Evidence map›Paper›PMID 34238962›Full record

ArticleScientific reports2021

Significance of peripheral blood indexes in differential diagnoses of SARS-CoV-2 and New Bunia virus.

Wentao He, Xiaoyi Liu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Development and validation of an efficient nomogram for risk assessment of norovirus infection in pediatric patients.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2022
    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

2 authors at 2 institutions in 1 country.

Wentao HeDepartment of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Jixi Road 218, Shushan District, Hefei, 230022, Anhui, People's Republic of China. 455160056@qq.com.
Xiaoyi LiuDepartment of Clinical Nutrition, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, Anhui, China.
First Affiliated Hospital of Anhui Medical University · CNUniversity of Science and Technology of China · CN

Funding

The National Natural Science Foundation of China 81771685
6 · The paper itself

Abstract

We aimed to provide a laboratory basis for differential diagnosis of COVID-19 and severe fever with thrombocytopenia syndrome (SFTS). Clinical data were collected from 32 COVID-19 patients (2019-nCoV group), 31 SFTS patients (SFTS group) and 30 healthy controls (control group). For each group of hospitalized patients, a retrospective analysis was performed on specific indices, including cytokines, T-lymphocyte subsets, routine blood parameters, C-reactive protein (CRP) and procalcitonin (PCT), and receiver operating characteristic (ROC) curves for the indices revealed the differences among groups. Compared with the 2019-nCoV group, the SFTS group had a significantly and greatly decreased counts of WBC, absolute lymphocyte, PLT and absolute CD4

Indexed as

PhlebovirusSARS-CoV-2Area Under CurveBiomarkersCOVID-19C-Reactive ProteinDiagnosis, DifferentialHumansLymphocyte CountProcalcitoninRetrospective StudiesROC CurveSevere Fever with Thrombocytopenia SyndromeTumor Necrosis Factor-alphaBiomarkersC-Reactive ProteinProcalcitoninTumor Necrosis Factor-alpha

Identifiers

PMID34238962
PMCPMC8266865
OpenAlexW3179054495

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.