Evidence map›Paper›PMID 40611144›Full record

Observational studyVirology journal2025

A novel nomogram for the early identification of coinfections in elderly patients with coronavirus disease 2019.

Ju Zou, Xiaoxu Wang, Jie Li, Min Liu, Xiaoting Zhao, Ling Wang, Xuyuan Kuang, Yan Huang, Jun Quan, Ruochan Chen

Abstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Virology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

10 authors.

Ju ZouHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Xiaoxu WangHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Jie LiHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Min LiuHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Xiaoting ZhaoDepartment of Infectious Disease, The First Affiliated Hospital of Xinxiang Medical University, Weihui, Henan, China.
Ling WangDepartment of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Xuyuan KuangDepartment of Hyperbaric Oxygen, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yan HuangHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Jun QuanHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. quanjun@csu.edu.cn.
Ruochan ChenHunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. 405031@csu.edu.cn.

Funding

the National Natural Sciences Foundation of China 82070613 and 82370638the Natural Science Foundation of Hunan Province China 2021JJ70146the Science and Technology Innovation Program of Hunan Province 2022RC1212
6 · The paper itself

Abstract

objectivesThis study aimed to establish a novel and practical nomogram for use upon hospital admission to identify coinfections among elderly patients with coronavirus disease 2019 (COVID-19) to provide timely intervention, limit antimicrobial agent overuse, and finally reduce unfavourable outcomes.

methodsThis prospective cohort study included COVID-19 patients consecutively admitted at multicenter medical facilities in a two-stage process. The nomogram was built on the multivariable logistic regression analysis. The performance of the nomogram was assessed for discrimination and calibration using receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA) in rigorous internal and external validation settings. Two different cutoff values were determined to stratify coinfection risk in elderly patients with COVID-19.

resultsThe coinfection rates in elderly patients determined to be and 26.61%. The nomogram was developed with the parameters of diabetes comorbidity, previous invasive procedure, and procalcitonin (PCT) level, which together showed areas under the curve of 0.86, 0.82, and 0.83 in the training, internal validation, and external validation cohorts, respectively. The nomogram outperformed both PCT or C-reactive protein level alone in detecting coinfections in elderly patients with COVID-19; in addition, we found the nomogram was specific for the elderly compared to non-elderly group. To facilitate clinical decision-making among elderly patients with COVID-19, we defined two cutoff values of prediction probability: a low cutoff of 6.65% to rule out coinfections and a high cutoff of 27.79% to confidently confirm coinfections.

conclusionsThis novel nomogram will assist in the early identification of coinfections in elderly patients with COVID-19.

Indexed as

CoinfectionCOVID-19NomogramsAgedAged, 80 and overComorbidityC-Reactive ProteinFemaleHumansMaleMiddle AgedProcalcitoninProspective StudiesROC CurveSARS-CoV-2C-Reactive ProteinProcalcitoninCoinfectionsCOVID-19Early identificationElderlyNomogram

Identifiers

PMID40611144
PMCPMC12231678

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LicenceCC BY-NC-ND
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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.