors.

Shilna Muttickal SwaminathanDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Indu Ramachandra RaoDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Srinivas Vinayak ShenoyDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Attur Ravindra PrabhuDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Pooja Basthi MohanDepartment of Gastroenterology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Dharshan RangaswamyDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Mohan V BhojarajaDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Shivashankara Kaniyoor NagriDepartment of Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India.
Shankar Prasad NagarajuDepartment of Nephrology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Manipal, India. shankarmmcmed@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global burden of diabetic kidney disease (DKD) is escalating, and it remains as a predominant cause of the end-stage renal disease (ESRD). DKD is associated with increased cardiovascular disease and morbidity in all types of diabetes. Prediction of progression with albuminuria and eGFR is challenging in DKD, especially in non-proteinuric DKD patients. The pathogenesis of DKD is multifactorial characterized by injury to all components of the nephron, whereas albuminuria is an indicator of only glomerular injury. The limits in the diagnostic and prognostic value of urine albumin demonstrate the need for alternative and clinically significant early biomarkers, allowing more targeted and effective diabetic treatment, to reduce the burden of DKD and ESRD. Identification of biomarkers, based on multifactorial pathogenesis of DKD can be the crucial paradigm in the treatment algorithm of DKD patients. This review focuses on the potential biomarkers linked to DKD pathogenesis, particularly with the hope of broadening the diagnostic window to identify patients with different stages of DKD progression.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesKidney Failure, ChronicAlbuminuriaBiomarkersDisease ProgressionGlomerular Filtration RateHumansBiomarkersAlbuminuriaDiabetic kidney diseaseeGFRNovel biomarkers

Identifiers

PMID36271990
PMCPMC10030535

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read18
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 Socratic graph.