Evidence map›Paper›PMID 34140530›Full record

ArticleScientific reports2021

Baseline T-lymphocyte subset absolute counts can predict both outcome and severity in SARS-CoV-2 infected patients: a single center study.

Marco Iannetta, Francesco Buccisano, Daniela Fraboni, Vincenzo Malagnino, Laura Campogiani, Elisabetta Teti, Ilaria Spalliera, Benedetta Rossi, Andrea Di Lorenzo, Raffaele Palmieri and 6 more

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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

16 authors.

Marco IannettaDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy. marco.iannetta@uniroma2.it.ORCID 0000-0002-6938-8627
Francesco BuccisanoDepartment of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Daniela FraboniDepartment of Oncohematology, Policlinico Tor Vergata, Rome, Italy.
Vincenzo MalagninoDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Laura CampogianiDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Elisabetta TetiDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Ilaria SpallieraDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Benedetta RossiDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Andrea Di LorenzoDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Raffaele PalmieriDepartment of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.
Angela CreaDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Marta ZordanDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Pietro VitaleDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Maria Teresa VosoDepartment of Biomedicine and Prevention, Tor Vergata University, Rome, Italy.ORCID 0000-0002-6164-4761
Massimo AndreoniDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.
Loredana SarmatiDepartment of System Medicine, Tor Vergata University, Via Montpellier 1, 00133, Rome, Italy.ORCID 0000-0003-1452-0333

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to evaluate the role of baseline lymphocyte subset counts in predicting the outcome and severity of COVID-19 patients. Hospitalized patients confirmed to be infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were included and classified according to in-hospital mortality (survivors/nonsurvivors) and the maximal oxygen support/ventilation supply required (nonsevere/severe). Demographics, clinical and laboratory data, and peripheral blood lymphocyte subsets were retrospectively analyzed. Overall, 160 patients were retrospectively included in the study. T-lymphocyte subset (total CD3+, CD3+ CD4+, CD3+ CD8+, CD3+ CD4+ CD8+ double positive [DP] and CD3+ CD4- CD8- double negative [DN]) absolute counts were decreased in nonsurvivors and in patients with severe disease compared to survivors and nonsevere patients (p < 0.001). Multivariable logistic regression analysis showed that absolute counts of CD3+ T-lymphocytes < 524 cells/µl, CD3+ CD4+ < 369 cells/µl, and the number of T-lymphocyte subsets below the cutoff (T-lymphocyte subset index [TLSI]) were independent predictors of in-hospital mortality. Baseline T-lymphocyte subset counts and TLSI were also predictive of disease severity (CD3+  < 733 cells/µl; CD3+ CD4+ < 426 cells/µl; CD3+ CD8+ < 262 cells/µl; CD3+ DP < 4.5 cells/µl; CD3+ DN < 18.5 cells/µl). The evaluation of peripheral T-lymphocyte absolute counts in the early stages of COVID-19 might represent a useful tool for identifying patients at increased risk of unfavorable outcomes.

Indexed as

CD4-Positive T-LymphocytesCD8-Positive T-LymphocytesSeverity of Illness IndexT-Lymphocyte SubsetsAgedAged, 80 and overCOVID-19FemaleHospital MortalityHumansLymphocyte CountMaleMiddle AgedNasopharynxRetrospective StudiesReverse Transcriptase Polymerase Chain Reaction

Identifiers

PMID34140530
PMCPMC8211786

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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.