Evidence map›Paper›PMID 38270315›Full record

ArticleImmunity, inflammation and disease2024

Effect of serum inflammatory factors in predicting co-infection with influenza viruses and Omicron.

Chengli Zhang, Wei Wang, Xianglin Luo, Minggang Yin, Xiaolong Guo

Open access · goldAbstract read
In one paragraph

Article in Immunity, inflammation and disease, 2024. 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
–field-weighted citation impact, top 99% 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, 0 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 1 country.

Chengli ZhangZigong First People's Hospital, Zigong Academy of Medical Sciences, Zigong, China.ORCID 0000-0002-6478-5017
Wei WangInformation Department, Zigong First People's Hospital, Zigong, China.
Xianglin LuoInformation Department, Zigong First People's Hospital, Zigong, China.
Minggang YinZigong First People's Hospital, Zigong Academy of Medical Sciences, Zigong, China.
Xiaolong GuoZigong First People's Hospital, Zigong Academy of Medical Sciences, Zigong, China.ORCID 0000-0002-2793-4204
Zigong First People's Hospital · CNArmy Medical University · CN

Funding

Health Commission of Sichuan Province Scientific Research Project 20PJ272Health Commission of Zigong City Scientific Research Project 20zd009Project of Zigong Academy of Medical Sciences and Technology Projects of Science and Technology Bureau of Zigong 2020YXY06Project of Zigong Academy of Medical Sciences and Technology Projects of Science and Technology Bureau of Zigong 2021ZCYKY04Technology Projects of Science and Technology Bureau of Zigong 2023YLWS12Zigong Academy of Medical Sciences Own Funds Research Projec ZGYKY22KF006
6 · The paper itself

Abstract

objectivesTo identify the key differences in laboratory indicators between mono-infection and co-infection by influenza viruses and Omicron to facilitate timely adjustments in patient treatment strategies.

methodsPrealbumin and C-reactive protein (CRP) levels were analyzed in 161 COVID-19 cases infected by SARS-CoV-2 (wild type), 299 cases infected by Omicron, 95 cases infected by influenza virus A/B (Flu A/B) and 133 co-infection cases infected with Flu A/B and Omicron. The receiver operating characteristic (ROC) curve and logistic regression equation were used to analyze the clinical predictive capacity of prealbumin and CRP in coinfected patients.

resultsThe co-infected and wild-type infected patients had significantly different CRP and prealbumin levels compared to mono-infected patients with Omicron or Flu A/B (p < .001). The ROC curve results indicated that prealbumin was more efficient than CRP in identifying co-infection from Omicron (AUC: 0.867 vs. 0.724) or Flu A/B (AUC: 0.797 vs. 0.730), and joint prediction significantly improved the diagnostic ability to discriminate co-infection from mono-infection (AUC: 0.934 and 0.887).

conclusionThe findings suggest that prealbumin is a valuable indicator that can warn of co-infection and guide timely treatment decisions. Joint prediction may offer an even more effective diagnostic tool for discriminating co-infection from mono-infection.

Indexed as

CoinfectionCOVID-19OrthomyxoviridaeHumansInflammationPrealbuminPrealbuminC-reactive proteininfluenza virusesOmicronprealbuminpredicting co-infection

Identifiers

PMID38270315
PMCPMC10802130
OpenAlexW4391102212

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.