Evidence map›Paper›PMID 35337004›Full record

ArticleViruses2022

Clinical and Immunological Predictors of Hemorrhagic Fever with Renal Syndrome Outcome during the Early Phase.

Geum-Young Lee, Won-Keun Kim, Jin Sun No, Yongjin Yi, Hayne Cho Park, Jaehun Jung, Seungchan Cho, Jingyeong Lee, Seung-Ho Lee, Kyungmin Park and 2 more

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Predictors of Severity in Hemorrhagic Fever with Renal Syndrome.International journal of general medicine · 2025
    Article
  7. Article
  8. 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

12 authors at 7 institutions in 1 country.

Geum-Young LeeDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.
Won-Keun KimDepartment of Microbiology, College of Medicine, Hallym University, Chuncheon 24252, Korea.ORCID 0000-0003-3178-8569
Jin Sun NoDivision of High-Risk Pathogens, Bureau of Infectious Diseases Diagnosis Control, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Yongjin YiDivision of Nephrology, Department of Internal Medicine, Dankook University Hospital, Cheonan 31116, Korea.ORCID 0000-0001-8553-7189
Hayne Cho ParkDepartment of Internal Medicine, Kangnam Sacred Heart Hospital, Seoul 02841, Korea.
Jaehun JungDepartment of Preventive Medicine, Gachon University College of Medicine, Incheon 21556, Korea.
Seungchan ChoDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.
Jingyeong LeeDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.
Seung-Ho LeeChem-Bio Technology Center, Agency for Defense Development, Daejeon 34075, Korea.ORCID 0000-0002-7840-422X
Kyungmin ParkDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.ORCID 0000-0002-2132-0674
Jongwoo KimDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.
Jin-Won SongDepartment of Microbiology, College of Medicine, Korea University, Seoul 02841, Korea.ORCID 0000-0003-0796-8332
Korea University · KRAgency for Defense Development · KRDankook University Hospital · KRGachon University · KRHallym University · KRHallym University Kangnam Sacred Heart Hospital · KRKorea Disease Control and Prevention Agency · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to accurately predict the early progression of hemorrhagic fever with renal syndrome (HFRS) is crucial for reducing morbidity and mortality rates in severely affected patients. However, the utility of biomarkers for predicting clinical outcomes remains elusive in HFRS. The aims of the current study were to analyze the serum levels of immune function-related proteins and identify novel biomarkers that may help ascertain clinical outcomes of HFRS. Enzyme-linked immunosorbent assay, Luminex, and bioanalyzer assays were used to quantitatively detect 15 biomarkers in 49 serum samples of 26 patients with HFRS. High hemoglobin (HGB) and low urine output (UO) levels were identified as potential biomarkers associated with the acute HFRS. The serum soluble urokinase plasminogen activator receptor (suPAR) and C-X-C motif chemokine ligand 10 (CXCL10) values increased in the early phase of diseases. Elevated suPAR, interleukin-10 (IL-10), CXCL10, and decreased transforming growth factor-beta 3 (TGF-β3) were representative predictors of the disease severity. Upregulation of the HGB showed a significant correlation with high levels of suPAR and CXCL10. Reduced UO positively correlated with increased suPAR, CXCL10, and TGF-β2, and decreased vascular endothelial growth factor and TGF-β3. The changing HGB and UO criteria, high suPAR, IL-10, CXCL10, and low TGF-β3 of HFRS raise significant awareness for physicians regarding prospective biomarkers for monitoring early warning signs of HFRS. This study provides critical insights into the clinical and immunological biomarkers for disease severity and progression in patients with HFRS to identify early predictions of fatal outcomes.

Indexed as

Hemorrhagic Fever with Renal SyndromeBiomarkersHumansInterleukin-10Receptors, Urokinase Plasminogen ActivatorTransforming Growth Factor beta3Vascular Endothelial Growth Factor ABiomarkersInterleukin-10Receptors, Urokinase Plasminogen ActivatorTransforming Growth Factor beta3Vascular Endothelial Growth Factor Abiomarkerearly phasehemorrhagic fever with renal syndromeprognosisseverity

Identifiers

PMID35337004
PMCPMC8954228
OpenAlexW4221055702

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.