Evidence map›Paper›PMID 41511474›Full record

ReviewJornal brasileiro de nefrologia2026

Novel biomarkers for CKD risk stratification: a literature review.

Sariya Khan, Aleena Zobairi, Elaf Rehan, Ashraf Hussein Mohammed

Abstract readReview
In one paragraph

Review in Jornal brasileiro de nefrologia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sariya KhanBatterjee Medical College, General Medicine Practice Program, Jeddah, Saudi Arabia.ORCID http://orcid.org/0009-0003-9809-872X
Aleena ZobairiBatterjee Medical College, General Medicine Practice Program, Jeddah, Saudi Arabia.ORCID http://orcid.org/0009-0009-4751-3317
Elaf RehanBatterjee Medical College, General Medicine Practice Program, Jeddah, Saudi Arabia.ORCID http://orcid.org/0009-0003-0899-971X
Ashraf Hussein MohammedMansoura University, Mansoura, Egypt.ORCID http://orcid.org/0000-0003-3302-1177

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionChronic kidney disease (CKD) is a progressive illness with high morbidity and mortality that warrants early and accurate risk stratification for optimal management. The traditional biomarkers, serum creatinine and estimated glomerular filtration rate (eGFR), are insufficient for detecting early CKD and long-term prognosis. Novel biomarkers have emerged as effective tools to complement CKD diagnosis, prognosis, and therapeutic monitoring.

aimThe aim of this research was to determine the potential of novel biomarkers in CKD risk stratification and their clinical significance for improving early detection, monitoring disease progression, and developing individualized treatment strategies.

methodsA literature review was conducted by searching the PubMed, Scopus, and Embase databases to identify studies on novel CKD biomarkers, including cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and specific microRNAs.

resultsEmerging evidence suggests that novel biomarkers provide superior predictive abilities compared to traditional markers. Cystatin C is more accurate in kidney function estimation, whereas NGAL and KIM-1 are markers of early kidney injury. MicroRNAs show potential in distinguishing between CKD subtypes and predicting disease progression. Clinical application of these biomarkers may enhance CKD risk stratification, allowing more targeted intervention strategies.

conclusionNew biomarkers in CKD risk stratification represent a watershed moment in nephrology, offering improved early detection and prognostic accuracy. While promising, additional large-scale research and clinical validation are required before they can be used routinely.

Indexed as

Renal Insufficiency, ChronicBiomarkersCystatin CHepatitis A Virus Cellular Receptor 1HumansLipocalin-2Risk AssessmentBiomarkersCystatin CHAVCR1 protein, humanHepatitis A Virus Cellular Receptor 1Lipocalin-2

Identifiers

PMID41511474
PMCPMC12788398

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Registered trials

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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.