Advancing insights in critical COVID-19: unraveling lymphopenia through propensity score matching - Findings from the Multicenter LYMPH-COVID Study.

OBJECTIVE: To elucidate the impact of lymphopenia on critical COVID-19 patient outcomes. METHODS: We conducted a multicenter prospective cohort study across five hospitals in Portugal and Brazil from 2020 to 2021. The study included adult patients admitted to the intensive care unit with SARS-CoV-2 pneumonia. Patients were categorized into two groups based on their lymphocyte counts within 48 hours of intensive care unit admission: the Lymphopenia Group (lymphocyte serum count < 1 × 109/L) and the Nonlymphopenia Group. Multivariate logistic regression, propensity score matching, Kaplan‒Meier survival curve analysis and Cox proportional hazards regression analysis were used. RESULTS: A total of 912 patients were enrolled, with 191 (20.9%) in the Nonlymphopenia Group and 721 (79.1%) in the Lymphopenia Group. Lymphopenia patients displayed significantly elevated disease severity indices, including Sequential Organ Failure Assessment and Simplified Acute Physiology Score 3 scores, at intensive care unit admission (p = 0.001 and p < 0.001, respectively). Additionally, they presented heightened requirements for vasopressor support (p = 0.045) and prolonged intensive care unit and in-hospital stays (both p < 0.001). Multivariate logistic regression analysis after propensity score matching revealed a significant contribution of lymphopenia to mortality, with an odds ratio of 1,621 (95%CI: 1,275 - 2,048; p < 0.001). Interaction models revealed an increase of 8% in mortality for each decade of longevity in patients with concomitant lymphopenia. In the subanalysis utilizing three-group stratification, the Severe Lymphopenia Group had the highest mortality rate, not only in direct comparisons but also in Kaplan‒Meier survival analysis (log-rank test p = 0.0048). CONCLUSION: Lymphopenia in COVID-19 patients is associated with increased disease severity and an increased risk of mortality, underscoring the need for prompt support for critically ill high-risk patients. These findings offer important insights into improving patient care strategies for COVID-19 patients.

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

Purpose: 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. Methods: 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. Results: 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. Conclusions: 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.