Evidence map›Paper›PMID 33843161›Full record

ArticleJournal of Zhejiang University. Science. B

Clinical characteristics and plasma antibody titer of patients with COVID-19 in Zhejiang, China.

Wei-Ling Xiang, Jing-Jing Cheng, Lian-Peng Wu, Bing-Yu Chen, Wen-Xin Li, Dan-Ying Qiu, Wei Zhang, Fei-Hang Ge, Dong Chen, Zhen Wang

Open access · bronzeAbstract read
In one paragraph

Article in Journal of Zhejiang University. Science. B. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 4 institutions in 1 country.

Wei-Ling XiangResearch Center of Blood Transfusion Medicine, Ministry of Education Key Laboratory of Laboratory Medicine, Department of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Jing-Jing ChengResearch Center of Blood Transfusion Medicine, Ministry of Education Key Laboratory of Laboratory Medicine, Department of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Lian-Peng WuDepartment of Laboratory Medicine, Wenzhou Central Hospital and Sixth People's Hospital of Wenzhou, Wenzhou 325000, China.
Bing-Yu ChenResearch Center of Blood Transfusion Medicine, Ministry of Education Key Laboratory of Laboratory Medicine, Department of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Wen-Xin LiResearch on the Application of Big Data-driven Integrated Blood Collection and Supply Auxiliary Diagnosis and Treatment System, Dongyang People's Hospital, Dongyang 322100, China.
Dan-Ying QiuRehabilitation & Sports Medicine Research Institute of Zhejiang Province, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Wei ZhangRehabilitation & Sports Medicine Research Institute of Zhejiang Province, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Fei-Hang GeRehabilitation & Sports Medicine Research Institute of Zhejiang Province, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Dong ChenDepartment of Laboratory Medicine, Wenzhou Central Hospital and Sixth People's Hospital of Wenzhou, Wenzhou 325000, China.
Zhen WangResearch Center of Blood Transfusion Medicine, Ministry of Education Key Laboratory of Laboratory Medicine, Department of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, China.
Blood Center of Zhejiang Province · CNZhejiang Provincial People's Hospital · CNWenzhou Central Hospital · CNWenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first affected humans in China on December 31, 2019 (Shi et al., 2020). Coronaviruses generally cause mild, self-limiting upper respiratory tract infections in humans, such as the common cold, pneumonia, and gastroenteritis (To et al., 2013; Berry et al., 2015; Chan et al., 2015). According to the Report of the World Health Organization (WHO)-China Joint Mission on COVID-19 (WHO, 2020), the case fatality rate of COVID-19 increases with age, while the rate among males is higher than that among females (4.7% and 2.8%, respectively). Since an effective vaccine and specific anti-viral drugs are still under development, passive immunization using the convalescent plasma (CP) of recovered COVID-19 donors may offer a suitable therapeutic strategy for severely ill patients in the meantime. So far, several studies have shown therapeutic efficacy of CP transfusion in treating COVID-19 cases. A pilot study first reported that transfusion of CP with neutralizing antibody titers above 1:640 was well tolerated and could potentially improve clinical outcomes through neutralizing viremia in severe COVID-19 cases (Chen et al., 2020). Immunoglobulin G (IgG) and IgM are the most abundant and important antibodies in protecting the human body from viral attack (Arabi et al., 2015; Marano et al., 2016). Our study aimed to understand the aspects of plasma antibody titer levels in convalescent patients, as well as assessing the clinical characteristics of normal, severely ill, and critically ill patients, and thus provide a basis for guiding CP therapy. We also hoped to find indicators which could serve as a reference in predicting the progression of the disease.

Indexed as

AdultAgedAntibodies, NeutralizingAntibodies, ViralChinaCOVID-19COVID-19 SerotherapyFemaleHumansImmunization, PassiveImmunoglobulin GImmunoglobulin MMaleMiddle AgedAntibodies, NeutralizingAntibodies, ViralImmunoglobulin GImmunoglobulin MCoronavirus disease 2019 (COVID-19); Convalescent plasma; Clinical characteristics; Antibody titer

Identifiers

PMID33843161
PMCPMC7759456
OpenAlexW3114426693

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.