Evidence map›Paper›PMID 35114938›Full record

Trial reportBMC microbiology2022

Development and multi-center clinical trials of an up-converting phosphor technology-based point-of-care (UPT-POCT) assay for rapid COVID-19 diagnosis and prediction of protective effects.

Pingping Zhang, Baisheng Li, Yao Wang, Wei Min, Xiaohui Wang, Yugui Zhou, Zhencui Li, Yong Zhao, Huan Zhang, Min Jiang and 12 more

Abstract readClinical TrialMulticenter Study
In one paragraph

Trial report in BMC microbiology, 2022. 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
–field-weighted citation impact
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.

  1. Review
  2. Review
  3. Article
  4. Review
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

22 authors.

Pingping Zhang *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, People's Republic of China.
Baisheng Li *Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China.
Yao Wang *Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100032, People's Republic of China.
Wei Min *Beijing Key Laboratory of POCT for Bioemergency and Clinic (No. BZ0329), Beijing, 100071, People's Republic of China.
Xiaohui Wang *Shenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Yugui Zhou *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, People's Republic of China.
Zhencui LiGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China.
Yong ZhaoState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, People's Republic of China.
Huan ZhangGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China.
Min JiangShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Huanying ZhengGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China.
Chao YangShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Wei ZhangGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China.
Le ZuoShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Qi GaoBeijing Key Laboratory of POCT for Bioemergency and Clinic (No. BZ0329), Beijing, 100071, People's Republic of China.
Zhengrong YangShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Yanzhao LiBeijing Key Laboratory of POCT for Bioemergency and Clinic (No. BZ0329), Beijing, 100071, People's Republic of China.
Tiejian FengShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China.
Changqing LinBeijing Key Laboratory of POCT for Bioemergency and Clinic (No. BZ0329), Beijing, 100071, People's Republic of China. changqing.lin@hotgen.com.cn.
Qinghua HuShenzhen Center for Disease Control and Prevention, Shenzhen, People's Republic of China. huqinghua@szcdc.net.
Tie SongGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, People's Republic of China. sjkzx_songtie@gd.gov.cn.
Ruifu YangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, People's Republic of China. ruifuyang@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuantitative point-of-care testing assay for detecting antibodies is critical to COVID-19 control. In this study, we established an up-conversion phosphor technology-based point-of-care testing (UPT-POCT), a lateral flow assay, for rapid COVID-19 diagnosis, as well as prediction of seral neutralizing antibody (NAb) activity and protective effects.

methodsUPT-POCT was developed targeting total antibodies against the receptor-binding domain (RBD) of SARS-CoV-2 spike protein. Using ELISA as a contrast method, we evaluated the quantitation accuracy with NAb and serum samples. Cutoff for serum samples was determined through 70 healthy and 140 COVID-19 patients. We evaluated the cross-reactions with antibodies against other viruses. Then, we performed multi-center clinical trials of UPT-POCT, including 782 patients with 387 clinically confirmed COVID-19 cases. Furthermore, RBD-specific antibody levels were detected using UPT-POCT and microneutralization assay for samples from both patients and vaccinees. Specifically, the antibodies of recovered patients with recurrent positive (RP) reverse transcriptase-polymerase chain reaction test results were discussed.

resultsThe ratios of signal intensities between the test and control bands on the lateral flow strip, namely, T/C ratios, was defined as the results of UPT-POCT. T/C ratios had excellent correlations with concentrations of NAb, as well as OD values of ELISA for serum samples. The sensitivity and specificity of UPT-POCT were 89.15% and 99.75% for 782 cases in seven hospitals in China, respectively. We evaluated RBD-specific antibodies for 528 seral samples from 213 recovered and 99 RP COVID-19 patients, along with 35 seral samples from inactivated SARS-CoV-2 vaccinees, and we discovered that the total RBD-specific antibody level indicated by T/C ratios of UPT-POCT was significantly related to the NAb titers in both COVID-19 patients (r = 0.9404, n = 527; ρ = 0.6836, n = 528) and the vaccinees (r = 0.9063, ρ = 0.7642, n = 35), and it was highly relevant to the protection rate against RP (r = 0.9886, n = 312).

conclusionThis study reveals that the UPT-POCT for quantitative detection of total RBD-specific antibody could be employed as a surrogate method for rapid COVID-19 diagnosis and prediction of protective effects.

Indexed as

Point-of-Care TestingAntibodies, NeutralizingAntibodies, ViralChinaCOVID-19COVID-19 Serological TestingCross ReactionsHumansImmunoassayLimit of DetectionSARS-CoV-2Sensitivity and SpecificitySpike Glycoprotein, CoronavirusVaccinationAntibodies, NeutralizingAntibodies, ViralSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Clinical trialCOVID-19Neutralizing activityProtective effectsRBD-specific total antibodiesUp-conversion phosphor technology

Identifiers

PMID35114938
PMCPMC8811342

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LicenceCC BY
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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.