Claudia Libertin

Professor of Medicine

Mayo Clinic Research Florida
Country flagUnited States

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Claudia Libertin is a Professor of Medicine at Mayo Clinic Research in Florida, USA. Her research interests include immuno-competence in COVID-19, infectious disease prevalence in transplant recipients, antibiotic resistance, and best practices in serologic screening for solid organ transplant candidates. She has contributed to various studies, aiming to enhance understanding and management of infection-related risks in clinical settings.

Articles (7)

Background: While ‘immuno-competence’ is a well-known term, it lacks an operational definition. To address this omission, this study explored whether the temporal and structured data of the complete blood cell count (CBC) can rapidly estimate immuno-competence. To this end, one or more ratios that included data on all monocytes, lymphocytes and neutrophils were investigated. Materials and methods: Longitudinal CBC data collected from 101 COVID-19 patients (291 observations) were analyzed. Dynamics were estimated with several approaches, which included non-structured (the classic CBC format) and structured data. Structured data were assessed as complex ratios that capture multicellular interactions among leukocytes. In comparing survivors with non-survivors, the hypothesis that immuno-competence may exhibit feedback-like (oscillatory or cyclic) responses was tested. Results: While non-structured data did not distinguish survivors from non-survivors, structured data revealed immunological and statistical differences between outcomes: while survivors exhibited oscillatory data patterns, non-survivors did not. In survivors, many variables (including IL-6, hemoglobin and several complex indicators) showed values above or below the levels observed on day 1 of the hospitalization period, displaying L-shaped data distributions (positive kurtosis). In contrast, non-survivors did not exhibit kurtosis. Three immunologically defined data subsets included only survivors. Because information was based on visual patterns generated in real time, this method can, potentially, provide information rapidly. Discussion: The hypothesis that immuno-competence expresses feedback-like loops when immunological data are structured was not rejected. This function seemed to be impaired in immuno-suppressed individuals. While this method rapidly informs, it is only a guide that, to be confirmed, requires additional tests. Despite this limitation, the fact that three protective (survival-associated) immunological data subsets were observed since day 1 supports many clinical decisions, including the early and personalized prognosis and identification of targets that immunomodulatory therapies could pursue. Because it extracts more information from the same data, structured data may replace the century-old format of the CBC.

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2024

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2022

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2022

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2021

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2021

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2020

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2020

Collaborators (3)

Ariel L. Rivas

University of New Mexico

UNITED STATES
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Mark Anthony Diaz

Assistant Professor

Avera McKennan Hospital and University Health Center

UNITED STATES
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Thomas Caulfield

Professor

Mayo Clinic Research Florida

UNITED STATES
View details
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