Evidence map›Paper›PMID 32903946›Full record

ReviewKidney diseases (Basel, Switzerland)2020

Diabetic Kidney Disease: Challenges, Advances, and Opportunities.

Ya Chen, Kyung Lee, Zhaohui Ni, John Cijiang He

Abstract readReview
In one paragraph

Review in Kidney diseases (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed, 2 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

107 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  14. Current perspectives on lipid management in diabetic kidney disease: Can fibrates offer advantages over statins for renal outcomes?Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2026
    Review
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47 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

4 authors.

Ya ChenDepartment of Medicine/Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Kyung LeeDepartment of Medicine/Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Zhaohui NiDepartment of Nephrology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
John Cijiang HeDepartment of Medicine/Nephrology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Funding

The Role of LRG1 in Diabetic Kidney DiseaseR01DK117913 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Bhaskar Chandra Das, Kyung Lee · 2018 to 2026
$2.6M
NIDDK NIH HHS R01 DK117913
6 · The paper itself

Abstract

backgroundDiabetic kidney disease (DKD) is the most common cause of the end-stage renal disease (ESRD). Regardless of intensive treatments with hyperglycemic control, blood pressure control, and the use of renin-angiotensin system blockades, the prevalence of DKD remains high. Recent studies suggest that the spectrum of DKD has been changed and many progresses have been made to develop new treatments for DKD. Therefore, it is time to perform a systemic review on the new developments in the field of DKD. SUMMARY: Although the classic clinical presentation of DKD is characterized by a slow progression from microalbuminuria to macroalbuminuria and by a hyperfiltration at the early stage and progressive decline of renal function at the late stage, recent epidemiological studies suggest that DKD patients have a variety of clinical presentations and progression rates to ESRD. Some DKD patients have a decline in renal function without albuminuria but display prominent vascular and interstitial fibrosis on renal histology. DKD patients are more susceptible to acute kidney injury, which might contribute to the interstitial fibrosis. A large portion of type 2 diabetic patients with albuminuria could have overlapping nondiabetic glomerular disease, and therefore, kidney biopsy is required for differential diagnosis for these patients. Only a small portion of DKD patients eventually progress to end-stage renal failure. However, we do not have sensitive and specific biomarkers to identify these high-risk patients. Genetic factors that have a strong association with DKD progression have not been identified yet. A combination of circulating tumor necrosis factor receptor (TNFR)1, TNFR2, and kidney injury molecular 1 provides predictive value for DKD progression. Artificial intelligence could enhance the predictive values for DKD progression by combining the clinical parameters and biological markers. Sodium-glucose co-transporter-2 inhibitors should be added to the new standard care of DKD patients. Several promising new drugs are in clinical trials. KEY MESSAGES: Over last years, our understanding of DKD has been much improved and new treatments to halt the progression of DKD are coming. However, better diagnostic tools, predictive markers, and treatment options are still urgently needed to help us to better manage these patients with this detrimental disease.

Indexed as

Diabetic kidney diseaseInflammationNonproteinuric pathwayProgressionTreatment

Identifiers

PMID32903946
PMCPMC7445658

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.