Evidence map›Paper›PMID 35371011›Full record

ArticleFrontiers in immunology2022

Definition of the Immune Parameters Related to COVID-19 Severity.

Sarah Birindelli, Maciej S Tarkowski, Marcello Gallucci, Marco Schiuma, Alice Covizzi, Przemysław Lewkowicz, Elena Aloisio, Felicia Stefania Falvella, Alberto Dolci, Agostino Riva and 2 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 29% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

Sarah BirindelliClinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy.
Maciej S TarkowskiDepartment of Biomedical and Clinical Sciences, "Luigi Sacco", University of Milan, Milan, Italy.
Marcello GallucciDepartment of Psychology, University of Milano Bicocca, Milan, Italy.
Marco SchiumaDepartment of Infectious Diseases, Division III, ASST Fatebenefratelli-Sacco, Milan, Italy.
Alice CovizziDepartment of Infectious Diseases, Division III, ASST Fatebenefratelli-Sacco, Milan, Italy.
Przemysław LewkowiczDepartment of Immunogenetics, Medical University of Lodz, Lodz, Poland.
Elena AloisioClinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy.
Felicia Stefania FalvellaClinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy.
Alberto DolciClinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy.
Agostino RivaDepartment of Biomedical and Clinical Sciences, "Luigi Sacco", University of Milan, Milan, Italy.
Massimo GalliDepartment of Biomedical and Clinical Sciences, "Luigi Sacco", University of Milan, Milan, Italy.
Mauro PanteghiniClinical Pathology Unit, ASST Fatebenefratelli-Sacco, Milan, Italy.
ASST Fatebenefratelli Sacco · ITLuigi Sacco Hospital · ITMedical University of Lodz · PLUniversity of Milan · ITUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A relevant portion of patients with disease caused by the severe acute respiratory syndrome coronavirus 2 (COVID-19) experience negative outcome, and several laboratory tests have been proposed to predict disease severity. Among others, dramatic changes in peripheral blood cells have been described. We developed and validated a laboratory score solely based on blood cell parameters to predict survival in hospitalized COVID-19 patients. We retrospectively analyzed 1,619 blood cell count from 226 consecutively hospitalized COVID-19 patients to select parameters for inclusion in a laboratory score predicting severity of disease and survival. The score was derived from lymphocyte- and granulocyte-associated parameters and validated on a separate cohort of 140 consecutive COVID-19 patients. Using ROC curve analysis, a best cutoff for score of 30.6 was derived, which was associated to an overall 82.0% sensitivity (95% CI: 78-84) and 82.5% specificity (95% CI: 80-84) for detecting outcome. The scoring trend effectively separated survivor and non-survivor groups, starting 2 weeks before the end of the hospitalization period. Patients' score time points were also classified into mild, moderate, severe, and critical according to the symptomatic oxygen therapy administered. Fluctuations of the score should be recorded to highlight a favorable or unfortunate trend of the disease. The predictive score was found to reflect and anticipate the disease gravity, defined by the type of the oxygen support used, giving a proof of its clinical relevance. It offers a fast and reliable tool for supporting clinical decisions and, most important, triage in terms of not only prioritization but also allocation of limited medical resources, especially in the period when therapies are still symptomatic and many are under development. In fact, a prolonged and progressive increase of the score can suggest impaired chances of survival and/or an urgent need for intensive care unit admission.

Indexed as

COVID-19HumansOxygenRetrospective StudiesROC CurveSARS-CoV-2Oxygenblood cell countclinical managementCOVID-19 outcomeimmunological changesoxygen therapyseverity scoretriage

Identifiers

PMID35371011
PMCPMC8971756
OpenAlexW4220686595

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.