Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients: Results from a Cohort Observational Study

• Published in: Journal of clinical medicine Vol. 12; no. 8; p. 3035
• Main Authors: Cidade, José Pedro, de Souza Dantas, Vicente Cés, de Figueiredo Thompson, Alessandra, de Miranda, Renata Carnevale Carneiro Chermont, Mamfrim, Rafaela, Caroli, Henrique, Escudini, Gabriela, Oliveira, Natalia, Castro, Taiza, Póvoa, Pedro
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 21-04-2023; MDPI
• Subjects: Biomarkers; Care and treatment; Clinical medicine; Clinical outcomes; Cluster analysis; Coronaviruses; COVID-19; Critically ill; Data collection; Data processing; Disease; Genotype & phenotype; Hospitals; Infections; Leukocytes; Lymphocytes; Medical research; Medicine, Experimental; Mortality; Observational studies; Patient outcomes; Phenotype; Population; Principal components analysis; Severe acute respiratory syndrome coronavirus 2; Statistical analysis; Statistics; Variables; Brazil; Portugal; United States > US; COVID-19; critical care; phenotypes; cluster analysis; mortality rate
• ISSN: 2077-0383; 2077-0383
• DOI: 10.3390/jcm12083035

: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity.
A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020-2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables.
814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B.
Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients' care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.