Evidence map›Paper›PMID 32511971›Full record

SynthesisClinica chimica acta; international journal of clinical chemistry2020

Comparative analysis of laboratory indexes of severe and non-severe patients infected with COVID-19.

Jinfeng Bao, Chenxi Li, Kai Zhang, Haiquan Kang, Wensen Chen, Bing Gu

Abstract readComparative StudyMeta-Analysis
In one paragraph

Synthesis in Clinica chimica acta; international journal of clinical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 5 pooled it
–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

68 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  11. Genetic correlations, shared risk genes and immunity landscapes between COVID-19 and venous thromboembolism: evidence from GWAS and bulk transcriptome data.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2024
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  19. Assessing Biomarkers in Viral Infection.Advances in experimental medicine and biology · 2023
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8 more citing papers are in PubMed but not listed here.

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

6 authors.

Jinfeng BaoMedical Technology School of Xuzhou Medical University, Xuzhou Key Laboratory of Laboratory Diagnostics, Xuzhou, Jiangsu 221004, China.
Chenxi LiMedical Technology School of Xuzhou Medical University, Xuzhou Key Laboratory of Laboratory Diagnostics, Xuzhou, Jiangsu 221004, China.
Kai ZhangPancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China.
Haiquan KangDepartment of Laboratory Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221006, China.
Wensen ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiao tong University Health Science Center, Xi'an, Shaanxi 710061, China; Department of Infection Management, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China. Electronic address: wensenchen@njmu.edu.cn.
Bing GuMedical Technology School of Xuzhou Medical University, Xuzhou Key Laboratory of Laboratory Diagnostics, Xuzhou, Jiangsu 221004, China; Department of Laboratory Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221006, China. Electronic address: binggu2015@xzhmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe pandemic coronavirus disease 2019 (COVID-19) has threaten the global health. The characteristics of laboratory findings of coronavirus are of great significance for clinical diagnosis and treatment. We found indicators that may most effectively predict a non-severe COVID-19 patient develop into a severe patient.

methodsWe conducted a meta-analysis to compare the laboratory findings of severe patients with non-severe patients with COVID-19 from searched articles.

resultsThrough the analysis of laboratory examination information of patients with COVID-19 from 35 articles (5912 patients), we demonstrated that severe cases possessed higher levels of leukocyte (1.20-fold), neutrophil (1.33-fold), CRP (3.04-fold), PCT (2.00-fold), ESR (1.44-fold), AST (1.40-fold), ALT (1.34-fold), LDH (1.54-fold), CK (1.44-fold), CK-MB (1.39-fold), total bilirubin (1.14-fold), urea (1.28-fold), creatine (1.09-fold), PT (1.03-fold) and D-dimer (2.74-fold), as well as lower levels of lymphocytes (1.44-fold), eosinophil (2.00-fold), monocyte (1.08-fold), Hemoglobin (1.53-fold), PLT (1.15-fold), albumin (1.15-fold), and APTT (1.02-fold). Lymphocyte subsets and series of inflammatory cytokines were also different in severe cases with the non-severe ones, including lower levels of CD4 T cells (2.10-fold) and CD8 T cells (2.00-fold), higher levels of IL-1β (1.02-fold), IL-6 (1.93-fold) and IL-10 (1.55-fold).

conclusionsSome certain laboratory inspections could predict the progress of the COVID-19 changes, especially lymphocytes, CRP, PCT, ALT, AST, LDH, D-dimer, CD4 T cells and IL6, which provide valuable signals for preventing the deterioration of the disease.

Indexed as

BetacoronavirusSeverity of Illness IndexClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19HumansPandemicsPneumonia, ViralSARS-CoV-2COVID-19Laboratory findingsMeta-analysisPrognosis

Identifiers

PMID32511971
PMCPMC7274996

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.