Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?

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Abstract

Background

COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.

Methods

This systematic review was registered at PROSPERO under CRD42020177154. We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31 ^st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.

Results

Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10 mg/L, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49 U/L, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88 pg/mL, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 to 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).

Discussion

This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors that predict severe COVID-19 outcomes and will inform clinical scores to support early decision-making.

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Most cited references 113

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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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Clinical Characteristics of Coronavirus Disease 2019 in China

Wei-jie Guan, Zheng-yi Ni, Yu Hu … (2020)

Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)

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Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Fei Zhou, Ting Yu, Ronghui Du … (2020)

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

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Author and article information

Contributors

Stephan Katzenschlager:

ORCID: https://orcid.org/0000-0003-4977-7999

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Alexandra J. Zimmer:

ORCID: https://orcid.org/0000-0002-6047-0923

Role: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Claudius Gottschalk: Role: ConceptualizationRole: Data curationRole: MethodologyRole: Writing – review & editing

Jürgen Grafeneder:

ORCID: https://orcid.org/0000-0002-3639-0106

Role: ConceptualizationRole: Data curationRole: MethodologyRole: Writing – review & editing

Stephani Schmitz:

ORCID: https://orcid.org/0000-0003-1188-2750

Role: Data curationRole: Formal analysis

Sara Kraker: Role: Data curationRole: Formal analysis

Marlene Ganslmeier: Role: Data curationRole: Formal analysis

Amelie Muth: Role: Data curationRole: Formal analysis

Alexander Seitel: Role: ConceptualizationRole: Data curationRole: MethodologyRole: Writing – review & editing

Lena Maier-Hein:

ORCID: https://orcid.org/0000-0003-4910-9368

Role: Data curationRole: MethodologyRole: SoftwareRole: Writing – review & editing

Andrea Benedetti: Role: ConceptualizationRole: MethodologyRole: Writing – review & editing

Jan Larmann:

ORCID: https://orcid.org/0000-0003-3365-4572

Role: Writing – review & editing

Markus A. Weigand: Role: Writing – review & editing

Sean McGrath:

ORCID: https://orcid.org/0000-0002-7281-3516

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – original draftRole: Writing – review & editing

Claudia M. Denkinger:

ORCID: https://orcid.org/0000-0002-7216-7067

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Chiara Lazzeri: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS One

Journal ID (publisher-id): plos

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 29 July 2021

Publication date Collection: 2021

Publication date PMC-release: 29 July 2021

Volume: 16

Issue: 7

Electronic Location Identifier: e0255154

Affiliations

[1 ] Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany

[2 ] Departments of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada

[3 ] Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany

[4 ] Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria

[5 ] Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany

[6 ] Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America

[7 ] German Center for Infection Research (DZIF), partner site Heidelberg, Heidelberg, Germany

Azienda Ospedaliero Universitaria Careggi, ITALY

Author notes

Competing Interests: I have read the journal’s policy and none of the authors of this manuscript have a competing interest.

‡ These authors also contributed equally to this work.

* E-mail: Claudia.Denkinger@ 123456uni-heidelberg.de

Author information

Stephan Katzenschlager https://orcid.org/0000-0003-4977-7999

Alexandra J. Zimmer https://orcid.org/0000-0002-6047-0923

Jürgen Grafeneder https://orcid.org/0000-0002-3639-0106

Stephani Schmitz https://orcid.org/0000-0003-1188-2750

Lena Maier-Hein https://orcid.org/0000-0003-4910-9368

Jan Larmann https://orcid.org/0000-0003-3365-4572

Sean McGrath https://orcid.org/0000-0002-7281-3516

Claudia M. Denkinger https://orcid.org/0000-0002-7216-7067

Article

Publisher ID: PONE-D-20-41054

DOI: 10.1371/journal.pone.0255154

PMC ID: 8321230

PubMed ID: 34324560

SO-VID: bb9b6eb7-842b-420e-beba-32cea2be86a9

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 1 January 2021

Date accepted : 10 July 2021

Page count

Figures: 5, Tables: 2, Pages: 19

Funding

Funded by: national science foundation graduate research fellowship program

Award ID: DGE1745303

Funded by: national library of medicine of the national institutes of health

Award ID: T32LM012411

Funded by: fonds de recherche du québec-nature et technologies b1x research scholarship

Funded by: heidelberg university hospital

Award Recipient :

ORCID: https://orcid.org/0000-0002-7216-7067

Claudia M. Denkinger

SM acknowledges support from the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE1745303, National Library Of Medicine of the National Institutes of Health under Award Number T32LM012411, and Fonds de recherche du Québec-Nature et technologies B1X research scholarship. CMD acknowledges the support of the Heidelberg University Hospital. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.

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Data Availability All relevant data are uploaded to Zenodo and publicly accessible via the following URL: https://zenodo.org/record/5102836#.YPH8vehKg2x.

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Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?

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Abstract

Background

Methods

Results

Discussion

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Novel Coronavirus Disease COVID-19

Most cited references 113

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

Clinical Characteristics of Coronavirus Disease 2019 in China

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

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