Evidence map›Paper›PMID 33828625›Full record

ArticlePolish journal of radiology2021

Elastography: a surrogate marker of renal allograft fibrosis - quantification by shear-wave technique.

Gulab Chhajer, Venkatesh Kasi Arunachalam, Rajkumar Ramasamy, Pankaj Mehta, Mathew Cherian

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polish journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 26% of its field
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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Gulab ChhajerKushal Imaging and Diagnostics Center, Sumerpur, India.
Venkatesh Kasi ArunachalamKovai Medical Center and Hospital, Coimbatore, India.
Rajkumar RamasamyKovai Medical Center and Hospital, Coimbatore, India.
Pankaj MehtaKMCHIHSR, Coimbatore, India.
Mathew CherianKovai Medical Center and Hospital, Coimbatore, India.
Kovai Medical Center and Hospital · INSpan Diagnostics (India) · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRenal fibrosis is the most common cause of allograft failure in kidney transplantations. Evaluation of renal abnormalities has progressed considerably over the past years. Currently, the diagnosis of intrarenal fibrosis and quantification of its development with non-invasive assessment tools is possible. This may help in early detection of renal allograft dysfunction. This study sought to assess the efficacy of 2D real-time shear-wave elastography (SWE) in the quantitative measurement of renal allograft dysfunction.

methodsA total of 172 patients were included in our study. SWE was performed in all these patients just before renal allograft biopsy. The cortical elasticity was assessed and described in terms of Young's modulus (kPa). Banff histopathological grading obtained from transplant kidney tissue biopsy was taken as the reference standard. The potential correlation between SWE scores and Banff classification was performed.

resultsThere was a significant correlation between the Banff grade and mean SWE score, with a correlation coefficient of 0.665 (

conclusionsRenal stiffness quantified by 2D SWE showed significant correlation with histopathological renal fibrosis. Thus, the study suggests that shear-wave elastography could be used as a surrogate marker for early detection of renal fibrosis.

Indexed as

elastographyrenal fibrosisrenal transplantSWEtransplant fibrosis

Identifiers

PMID33828625
PMCPMC8018265
OpenAlexW3151999877

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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.