Evidence mapPaperPMID 35645693Full record

ArticleEJIFCC2022

Novel Damage Biomarkers of Sepsis-Related Acute Kidney Injury.

Dániel Ragán, Zoltán Horváth-Szalai, Balázs Szirmay, Diána Mühl

Abstract read
In one paragraph

Article in EJIFCC, 2022. 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. New Insights into Cardiac Intensive Care.Reviews in cardiovascular medicine · 2026
    Review
  2. Article
  3. Article
  4. Implementation and One-Year Evaluation of Proenkephalin A in Critical Care.International journal of molecular sciences · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
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.

Dániel RagánDepartment of Laboratory Medicine, Medical School, University of Pécs, Hungary.ORCID https://orcid.org/0000-0002-5429-0168
Zoltán Horváth-SzalaiDepartment of Laboratory Medicine, Medical School, University of Pécs, Hungary.
Balázs SzirmayDepartment of Laboratory Medicine, Medical School, University of Pécs, Hungary.
Diána MühlDepartment of Anesthesiology and Intensive Therapy, Medical School, University of Pécs, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis-related acute kidney injury (AKI) is one of the most common complications of sepsis at the intensive care unit (ICU) with more adverse mortality rates. The early diagnosis and reliable monitoring of sepsis-related AKI are essential in achieving a favorable outcome. Novel serum and urinary biomarkers could yield valuable information during this process. Regarding the widely used Kidney Disease Improving Global Outcomes (KDIGO) classifications, the diagnosis of AKI is still based on the increase of serum creatinine levels and the decrease of urine output; however, these parameters have limitations in reflecting the extent of kidney damage, therefore more sensitive and specific laboratory biomarkers are needed for the early diagnosis and prognosis of sepsis-related AKI. Regarding this, several serum parameters are discussed in this review including presepsin and the most important actin scavenger proteins (gelsolin, Gc-globulin) while other urinary markers are also examined including cell cycle arrest biomarkers, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1), Cystatin C and actin. Novel biomarkers of sepsis-related AKI could facilitate the early diagnosis and monitoring of sepsis-related AKI.

Indexed as

acute kidney injurygelsolinnovel biomarkerpresepsinSepsis-3urinary actinurinary Gc-globulin

Identifiers

PMID35645693
PMCPMC9092722

What Socratic holds

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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 Socratic graph.