Evidence map›Paper›PMID 33884718›Full record

ArticleInternational journal of clinical practice2021

Combined predictive performance of age and neutrophilic percentage on admission for severe novel coronavirus disease 2019.

Yuhong Chen, Haijun Zhi, Kun Zhang, Guijun Zhu, Lixia Liu, Xixin Yan, Zhigang Cai, Congcong Zhao, Zhenjie Hu

Open access · bronzeAbstract read
In one paragraph

Article in International journal of clinical practice, 2021. 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
0.1field-weighted citation impact, top 52% 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, 2 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

9 authors at 2 institutions in 1 country.

Yuhong ChenDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Haijun ZhiEmergency Department, Cangzhou Central Hospital, Cangzhou, China.
Kun ZhangDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Guijun ZhuDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Lixia LiuDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Xixin YanDepartment of Respiration, Hebei Medical University Second Affiliated Hospital, Shijiazhuang, China.
Zhigang CaiDepartment of Respiration, Hebei Medical University Second Affiliated Hospital, Shijiazhuang, China.
Congcong ZhaoDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Zhenjie HuDepartment of Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.ORCID https://orcid.org/0000-0003-1404-5691
Hebei Medical University · CNCangzhou Central Hospital · CN

Funding

Department of Science and Technology of Hebei Province of China 20277707D
6 · The paper itself

Abstract

backgroundNovel coronavirus disease 2019 (COVID-19) poses a huge threat to the global public health. This study aimed to identify predictive indicators of severe COVID-19.

methodsWe retrospectively collected clinical data on hospital admission of all patients with severe COVID-19 and a control cohort (1:1) of gender- and hospital-matched patients with mild disease from 13 designated hospitals in the Hebei Province between 22 January and 15 April 2020.

resultsA total of 104 patients (52 with severe COVID-19 and 52 with mild disease) were included. Only age, fever, duration from symptom onset to confirmation, respiratory rate, percutaneous oxygen saturation (SpO

conclusionThe combination of age and neutrophil percentage could effectively predict severe COVID-19. The sum of age and neutrophil percentage was recommended for clinical application because of its excellent predictive value and practicability. TRAIL REGISTRATION: China Clinical Trial Registry, number ChiCTR2000030226. Registered 26 February 2020-Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=49855.

Indexed as

COVID-19ChinaHumansNeutrophilsPrognosisRetrospective StudiesSARS-CoV-2

Identifiers

PMID33884718
PMCPMC8250231
OpenAlexW3155213266

What OpenQuestion holds

Textmetadata
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.