Evidence map›Paper›PMID 37122321›Full record

ArticleFrontiers in medicine2023

Construction and validation of a deterioration model for elderly COVID-19 Sub-variant BA.2 patients.

Yinyan Wu, Benjie Xiao, Jingjing Xiao, Yudi Han, Huazheng Liang, Zhangwei Yang, Yong Bi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. 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

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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, 0 citations in OpenAlex.

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

7 authors at 3 institutions in 1 country.

Yinyan WuDepartment of Neurology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
Benjie XiaoDepartment of Neurology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
Jingjing XiaoDepartment of Neurology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
Yudi HanDepartment of Neurology, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine, Shanghai, China.
Huazheng LiangShanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Shanghai, China.
Zhangwei YangMedical Department, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Yong BiAffiliated Zhoupu Hospital, Shanghai University of Medicine and Health Siences, Shanghai, China.
Tongji University · CNShanghai University of Medicine and Health Sciences · CNSuzhou Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale: COVID-19 pandemic has imposed tremendous stress and burden on the economy and society worldwide. There is an urgent demand to find a new model to estimate the deterioration of patients inflicted by Omicron variants. Objective: This study aims to develop a model to predict the deterioration of elderly patients inflicted by Omicron Sub-variant BA.2. Methods: COVID-19 patients were randomly divided into the training and the validation cohorts. Both Lasso and Logistic regression analyses were performed to identify prediction factors, which were then selected to build a deterioration model in the training cohort. This model was validated in the validation cohort. Measurements and main results: The deterioration model of COVID-19 was constructed with five indices, including C-reactive protein, neutrophil count/lymphocyte count (NLR), albumin/globulin ratio (A/G), international normalized ratio (INR), and blood urea nitrogen (BUN). The area under the ROC curve (AUC) showed that this model displayed a high accuracy in predicting deterioration, which was 0.85 in the training cohort and 0.85 in the validation cohort. The nomogram provided an easy way to calculate the possibility of deterioration, and the decision curve analysis (DCA) and clinical impact curve analysis (CICA)showed good clinical net profit using this model. Conclusion: The model we constructed can identify and predict the risk of deterioration (requirement for ventilatory support or death) in elderly patients and it is clinically practical, which will facilitate medical decision making and allocating medical resources to those with critical conditions.

Indexed as

coronavirusCOVID-19deterioration modelpredictionprognosis

Identifiers

PMID37122321
PMCPMC10133498
OpenAlexW4365455499

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.