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Can we predict the severe course of COVID-19 - a systematic review and meta-analysis of indicators of clinical outcome?
Katzenschlager, Stephan; Zimmer, Alexandra J; Gottschalk, Claudius; Grafeneder, Jürgen; Schmitz, Stephani; Kraker, Sara; Ganslmeier, Marlene; Muth, Amelie; Seitel, Alexander; Maier-Hein, Lena; Benedetti, Andrea; Larmann, Jan; Weigand, Markus A; McGrath, Sean; Denkinger, Claudia M.
  • Katzenschlager S; Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
  • Zimmer AJ; Departments of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
  • Gottschalk C; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
  • Grafeneder J; Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.
  • Schmitz S; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
  • Kraker S; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
  • Ganslmeier M; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
  • Muth A; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
  • Seitel A; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Maier-Hein L; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Benedetti A; Departments of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada.
  • Larmann J; Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
  • Weigand MA; Department of Anesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
  • McGrath S; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America.
  • Denkinger CM; Division of Tropical Medicine, Center for Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany.
PLoS One ; 16(7): e0255154, 2021.
Article in English | MEDLINE | ID: covidwho-1331999
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 31st 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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0255154

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Prognostic study / Randomized controlled trials / Reviews / Systematic review/Meta Analysis Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0255154