Evidence map›Paper›PMID 34635609›Full record

ArticleAnnals of laboratory medicine2022

Diagnostic Characteristics of Urinary Red Blood Cell Distribution Incorporated in UF-5000 for Differentiation of Glomerular and Non-Glomerular Hematuria.

Hanwool Cho, Jaeeun Yoo, Hyunjung Kim, Hyunsik Jang, Yonggoo Kim, Hyojin Chae

Open access · diamondAbstract read
In one paragraph

Article in Annals of laboratory medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

20 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Evaluation of the fully automated urine particle analyzer UF-1500.Journal of clinical laboratory analysis · 2023
    Article
  18. Review
  19. Article
  20. 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

6 authors at 3 institutions in 1 country.

Hanwool ChoDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0002-5956-480X
Jaeeun YooDepartment of Laboratory Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0001-9917-5393
Hyunjung KimDepartment of Laboratory Medicine, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0003-4795-842X
Hyunsik JangDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0001-5440-4009
Yonggoo KimDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0003-2808-3795
Hyojin ChaeDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID https://orcid.org/0000-0001-5870-1887
The Catholic University of Korea Seoul St. Mary's Hospital · KRThe Catholic University of Korea Incheon St. Mary's Hospital · KRThe Catholic University of Korea Uijeongbu St. Mary's Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutomated urine sediment analysis has been developed to address the limitations of microscopic examination of dysmorphic red blood cells (RBCs). We evaluated the urinary RBC distribution (URD) parameter of a recently launched automated urinary flow cytometry analyzer, UF-5000 (Sysmex, Kobe, Japan), to differentiate glomerular hematuria (GH) from non-GH (NGH).

methodsSamples submitted for urine sediment analysis from patients with hematuria (>20 RBCs/μL) were divided into derivation (N=156; 101 GH, 55 NGH) and validation cohorts (N=107; 60 GH, 47 NGH). The clinical diagnosis of GH or NGH was established based on clinical data review. Differences in UF-5000 parameters (URD, small RBC, lysed RBC, RBC-P70FSC, RBC-SF-FSC-W, mean forward-scattered light, and mean side-scattered light) between GH and NGH, and areas under the ROC curves (AUC) were analyzed in the derivation cohort. The derived ideal cut-off value was evaluated in the validation cohort. We applied the Kitasato criteria to compare the diagnostic performance.

resultsURD (%), differed significantly between GH and NGH (

conclusionsURD is a rapid, objective, and quantitative measure that can be used to differentiate GH and NGH.

Indexed as

HematuriaKidney DiseasesCell DifferentiationErythrocytesHumansKidney GlomerulusAutomated urinary flow cytometry analyzerGlomerular hematuriaUF-5000Urinary RBC distribution

Identifiers

PMID34635609
PMCPMC8548254
OpenAlexW3205216910

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.