ArticleCytokine2023
T-cell lymphocytopenia: An omnipresent predictor of morbidity and mortality in consequence of SARS-CoV disease and influenza A infections.
Article in Cytokine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Machine learning for early screening of influenza A-associated invasive pulmonary aspergillosis in hospitalized patients: a real-world study.Frontiers in cellular and infection microbiology · 2026Article
- Local and systemic host responses to influenza and concurrent or sequential SARS-CoV-2 infection.Frontiers in cellular and infection microbiology · 2026Review
- A glimpse into viral warfare: decoding the intriguing role of highly pathogenic coronavirus proteins in apoptosis regulation.Journal of biomedical science · 2024Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of the researchWe proposed T-cell lymphocytopenia as a strategic predictor of serious coronavirus and influenza infections. Our preeminent goal was to determine whether a degree of T-cell lymphopenia would identify a distinct threshold cell count to differentiate between severe and non-severe infections. We codified an Index Severity Score to exploit an association between T-cell cytopenia and the grade of disease activity. PRINCIPAL
resultA T-cell count of 560 cells/uL or below signified a trend towards advanced disease. KEY FINDINGS AND
conclusions
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.