Evidence map›Paper›PMID 41694973›Full record

ArticleCureus2026

Predicting the Course of Immunoglobulin A Nephropathy Using Urinary Soluble Cluster of Differentiation 163 as a Prognostic Biomarker.

S K Afsana Hossain, Muhammad Nazrul Islam, A H Hamid Ahmed, H M Mohiuddin Alamgir, Md Saiful Ahammad Sarker, Mohammad Kamrul Hasan, Tashnia Tamanna Chowdhury, Mamun Chowdhury Raju, A K M Shahidur Rahman, S M Remin Rafi and 1 more

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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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

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

S K Afsana HossainNephrology, Directorate General of Health Services (DGHS), Dhaka, BGD.
Muhammad Nazrul IslamNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.
A H Hamid AhmedNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.
H M Mohiuddin AlamgirNephrology, Directorate General of Health Services (DGHS), Dhaka, BGD.
Md Saiful Ahammad SarkerNephrology, Directorate General of Health Services (DGHS), Dhaka, BGD.
Mohammad Kamrul HasanNephrology, East West Medical College and Hospital, Dhaka, BGD.
Tashnia Tamanna ChowdhuryNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.
Mamun Chowdhury RajuNephrology, Directorate General of Health Services (DGHS), Dhaka, BGD.
A K M Shahidur RahmanNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.
S M Remin RafiNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.
Md Masudul KarimNephrology, Bangladesh Medical University (BMU), Dhaka, BGD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmunoglobulin A nephropathy (IgAN) is the most prevalent primary glomerulonephritis (GN) worldwide and is often underdiagnosed because of its asymptomatic presentation. Proteinuria-based assessment in monitoring disease progression is limited. Early renal biopsy may fail to predict disease severity. So, the development of a non-invasive biomarker can predict early disease progression.

objectiveTo evaluate urinary soluble cluster differentiation 163 (u-sCD163) in predicting short-term treatment response and its correlation with histologic activity in biopsy-proven IgAN. METHODOLOGY: This prospective observational study was carried out at the Department of Nephrology, Bangladesh Medical University (BMU), Dhaka, Bangladesh. A total of 55 patients with biopsy-proven primary IgAN were enrolled. Urine routine microscopic examination (R/M/E), 24-hour urinary total protein (UTP), and serum creatinine were measured at baseline, and at each follow-up (every three-month interval, up to six months). u-sCD163 was measured at baseline and at the sixth month. Patients were managed according to the KDIGO, 2021guideline and followed up in the third and sixthmonths.

resultsMean age of the study patients was 31.3 ± 5.61 years. The sex distribution highlights a male predominance, as the male-to-female ratio was 1.7:1. Baseline u-sCD163 was 3.78 ± 0.96 ng/mg in the partial response group and 7.82 ± 4.00 ng/mg in the no-response group (

conclusionsu-sCD163 may be a potential biomarker to predict the short-term treatment response status and histologic activity in biopsy-proven IgAN. Elevated biomarkers at baseline were associated with more proteinuria and risk of response failure.

Indexed as

biomarkerdisease progressioniga nephropathyresponse statusurinary scd163

Identifiers

PMID41694973
PMCPMC12902705

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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.