Evidence map›Paper›PMID 24949439›Full record

ReviewBioMed research international2014

Circulating endothelial cells and chronic kidney disease.

Kunying Zhang, Fang Yin, Lin Lin

Open access · hybridAbstract readReview
In one paragraph

Review in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. The Future of Kawasaki Disease Diagnosis: Liquid Biopsy May Hold the Key.International journal of molecular sciences · 2024
    Review
  4. Review
  5. Chronic kidney disease in the pathogenesis of acute ischemic stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2019
    Review
  6. Circulating endothelial cells as biomarker for cardiovascular diseases.Research and practice in thrombosis and haemostasis · 2019
    Article
  7. Article
  8. Article
  9. 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

3 authors at 1 institution in 1 country.

Kunying ZhangDepartment of Nephrology, Weifang People's Hospital, No. 151 Guangwen Street, Kuiwen District, Weifang, Shandong 261041, China.
Fang YinDepartment of Nephrology, Weifang People's Hospital, No. 151 Guangwen Street, Kuiwen District, Weifang, Shandong 261041, China.
Lin LinDepartment of Nephrology, Weifang People's Hospital, No. 151 Guangwen Street, Kuiwen District, Weifang, Shandong 261041, China.
Weifang People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endothelial dysfunction may play a crucial role in initiation of the pathogenesis of vascular disease and atherosclerosis. The identification and quantification of circulating endothelial cells (CEC) have been developed as a novel marker of endothelial function. We describe, in great detail, mechanisms of endothelial dysfunction and CEC detachment. We also review the relationship between numbers of CEC and disease severity and response to treatment. In addition, we describe the possible clinical use of CEC in chronic kidney disease (CKD) and kidney transplantation. In summary, CEC have been developed as a novel approach to assess the endothelial damage. Measurement of the CEC level would provide an important diagnostic and prognostic value on the endothelium status and the long-term outcome of vascular dysfunction.

Indexed as

Endothelial CellsFlow CytometryHumansPrognosisRenal Insufficiency, ChronicVascular Diseases

Identifiers

PMID24949439
PMCPMC4052150
OpenAlexW2117433781

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.