Evidence map›Paper›PMID 39344493›Full record

ArticleRenal failure2024

Ultrasound viscoelastic imaging in the noninvasive quantitative assessment of chronic kidney disease.

Han Yuan, Qun Huang, Jing Wen, Yong Gao

Abstract read
In one paragraph

Article in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Review
  3. Kidney Elastography in Adult Nephrology: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Article
  6. Review
  7. Review
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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

4 authors.

Han YuanDepartment of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Guangxi, China.
Qun HuangDepartment of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Guangxi, China.
Jing WenDepartment of Hematology and Rheumatology, First Affiliated Hospital of Guangxi Medical University, Guangxi, China.
Yong GaoDepartment of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Guangxi, China.ORCID 0000-0002-2468-9282

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to evaluate the clinical application value of ultrasound viscoelastic imaging in noninvasive quantitative assessment of chronic kidney disease (CKD).

methodsA total of 332 patients with CKD and 190 healthy adults as a control group were prospectively enrolled. Before kidney biopsy, ultrasound viscoelastic imaging was performed to measure the mean stiffness value (Emean), mean viscosity coefficient (Vmean), and mean dispersion coefficient (Dmean) of the renal. CKD patients were divided into three groups based on estimated glomerular filtration rate. The differences in clinic, pathology, ultrasound image parameters between the control and patient groups, or among different CKD groups were compared. The correlation between viscoelastic parameters and pathology were analyzed.

resultsEmean, Vmean, and Dmean in the control group were less than the CKD group (

conclusionsUltrasound viscoelastic imaging has advantages in noninvasive quantitative identification and evaluating renal function of CKD. Emean > 6.61 kPa, Vmean > 1.86 Pa·s, or Dmean > 7.51 m/s/kHz may suggest renal dysfunction. Combining Vmean, Dmean, and Emean can improve the efficiency of identifying CKD.

Indexed as

Elasticity Imaging TechniquesGlomerular Filtration RateKidneyRenal Insufficiency, ChronicAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedProspective StudiesUltrasonographychronic kidney diseaseinflammationinterstitial fibrosisrenal functionUltrasound viscoelastic imaging

Identifiers

PMID39344493
PMCPMC11443565

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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.