Tags

Type your tag names separated by a space and hit enter

Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis.
Eur J Clin Invest. 2020 Oct; 50(10):e13362.EJ

Abstract

BACKGROUND

Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management.

METHODS

A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates.

RESULTS

We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality.

CONCLUSIONS

Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality.

Authors+Show Affiliations

School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK. Department of Cardiovascular Medicine, Humanitas Clinical and Research Center - IRCCS, Milan, Italy. Department of Radiology, Humanitas Clinical and Research Center - IRCCS, Milan, Italy.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.Department of Cardiology-Intensive Therapy, Poznan University of Medical Sciences, Poznan, Poland.Department of Multimodality Cardiovascular Imaging, IRCCS Policlinico San Donato, San Donato Milanese, Italy.Institute for Liver and Digestive Health, Royal Free Hospital & UCL, University College London, London, UK.Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. Cardiology Division, University Hospital of Pisa, Pisa, Italy.Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padua Medical School, Padova, Italy.School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK. Department of Clinical Therapeutics, National and Kapodistrian University of Athens School of Medicine, Athen, Greece.

Pub Type(s)

Journal Article
Meta-Analysis
Systematic Review

Language

eng

PubMed ID

32726868

Citation

Figliozzi, Stefano, et al. "Predictors of Adverse Prognosis in COVID-19: a Systematic Review and Meta-analysis." European Journal of Clinical Investigation, vol. 50, no. 10, 2020, pp. e13362.
Figliozzi S, Masci PG, Ahmadi N, et al. Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis. Eur J Clin Invest. 2020;50(10):e13362.
Figliozzi, S., Masci, P. G., Ahmadi, N., Tondi, L., Koutli, E., Aimo, A., Stamatelopoulos, K., Dimopoulos, M. A., Caforio, A. L. P., & Georgiopoulos, G. (2020). Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis. European Journal of Clinical Investigation, 50(10), e13362. https://doi.org/10.1111/eci.13362
Figliozzi S, et al. Predictors of Adverse Prognosis in COVID-19: a Systematic Review and Meta-analysis. Eur J Clin Invest. 2020;50(10):e13362. PubMed PMID: 32726868.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Predictors of adverse prognosis in COVID-19: A systematic review and meta-analysis. AU - Figliozzi,Stefano, AU - Masci,Pier Giorgio, AU - Ahmadi,Navid, AU - Tondi,Lara, AU - Koutli,Evangelia, AU - Aimo,Alberto, AU - Stamatelopoulos,Kimon, AU - Dimopoulos,Meletios-Athanasios, AU - Caforio,Alida L P, AU - Georgiopoulos,Georgios, Y1 - 2020/08/27/ PY - 2020/05/31/received PY - 2020/07/10/revised PY - 2020/07/20/accepted PY - 2020/7/30/pubmed PY - 2020/10/3/medline PY - 2020/7/30/entrez KW - COVID-19 KW - meta-analysis KW - outcomes KW - predictors SP - e13362 EP - e13362 JF - European journal of clinical investigation JO - Eur J Clin Invest VL - 50 IS - 10 N2 - BACKGROUND: Identification of reliable outcome predictors in coronavirus disease 2019 (COVID-19) is of paramount importance for improving patient's management. METHODS: A systematic review of literature was conducted until 24 April 2020. From 6843 articles, 49 studies were selected for a pooled assessment; cumulative statistics for age and sex were retrieved in 587 790 and 602 234 cases. Two endpoints were defined: (a) a composite outcome including death, severe presentation, hospitalization in the intensive care unit (ICU) and/or mechanical ventilation; and (b) in-hospital mortality. We extracted numeric data on patients' characteristics and cases with adverse outcomes and employed inverse variance random-effects models to derive pooled estimates. RESULTS: We identified 18 and 12 factors associated with the composite endpoint and death, respectively. Among those, a history of CVD (odds ratio (OR) = 3.15, 95% confidence intervals (CIs) 2.26-4.41), acute cardiac (OR = 10.58, 5.00-22.40) or kidney (OR = 5.13, 1.78-14.83) injury, increased procalcitonin (OR = 4.8, 2.034-11.31) or D-dimer (OR = 3.7, 1.74-7.89), and thrombocytopenia (OR = 6.23, 1.031-37.67) conveyed the highest odds for the adverse composite endpoint. Advanced age, male sex, cardiovascular comorbidities, acute cardiac or kidney injury, lymphocytopenia and D-dimer conferred an increased risk of in-hospital death. With respect to the treatment of the acute phase, therapy with steroids was associated with the adverse composite endpoint (OR = 3.61, 95% CI 1.934-6.73), but not with mortality. CONCLUSIONS: Advanced age, comorbidities, abnormal inflammatory and organ injury circulating biomarkers captured patients with an adverse clinical outcome. Clinical history and laboratory profile may then help identify patients with a higher risk of in-hospital mortality. SN - 1365-2362 UR - https://www.unboundmedicine.com/medline/citation/32726868/Predictors_of_adverse_prognosis_in_COVID_19:_A_systematic_review_and_meta_analysis_ L2 - https://doi.org/10.1111/eci.13362 DB - PRIME DP - Unbound Medicine ER -