Evidence map›Paper›PMID 35410139›Full record

ArticleBMC infectious diseases2022

Discriminant models for the prediction of postponed viral shedding time and disease progression in COVID-19.

Wen-Yang Li, Daqing Wang, Yuhao Guo, Hong Huang, Hongwen Zhao, Jian Kang, Wei Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 4 institutions in 1 country.

Wen-Yang LiRespiratory and Critical Care Department, The First Hospital of China Medical University, Shenyang, China.
Daqing WangDepartment of Respiratory Disease, Liaoning Province Peoples' Hospital, Shenyang, China.
Yuhao GuoDepartment of Mathematics and Statistics, Xian Jiaotong University, Xian, 710049, China.
Hong HuangRespiratory and Critical Care Department, The First Hospital of China Medical University, Shenyang, China.
Hongwen ZhaoRespiratory and Critical Care Department, The First Hospital of China Medical University, Shenyang, China.
Jian KangRespiratory and Critical Care Department, The First Hospital of China Medical University, Shenyang, China.
Wei WangRespiratory and Critical Care Department, The First Hospital of China Medical University, Shenyang, China. wwbycmu@126.com.
China Medical University · CNFirst Hospital of China Medical University · CNLiaoning Provincial People's Hospital · CNXi'an Jiaotong University · CN

Funding

Department of Science and Technology of Liaoning Province (CN) NO. 2020JH2/10300003.
6 · The paper itself

Abstract

backgroundCOVID-19 infection can cause life-threatening respiratory disease. This study aimed to fully characterize the clinical features associated with postponed viral shedding time and disease progression, then develop and validate two prognostic discriminant models.

methodsThis study included 125 hospitalized patients with COVID-19, for whom 44 parameters were recorded, including age, gender, underlying comorbidities, epidemiological features, laboratory indexes, imaging characteristics and therapeutic regimen, et al. Fisher's exact test and Mann-Whitney test were used for feature selection. All models were developed with fourfold cross-validation, and the final performances of each model were compared by the Area Under Receiving Operating Curve (AUROC). After optimizing the parameters via L

resultsSixty-nine patients had a postponed viral shedding time (> 14 days), and 28 of 125 patients progressed into severe cases. Six and eleven demographic, clinical features and therapeutic regimen were significantly associated with postponed viral shedding time and disease progressing, respectively (p < 0.05). The optimal discriminant models are: y

conclusionThe two discriminant models could effectively predict the postponed viral shedding time and disease severity and could be used as early-warning tools for COVID-19.

Indexed as

COVID-19Disease ProgressionHumansInfantPrognosisRetrospective StudiesSARS-CoV-2Virus SheddingCOVID-19Disease progressionPostponed viral shedding timePrognostic discriminant model

Identifiers

PMID35410139
PMCPMC8996205
OpenAlexW4223550158

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.