Evidence map›Paper›PMID 39021823›Full record

ArticleFrontiers in medicine2024

Biomarker-guided detection of acute kidney injury in abdominal aortic surgery: the new and the old.

Christian Nusshag, Vivienne Theobald, Markus Wortmann, Philipp Kaimann, Maximilian Dietrich, Daniel Gruneberg, Kevin Tourelle, Maik von der Forst, Markus A Weigand, Moritz S Bischoff and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Christian Nusshag *Department of Nephrology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Vivienne Theobald *Department of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Markus WortmannDepartment of Vascular, Endovascular Surgery and Transplant Surgery, Stuttgart Hospital, Stuttgart, Germany.
Philipp KaimannDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Maximilian DietrichDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Daniel GrunebergDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Kevin TourelleDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Maik von der ForstDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Markus A WeigandDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.
Moritz S BischoffDepartment of Vascular and Endovascular Surgery, University Hospital Heidelberg, Heidelberg, Germany.
Dittmar BöcklerDepartment of Vascular and Endovascular Surgery, University Hospital Heidelberg, Heidelberg, Germany.
Felix C F SchmittDepartment of Anesthesiology, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Acute kidney injury (AKI) is a common complication in patients undergoing major vascular surgery. Despite significant research efforts in this area, the incidence of AKI remains high, posing a significant challenge to healthcare systems, especially in situations where resources are limited. Early prediction of AKI severity and individualized postoperative care is therefore essential. Methods: The primary objective of this exploratory study was to assess the diagnostic value of urine cell-cycle arrest biomarkers [(TIMP-2) × (IGFBP7)] and soluble urokinase plasminogen activator receptor (suPAR) for predicting moderate or severe AKI within 24 h after open aortic surgery, and compared to routine kidney biomarkers. Seventy-five patients undergoing elective aortic surgery were included. Clinical parameters, urine and blood samples were collected preoperatively, immediately postoperatively, and 24 h later. AKI was defined using KDIGO criteria. Individual and combined diagnostic performance of biomarkers were evaluated. Results: Of the 75 patients, 61% developed AKI, of which 28% developed moderate or severe AKI within 24 h of surgery. Baseline demographics, comorbidities and kidney parameters did not differ between patients with moderate or severe AKI (AKI II/III) and none or mild AKI (AKI 0/I), except for higher preoperative suPAR levels in later AKI II/III patients. Urine osmolality, Cystatin C and serum creatinine had the highest predictive power for AKI II/III with AUCs of 0.75-0.72. (TIMP-2) × (IGFBP7), and neither (TIMP-2) × (IGFBP7) nor suPAR individually showed superior diagnostic value. Combining CysC or SCr with urine osmolality and 6 h urine output gave the best performance with AUCs of 0.86 (95% CI, 0.74-0.96) and 0.85 (95% CI, 0.75-0.95) respectively. Conclusion: Our study suggests that routine parameters like urine osmolality, CysC, SCr and 6 h urine output perform best in predicting postoperative AKI after aortic surgery compared to the new biomarkers (TIMP-2) × (IGFBP7) and suPAR. Combining biomarkers, particularly CysC or SCr with urine output, urine osmolality, may enhance diagnostic accuracy. Further validation in larger cohorts and clinical settings is warranted to establish their clinical utility.

Indexed as

acute kidney injuryaortic surgerybiomarkerscell cycle arrestintensive care medicinesoluble urokinase plasminogen activator receptor

Identifiers

PMID39021823
PMCPMC11251966

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.