Evidence map›Paper›PMID 35574553›Full record

ArticleFrontiers in surgery2022

Procalcitonin, Interleukin-6 and C-reactive Protein Levels Predict Renal Adverse Outcomes and Mortality in Patients with Acute Type A Aortic Dissection.

Xuelian Chen, Jiaojiao Zhou, Miao Fang, Jia Yang, Xin Wang, Siwen Wang, Lichuan Yang

Abstract read
In one paragraph

Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

7 authors.

Xuelian ChenDivision of Nephrology, Department of Medicine, West China Hospital of Sichuan University, Chengdu, China.
Jiaojiao ZhouDepartment of Ultrasound, West China Hospital of Sichuan University, Chengdu, China.
Miao FangDepartment of Orthopedics, Second People's Hospital of Chengdu, Chengdu, China.
Jia YangDivision of Nephrology, Department of Medicine, West China Hospital of Sichuan University, Chengdu, China.
Xin WangDepartment of Pediatric Nephrology, West China Second University Hospital, Sichuan University, Chengdu, China.
Siwen WangDivision of Nephrology, Department of Medicine, West China Hospital of Sichuan University, Chengdu, China.
Lichuan YangDivision of Nephrology, Department of Medicine, West China Hospital of Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute type A aortic coarctation (AAAD) is a highly deadly and serious life-threatening disease. The purpose of this study was to estimate the predictive value of peak procalcitonin, interleukin-6, and C-reactive protein levels on adverse renal outcomes and mortality in patients undergoing surgery for AAAD. Methods: Perioperative peak PCT, CRP, and IL-6 levels were retrospectively collected in 331 patients hospitalized with AAAD from 2009 to 2021. The primary endpoints were AKI stage 2-3 and mortality. The receiver operating characteristic (ROC) curves were used to compare the predictive values of peak PCT, CRP, and IL-6 for different clinical outcomes. Multivariable logistic regression analysis was used to find risk factors for AKI and 30-day mortality. Results: The incidence of AKI stage 2-3 following AAAD was 50.8% (168/331). The 30-day and overall mortality were significantly greater in the AKI 2-3 group than in the AKI 0-1 group ( Conclusion: In patients with surgery for AAAD, peak PCT provides a well-predictive indicator of AKI stage 2-3 and peak IL-6 indicates a favorable predictor of 30-day mortality.

Indexed as

acute type A aortic coarctationadverse renal outcomesC-reactive proteininflammatory biomarkersinterleukin-6mortalityprocalcitonin

Identifiers

PMID35574553
PMCPMC9096660

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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.