Elevated level of circulating calprotectin correlates with severity and high mortality in patients with COVID‐19

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Abstract

Background

Patients with coronavirus disease‐2019 (COVID‐19) are characterized by hyperinflammation. Calprotectin (S100A8/S100A9) is a calcium‐ and zinc‐binding protein mainly secreted by neutrophilic granulocytes or macrophages and has been suggested to be correlated with the severity and prognosis of COVID‐19.

Aim

To thoroughly evaluate the diagnostic and prognostic utility of calprotectin in patients with COVID‐19 by analyzing relevant studies.

Methods

PubMed, Web of Science, and Cochrane Library were comprehensively searched from inception to August 1, 2023 to retrieve studies about the application of calprotectin in COVID‐19. Useful data such as the level of calprotectin in different groups and the diagnostic efficacy of this biomarker for severe COVID‐19 were extracted and aggregated by using Stata 16.0 software.

Results

Fifteen studies were brought into this meta‐analysis. First, the pooled standardized mean differences (SMDs) were used to estimate the differences in the levels of circulating calprotectin between patients with severe and non‐severe COVID‐19. The results showed an overall estimate of 1.84 (95% confidence interval [CI]: 1.09–2.60). Diagnostic information was extracted from 11 studies, and the pooled sensitivity and specificity of calprotectin for diagnosing severe COVID‐19 were 0.75 (95% CI: 0.64–0.84) and 0.88 (95% CI: 0.79–0.94), respectively. The AUC was 0.89 and the pooled DOR was 18.44 (95% CI: 9.07–37.51). Furthermore, there was a strong correlation between elevated levels of circulating calprotectin and a higher risk of mortality outcomes in COVID‐19 patients (odds ratio: 8.60, 95% CI: 2.17–34.12; p < 0.1).

Conclusion

This meta‐analysis showed that calprotectin was elevated in patients with severe COVID‐19, and this atypical inflammatory cytokine might serve as a useful biomarker to distinguish the severity of COVID‐19 and predict the prognosis.

Abstract

This article showed that calprotectin may be a useful biomarker to distinguish the severity and predict the prognosis of COVID‐19.

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Most cited references 62

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

David Moher, Alessandro Liberati, Jennifer Tetzlaff … (2009)

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Is Open Access

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.

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Author and article information

Contributors

Xiqiang Xu: xxqsdjn@126.com

Jun Dong:

ORCID: http://orcid.org/0000-0002-5626-975X

slyydj2019@163.com

Journal

Journal ID (nlm-ta): Immun Inflamm Dis

Journal ID (iso-abbrev): Immun Inflamm Dis

Journal ID (doi): 10.1002/(ISSN)2050-4527

Journal ID (publisher-id): IID3

Title: Immunity, Inflammation and Disease

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Electronic): 2050-4527

Publication date (Electronic): 13 March 2024

Publication date Collection: March 2024

Volume: 12

Issue: 3 ( doiID: 10.1002/iid3.v12.3 )

Electronic Location Identifier: e1212

Affiliations

[ ¹ ] Department of Orthopaedics Shandong Provincial Hospital Affiliated to Shandong First Medical University Jinan Shandong Province China

[ ² ] Graduate School of Education Shandong Sport University Jinan Shandong Province China

Author notes

[*] [* ] Correspondence Jun Dong and Xiqiang Xu, Department of Orthopaedics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324, Rd Jing Wu Wei Qi, Jinan 250021, Shandong, China.

Email: slyydj2019@ 123456163.com and xxqsdjn@ 123456126.com

Author information

Qingyu Zhang https://orcid.org/0000-0002-0497-3630

Jun Dong http://orcid.org/0000-0002-5626-975X

Article

Publisher ID: IID31212

DOI: 10.1002/iid3.1212

PMC ID: 10936233

PubMed ID: 38477671

SO-VID: 2393bd22-a96a-4d91-912b-c4b26e3c33e3

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date revision received : 22 January 2024

Date received : 27 November 2023

Date accepted : 01 March 2024

Page count

Figures: 8, Tables: 1, Pages: 14, Words: 6063

Funding

Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;

Award ID: 82302682

Funded by: Taishan Scholar Project of Shandong Province , doi 10.13039/501100010040;

Award ID: tsqn201909183

Funded by: Natural Science Foundation of Shandong Province , doi 10.13039/501100007129;

Award ID: ZR2020MH098

Award ID: ZR2020QH072

Funded by: Shandong First Medical University , doi 10.13039/501100015507;

Award ID: 2020RC008

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source-schema-version-number 2.0

cover-date March 2024

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.9 mode:remove_FC converted:13.03.2024

Keywords: biomarker,calprotectin,covid‐19,meta‐analysis,systematic review

Data availability:

Keywords: biomarker, calprotectin, covid‐19, meta‐analysis, systematic review

Elevated level of circulating calprotectin correlates with severity and high mortality in patients with COVID‐19

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Novel Coronavirus Disease COVID-19

Most cited references 62

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

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