Evidence map›Paper›PMID 37873973›Full record

ArticleRenal failure2023

Research on the correlation between the renal resistive index, renal microvessel density, and fibrosis.

Jingping Wu, Jian Liu, Guanghan Li, Weiliang Sun, Jiang Liu, Wenge Li, Hao Wang, Min Zheng

Abstract read
In one paragraph

Article in Renal failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

8 authors.

Jingping WuDepartment of Ultrasound Medicine, China-Japan Friendship Hospital, Beijing, China.
Jian LiuDepartment of Ultrasound Medicine, China-Japan Friendship Hospital, Beijing, China.
Guanghan LiDepartment of Ultrasound Medicine, China-Japan Friendship Hospital, Beijing, China.
Weiliang SunInstitute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Jiang LiuChina-Japan Friendship School of Clinical Medicine, Peking University, Beijing, China.
Wenge LiDepartment of Nephrology, China-Japan Friendship Hospital, Beijing, China.
Hao WangDepartment of Radiation Oncology, China-Japan Friendship Hospital, Beijing, China.
Min ZhengDepartment of Ultrasound Medicine, China-Japan Friendship Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study was designed to investigate the relationship between the renal resistive index (RRI), renal microvessel density (RMD), and fibrosis in patients with chronic kidney disease (CKD).

methodsA total of 73 CKD patients were included in the study. Prior to kidney biopsy, we recorded the RRI of the interlobar artery and the estimated glomerular filtration rate (eGFR). Immunohistochemical analysis was performed to assess CD34 expression, and Masson staining was used to evaluate histopathological specimens for RMD and the degree of fibrosis. The percentage of the positive area (PPA) was recorded. Subsequently, we investigated the correlation between RRI, RMD, and kidney fibrosis.

resultsRMD (CD34 PPA-total and CD34 PPA-peritubular capillary) showed a slight increase in early CKD stages (1-2) and gradually declined from CKD stages 2 to 5. No correlation was observed between the RRI and RMD or between the RRI and fibrosis across CKD stages 1 to 5. However, across CKD stages 2 to 5, RRI negatively correlated with CD34 PPA-glomerulus (r = -0.353,

conclusionThere was no correlation between RRI and RMD or between RRI and fibrosis across CKD stages 1 to 5 (RRI ≤ 0.7).

Indexed as

Microvascular DensityRenal Insufficiency, ChronicFibrosisHumansKidneyKidney Glomeruluschronic kidney diseasefibrosismicrovessel densityrenal resistive indexUltrasonography

Identifiers

PMID37873973
PMCPMC11001374

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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.