AI Article Synopsis

  • The study aimed to assess how baseline lymphocyte counts can predict the severity and outcomes of COVID-19 patients, focusing on those hospitalized with SARS-CoV-2.
  • It included 160 patients and found that lower counts of various T-lymphocyte subsets were associated with increased mortality and severe disease cases compared to survivors.
  • Key T-lymphocyte thresholds were identified as independent predictors of in-hospital mortality and disease severity, highlighting the potential of lymphocyte counts as a tool for early risk assessment in COVID-19 patients.

Article Abstract

The aim of this study was to evaluate the role of baseline lymphocyte subset counts in predicting the outcome and severity of COVID-19 patients. Hospitalized patients confirmed to be infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were included and classified according to in-hospital mortality (survivors/nonsurvivors) and the maximal oxygen support/ventilation supply required (nonsevere/severe). Demographics, clinical and laboratory data, and peripheral blood lymphocyte subsets were retrospectively analyzed. Overall, 160 patients were retrospectively included in the study. T-lymphocyte subset (total CD3+, CD3+ CD4+, CD3+ CD8+, CD3+ CD4+ CD8+ double positive [DP] and CD3+ CD4- CD8- double negative [DN]) absolute counts were decreased in nonsurvivors and in patients with severe disease compared to survivors and nonsevere patients (p < 0.001). Multivariable logistic regression analysis showed that absolute counts of CD3+ T-lymphocytes < 524 cells/µl, CD3+ CD4+ < 369 cells/µl, and the number of T-lymphocyte subsets below the cutoff (T-lymphocyte subset index [TLSI]) were independent predictors of in-hospital mortality. Baseline T-lymphocyte subset counts and TLSI were also predictive of disease severity (CD3+  < 733 cells/µl; CD3+ CD4+ < 426 cells/µl; CD3+ CD8+ < 262 cells/µl; CD3+ DP < 4.5 cells/µl; CD3+ DN < 18.5 cells/µl). The evaluation of peripheral T-lymphocyte absolute counts in the early stages of COVID-19 might represent a useful tool for identifying patients at increased risk of unfavorable outcomes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211786PMC
http://dx.doi.org/10.1038/s41598-021-90983-0DOI Listing

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