Evidence mapPaperPMID 37545693Full record

ReviewBiochemia medica2023

Diagnostic challenges of diabetic kidney disease.

Marijana Vučić Lovrenčić, Sandra Božičević, Lea Smirčić Duvnjak

Abstract readReview
In one paragraph

Review in Biochemia medica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
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  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. ABCDE to identify and prevent chronic kidney disease: a call to action.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
    Article
  14. Article
  15. Article
  16. A nomograph model for predicting the risk of diabetes nephropathy.International urology and nephrology · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Marijana Vučić LovrenčićDepartment of clinical chemistry and laboratory medicine, University hospital Merkur, Zagreb, Croatia.
Sandra BožičevićDepartment of clinical chemistry and laboratory medicine, University hospital Merkur, Zagreb, Croatia.
Lea Smirčić DuvnjakVuk Vrhovac University clinic for diabetes, endocrinology and metabolic diseases, University hospital Merkur, Zagreb, Croatia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) is one of the most common microvascular complications of both type 1 and type 2 diabetes and the most common cause of the end-stage renal disease (ESRD). It has been evidenced that targeted interventions at an early stage of DKD can efficiently prevent or delay the progression of kidney failure and improve patient outcomes. Therefore, regular screening for DKD has become one of the fundamental principles of diabetes care. Long-established biomarkers such as serum-creatinine-based estimates of glomerular filtration rate and albuminuria are currently the cornerstone of diagnosis and risk stratification in routine clinical practice. However, their immanent biological limitations and analytical variations may influence the clinical interpretation of the results. Recently proposed new predictive equations without the variable of race, together with the evidence on better accuracy of combined serum creatinine and cystatin C equations, and both race- and sex-free cystatin C-based equation, have enabled an improvement in the detection of DKD, but also require the harmonization of the recommended laboratory tests, wider availability of cystatin C testing and specific approach in various populations. Considering the complex pathophysiology of DKD, particularly in type 2 diabetes, a panel of biomarkers is needed to classify patients in terms of the rate of disease progression and/or response to specific interventions. With a personalized approach to diagnosis and treatment, in the future, it will be possible to respond to DKD better and enable improved outcomes for numerous patients worldwide.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesBiomarkersCystatin CGlomerular Filtration RateHumansBiomarkersCystatin Calbuminuriabiomarkersdiabetic nephropathydiagnostic testsglomerular filtration rate

Identifiers

PMID37545693
PMCPMC10373061

What Socratic holds

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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.