Evidence map›Paper›PMID 39845955›Full record

Observational studyFrontiers in immunology2024

Investigating the relationship between the immune response and the severity of COVID-19: a large-cohort retrospective study.

Riccardo Giuseppe Margiotta, Emanuela Sozio, Fabio Del Ben, Antonio Paolo Beltrami, Daniela Cesselli, Marco Comar, Alessandra Devito, Martina Fabris, Francesco Curcio, Carlo Tascini and 1 more

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Riccardo Giuseppe Margiotta *Physics Department, International School for Advanced Studies (SISSA), Trieste, Italy.
Emanuela Sozio *Infectious Disease Unit, Azienda Sanitaria Universitaria Friuli Centrale (ASU FC), Udine, Italy.
Fabio Del BenDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Antonio Paolo BeltramiDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Daniela CesselliDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Marco ComarDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Alessandra DevitoDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Martina FabrisDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Francesco CurcioDepartment of Medicine (DMED), University of Udine, Udine, Italy.
Carlo TasciniInfectious Disease Unit, Azienda Sanitaria Universitaria Friuli Centrale (ASU FC), Udine, Italy.
Guido SanguinettiPhysics Department, International School for Advanced Studies (SISSA), Trieste, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has left an indelible mark globally, presenting numerous challenges to public health. This crisis, while disruptive and impactful, has provided a unique opportunity to gather precious clinical data extensively. In this observational, case-control study, we utilized data collected at the Azienda Sanitaria Universitaria Friuli Centrale, Italy, to comprehensively characterize the immuno-inflammatory features in COVID-19 patients. Specifically, we employed multicolor flow cytometry, cytokine assays, and inflammatory biomarkers to elucidate the interplay between the infectious agent and the host's immune status. We characterized immuno-inflammatory profiles within the first 72 hours of hospital admission, stratified by age, disease severity, and time elapsed since symptom onset. Our findings indicate that patients admitted to the hospital shortly after symptom onset exhibit a distinct pattern compared to those who arrive later, characterized by a more active immune response and heightened cytokine activity, but lower markers of tissue damage. We used univariate and multivariate logistic regression models to identify informative markers for outcome severity. Predictors incorporating the immuno-inflammatory features significantly outperformed standard baselines, identifying up to 59% of patients with positive outcomes while maintaining a false omission rate as low as 4%. Overall, our study sheds light on the immuno-inflammatory aspects observed in COVID-19 patients prior to vaccination, providing insights for guiding the clinical management of first-time infections by a novel virus.

Indexed as

COVID-19SARS-CoV-2AdultAgedAged, 80 and overBiomarkersCase-Control StudiesCytokinesFemaleHumansItalyMaleMiddle AgedRetrospective StudiesSeverity of Illness IndexBiomarkersCytokinesCOVID-19cytokinesflow cytometryimmune systemimmunologyinflammationpredictive modeling

Identifiers

PMID39845955
PMCPMC11750771

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.