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Decoding Immuno-Competence: A Novel Analysis of Complete Blood Cell Count Data in COVID-19 Outcomes
Prakasha Kempaiah1, Claudia R Libertin2, Rohit A Chitale3
1Department of Medicine, Division of Infectious Diseases, Mayo Clinic, Jacksonville, FL 32224, USA.
Insights
Structured complete blood cell count (CBC) data can rapidly estimate immuno-competence by analyzing temporal patterns. Survivors showed distinct oscillatory patterns, unlike non-survivors, suggesting a novel approach to immune status assessment.
Area of Science:
- Immunology
- Hematology
- Computational Biology
Background:
- The term 'immuno-competence' lacks a clear operational definition.
- Complete blood cell count (CBC) data, including monocytes, lymphocytes, and neutrophils, were investigated for their potential to estimate immune competence.
- Temporal and structured CBC data offer a novel approach to assessing immune status.
Purpose of the Study:
- To develop an operational definition for immuno-competence using CBC data.
- To explore the utility of structured, temporal CBC data in rapidly estimating immune competence.
- To differentiate between survivors and non-survivors based on CBC data patterns.
Main Methods:
- Longitudinal CBC data from 101 COVID-19 patients were analyzed.
- Structured data, represented as complex leukocyte ratios, were used to capture multicellular interactions.
- Hypothesis testing compared oscillatory patterns in survivors versus non-survivors.
Main Results:
- Structured CBC data, unlike non-structured data, distinguished between survivors and non-survivors.
- Survivors exhibited oscillatory data patterns, while non-survivors did not.
- Three survival-associated immunological data subsets were identified from day 1.
Conclusions:
- The study supports the hypothesis that immuno-competence involves feedback loops, observable in structured immunological data.
- Impaired feedback loops were noted in immuno-suppressed individuals.
- Structured CBC data offer rapid insights for clinical decisions, including prognosis and therapeutic target identification, potentially replacing the traditional CBC format.
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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