Evidence map›Paper›PMID 33833617›Full record

ArticleMediators of inflammation2021

C-Reactive Protein-to-Albumin Ratio Predicts Sepsis and Prognosis in Patients with Severe Burn Injury.

Yaohua Yu, Weiwei Wu, Yanyan Dong, Jiliang Li

Abstract read
In one paragraph

Article in Mediators of inflammation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. PCT-to-albumin ratio and CRP-to-albumin ratio as predictors of febrile neutropenia complications: a prospective observational trial.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
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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

4 authors.

Yaohua YuDepartment of Plastic and Burn Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, No. 41 Xibei Road, Haishu District, Ningbo City, 315000 Zhejiang Province, China.
Weiwei WuDepartment of Plastic and Burn Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, No. 41 Xibei Road, Haishu District, Ningbo City, 315000 Zhejiang Province, China.
Yanyan DongNingbo College of Health Sciences, China.
Jiliang LiDepartment of Plastic and Burn Surgery, Hwa Mei Hospital, University of Chinese Academy of Sciences, No. 41 Xibei Road, Haishu District, Ningbo City, 315000 Zhejiang Province, China.ORCID https://orcid.org/0000-0002-0881-002X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis is a leading cause of mortality among severe burns. This study was conducted to investigate the predictive role of C-reactive protein-to-albumin ratio (CAR) for sepsis and prognosis in severe burns.

methodsPatients with severe burn injuries from 2013 to 2017 were enrolled and divided into septic and nonseptic groups based on the presence of sepsis within 30 days postburn. Independent risk factors for sepsis were performed by the univariate and multivariate logistic regression analyses. The association between CAR level at admission and postburn 30-day mortality was designed via the Kaplan-Meier method.

resultsOf all the 196 enrolled patients, 83 patients developed sepsis within 30 days postburn injury, with an incidence of 42.3%. TBSA percentage (OR: 1.65, 95% CI: 1.17-2.32,

conclusionsThe CAR level at admission was an independent risk factor for sepsis and prognosis in severe burns.

Indexed as

AdultBurnsC-Reactive ProteinFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsSepsisSerum AlbuminC-Reactive ProteinSerum Albumin

Identifiers

PMID33833617
PMCPMC8016580

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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.