ReviewJournal of diabetes research2026
Advances in the Identification of Novel Urinary Biomarkers for Diabetic Kidney Disease.
Review in Journal of diabetes research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Advances in the Identification of Novel Urinary Biomarkers for Diabetic Kidney Disease.Journal of diabetes research · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
Diabetic kidney disease (DKD) is a major microvascular complication of diabetes and remains one of the leading causes of end-stage renal disease, significantly affecting patients' survival rates and quality of life. Currently, commonly used clinical assessment indicators include proteinuria and estimated glomerular filtration rate (eGFR); however, these indicators have limited sensitivity, making it difficult to detect early kidney damage in a timely manner and to accurately monitor disease progression. This review provides a comprehensive overview of recent progress in identifying various urinary biomarkers that reflect renal tubular injury, oxidative stress, inflammatory responses, fibrotic remodeling, metabolic dysregulation, and exosomal components. Furthermore, we discuss the potential clinical applications of these biomarkers in DKD early diagnosis, disease stratification, and prognostic evaluation. Looking ahead to the future and the ongoing development of multiomics integration and artificial intelligence-assisted modeling, urinary biomarkers are expected to drive DKD diagnosis and management toward a future characterized by early detection, precision, dynamic monitoring, and noninvasive assessment.
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What Socratic holds
Registered trials
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.