Evidence map›Paper›PMID 38137465›Full record

ArticleBiomedicines2023

Urinary Collectrin as Promising Biomarker for Acute Kidney Injury in Patients Undergoing Cardiac Surgery.

Johanna Tichy, Sahra Pajenda, Martin H Bernardi, Ludwig Wagner, Sylvia Ryz, Monika Aiad, Daniela Gerges, Alice Schmidt, Andrea Lassnigg, Harald Herkner and 1 more

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Observational
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

11 authors at 1 institution in 1 country.

Johanna TichyDepartment of Anesthesiology, Intensive Care Medicine and Pain Medicine, Division of Cardiac Thoracic Vascular Anesthesia and Intensive Care Medicine, Medical University of Vienna, 1090 Vienna, Austria.
Sahra PajendaDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Martin H BernardiDepartment of Anesthesiology, Intensive Care Medicine and Pain Medicine, Division of Cardiac Thoracic Vascular Anesthesia and Intensive Care Medicine, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-8297-898X
Ludwig WagnerDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Sylvia RyzDepartment of Anesthesiology, Intensive Care Medicine and Pain Medicine, Division of Cardiac Thoracic Vascular Anesthesia and Intensive Care Medicine, Medical University of Vienna, 1090 Vienna, Austria.
Monika AiadDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Daniela GergesDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Alice SchmidtDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Andrea LassniggDepartment of Anesthesiology, Intensive Care Medicine and Pain Medicine, Division of Cardiac Thoracic Vascular Anesthesia and Intensive Care Medicine, Medical University of Vienna, 1090 Vienna, Austria.
Harald HerknerDepartment of Emergency Medicine, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0003-1329-6149
Wolfgang WinnickiDepartment of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-0511-6120
Medical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly detection of acute kidney injury (AKI) is crucial for timely intervention and improved patient outcomes after cardiac surgery. This study aimed to evaluate the potential of urinary collectrin as a novel biomarker for AKI in this patient population.

methodsIn this prospective, observational cohort study, 63 patients undergoing elective cardiac surgery with cardiopulmonary bypass (CPB) were studied at the Medical University of Vienna between 2016 and 2018. We collected urine samples prospectively at four perioperative time points, and urinary collectrin was measured using an enzyme-linked immunosorbent assay. Patients were divided into two groups, AKI and non-AKI, defined by Kidney Disease: Improving Global Outcomes Guidelines, and differences between groups were analyzed.

resultsPostoperative AKI was found in 19 (30%) patients. Urine sample analysis revealed an inverse correlation between urinary collectrin and creatinine and AKI stages, as well as significant changes in collectrin levels during the perioperative course. Baseline collectrin levels were 5050 ± 3294 pg/mL, decreased after the start of CPB, reached their nadir at the end of surgery, and began to recover slightly on postoperative day (POD) 1. The most effective timepoint for distinguishing between AKI and non-AKI patients based on collectrin levels was POD 1, with collectrin levels of 2190 ± 3728 pg/mL in AKI patients and 3768 ± 3435 pg/mL in non-AKI patients (

conclusionsUrinary collectrin shows promise as a novel biomarker for the early detection of AKI in patients undergoing cardiac surgery on CPB. Its dynamic changes throughout the perioperative period, especially on POD 1, provide valuable insights for timely diagnosis and intervention. Further research and validation studies are needed to confirm its clinical usefulness and potential impact on patient outcomes.

Indexed as

acute kidney injurybiomarkercardiac surgerycollectrin

Identifiers

PMID38137465
PMCPMC10741128
OpenAlexW4389453576

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.