Harrison AG, Lin T, Wang P. Mechanisms of SARS-CoV-2 transmission and Pathogenesis. Trends Immunol. 2020;41:1100–15.

Article  CAS  PubMed  PubMed Central  Google Scholar 

WHO COVID-19. Dashboard [Internet]. June 01 2023. Geneva: World Health Organization; [cited June 01 2023]. https://covid19.who.int/

Modes ME, et al. Clinical characteristics and outcomes among adults hospitalized with laboratory-confirmed SARS-CoV-2 infection during periods of B.1.617.2 (Delta) and B.1.1.529 (omicron) variant predominance - one hospital, California, July 15-September 23, 2021, and December 21, 2021-January 27, 2022. MMWR Morb Mortal Wkly Rep. 2022;71:217–23.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Rzymski P, Kasianchuk N, Sikora D, Poniedziałek B. COVID-19 vaccinations and rates of infections, hospitalizations, ICU admissions, and deaths in Europe during SARS-CoV-2 Omicron wave in the first quarter of 2022. J Med Virol. 2023;95:e28131.

Article  CAS  PubMed  Google Scholar 

Mhawish H, et al. Comparison of severity of immunized versus non-immunized COVID-19 patients admitted to ICU: a prospective observational study. Annals Med Surg. 2021;71:102951.

Article  Google Scholar 

Moghadas SM, et al. The impact of vaccination on Coronavirus Disease 2019 (COVID-19) outbreaks in the United States. Clin Infect Dis. 2021;73:2257–64.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Covid C, et al. COVID-19 vaccine breakthrough infections reported to CDC—United States, January 1–April 30, 2021. Morb Mortal Wkly Rep. 2021;70:792.

Article  Google Scholar 

Grasselli G et al. Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020.

Kartsonaki C, et al. Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19. Int J Epidemiol. 2023;52:355–76.

Article  PubMed  PubMed Central  Google Scholar 

Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323:1239–42.

Article  CAS  PubMed  Google Scholar 

Hu B, Guo H, Zhou P, Shi Z-L. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol. 2021;19:141–54.

Article  CAS  PubMed  Google Scholar 

Zhou Y, et al. Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: a systematic review and meta-analysis. Int J Infect Dis. 2020;99:47–56.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jain V, Yuan J-M. Predictive symptoms and comorbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis. Int J Public Health. 2020;65:533–46.

Article  PubMed  Google Scholar 

Ahlström B, et al. The Swedish covid-19 intensive care cohort: risk factors of ICU admission and ICU mortality. Acta Anaesthesiol Scand. 2021;65:525–33.

Article  PubMed  PubMed Central  Google Scholar 

Bart GP, et al. Demographic risk factors for COVID-19 infection, severity, ICU admission and death: a meta-analysis of 59 studies. BMJ Open. 2021;11:e044640.

Article  Google Scholar 

Del Valle DM, et al. An inflammatory cytokine signature predicts COVID-19 severity and survival. Nat Med. 2020;26:1636–43.

Article  PubMed  PubMed Central  Google Scholar 

Han H, et al. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg Microbes Infections. 2020;9:1123–30.

Article  CAS  Google Scholar 

Fara A, Mitrev Z, Rosalia RA, Assas BM. Cytokine storm and COVID-19: a chronicle of pro-inflammatory cytokines. Open Biology. 2020;10:200160.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yang L, et al. COVID-19: immunopathogenesis and immunotherapeutics. Signal Transduct Target Therapy. 2020;5:128.

Article  CAS  Google Scholar 

Mahmudpour M, Roozbeh J, Keshavarz M, Farrokhi S, Nabipour I. COVID-19 cytokine storm: the anger of inflammation. Cytokine. 2020;133:155151.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fraser DD, et al. Novel outcome biomarkers identified with targeted proteomic analyses of plasma from critically ill coronavirus Disease 2019 patients. Crit Care Explor. 2020;2:e0189.

Article  PubMed  PubMed Central  Google Scholar 

Fraser DD, et al. Inflammation profiling of critically ill coronavirus Disease 2019 patients. Crit Care Explor. 2020;2:e0144.

Article  PubMed  PubMed Central  Google Scholar 

Fraser DD, et al. Endothelial Injury and Glycocalyx Degradation in critically ill coronavirus Disease 2019 patients: implications for microvascular platelet aggregation. Crit care Explorations. 2020;2:e0194–0194.

Article  Google Scholar 

Gorog DA, et al. Current and novel biomarkers of thrombotic risk in COVID-19: a Consensus Statement from the International COVID-19 thrombosis biomarkers Colloquium. Nat Reviews Cardiol. 2022;19:475–95.

Article  CAS  Google Scholar 

Yao Y, et al. D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: a case control study. J Intensive Care. 2020;8:49.

Article  PubMed  PubMed Central  Google Scholar 

Cabrera-Garcia D, et al. Plasma biomarkers associated with survival and thrombosis in hospitalized COVID-19 patients. Int J Hematol. 2022;116:937–46.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Fraser DD, et al. Detection and profiling of human coronavirus immunoglobulins in critically ill coronavirus Disease 2019 patients. Crit Care Explor. 2021;3:e0369.

Article  PubMed  PubMed Central  Google Scholar 

Fraser DD, et al. Cohort-specific serological recognition of SARS-CoV-2 variant RBD antigens. Ann Clin Lab Sci. 2022;52:651–62.

CAS  PubMed  Google Scholar 

Fraser DD, et al. Critically ill COVID-19 patients exhibit Anti-SARS-CoV-2 serological responses. Pathophysiology. 2021;28:212–23.

Article  PubMed  PubMed Central  Google Scholar 

Iosef C, et al. COVID-19 plasma proteome reveals novel temporal and cell-specific signatures for disease severity and high-precision disease management. J Cell Mol Med. 2023;27:141–57.

Article  CAS  PubMed  Google Scholar 

Singer M, et al. The Third International Consensus definitions for Sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–10.

Article  CAS  PubMed  PubMed Central  Google Scholar 

CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel [Internet]. https://www.fda.gov/media/134922/download

NIH HRPP. POLICY: Guidelines for Limits of Blood Drawn for Research Purposes in the Clinical Center. M95-9 (rev.) June 5. 2009.

Brisson AR, Matsui D, Rieder MJ, Fraser DD. Translational research in pediatrics: tissue sampling and biobanking. Pediatrics. 2012;129:153–62.

Article  PubMed  Google Scholar 

Gillio-Meina C, Cepinskas G, Cecchini EL, Fraser DD. Translational research in pediatrics II: blood collection, processing, shipping, and storage. Pediatrics. 2013;131:754–66.

Article  PubMed  Google Scholar 

Priestap F, Kao R, Martin CM. External validation of a prognostic model for intensive care unit mortality: a retrospective study using the Ontario critical care information system. Can J Anaesth. 2020.

Kursa MB, Rudnicki W R. Feature Selection with the Boruta Package. Journal of Statistical Software. 2010;36(11):1–13.

Tang C, Garreau D, and von Luxburg U. When do random forests fail? In: NeurIPS. 2018;2987–97.

Van der Maaten L, Hinton G. Visualizing data using t-SNE. J Mach Learn Res. 2008;9.

Jambu M. Chap. 10 - classification of individuals–variables data sets. In: Jambu M, editor. Exploratory and Multivariate Data Analysis. Boston: Academic; 1991;305–405.

Chapter  Google Scholar 

Pedregosa F, et al. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12:2825–30.

Google Scholar 

Bateman A, et al. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 2021;49:D480–9.

Article  Google Scholar 

Zhang Y, Zhang Y, Qi P, Manning CD, Langlotz CP. Biomedical and clinical English model packages for the Stanza Python NLP library. J Am Med Inform Assoc. 2021;28:1892–9.

Article  PubMed  PubMed Central  Google Scholar 

Qi P, Zhang Y, Zhang Y, Bolton J, Manning CD. Stanza: A Python natural language processing toolkit for many human languages. arXiv preprint arXiv:2003.07082. 2020.

Honnibal M, Montani I, Van Landeghem S, Boyd A. spaCy: Industrial-strength Natural Language Processing in Python. 2020.

Gupta S, et al. Factors Associated with Death in critically ill patients with Coronavirus Disease 2019 in the US. JAMA Intern Med. 2020;180:1436–47.

Article  CAS  PubMed  Google Scholar 

di Flora DC et al. Analysis of Plasma Proteins Involved in Inflammation, Immune Response/Complement System, and Blood Coagulation upon Admission of COVID-19 Patients to Hospital May Help to Predict the Prognosis of the Disease. Cells. 2023;12.

Völlmy F et al. A serum proteome signature to predict mortality in severe COVID-19 patients. Life Sci Alliance. 2021;4.

Bhatraju PK et al. Covid-19 in critically ill patients in the Seattle Region - Case Series. N Engl J Med. 2020.

Gutmann C, et al. SARS-CoV-2 RNAemia and proteomic trajectories inform prognostication in COVID-19 patients admitted to intensive care. Nat Commun. 2021;12:3406.

Article  CAS  PubMed  PubMed Central