Evidence map›Paper›PMID 38908098›Full record

ArticleEBioMedicine2024

The long Pentraxin PTX3 serves as an early predictive biomarker of co-infections in COVID-19.

Francesco Scavello, Enrico Brunetta, Sarah N Mapelli, Emanuele Nappi, Ian David García Martín, Marina Sironi, Roberto Leone, Simone Solano, Giovanni Angelotti, Domenico Supino and 16 more

Erratum issuedAbstract read
In one paragraph

Article in EBioMedicine, 2024. 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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Francesco ScavelloIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Enrico BrunettaInfectious Diseases Unit, Hospital Health Direction, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Sarah N MapelliIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Emanuele NappiIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy.
Ian David García MartínDepartment of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy.
Marina SironiIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Roberto LeoneIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Simone SolanoIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Giovanni AngelottiArtificial Intelligence Center, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Domenico SupinoIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Silvia CarnevaleIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Hang ZhongIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy.
Elena MagriniIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Matteo StravalaciIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Alessandro ProttiDepartment of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy; Department of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Alessandro SantiniDepartment of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy; Department of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Elena CostantiniDepartment of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Victor SavevskiArtificial Intelligence Center, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Antonio VozaDepartment of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy; Emergency Department, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Barbara BottazziIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Michele BartolettiInfectious Diseases Unit, Hospital Health Direction, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy.
Maurizio CecconiDepartment of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy; Department of Anesthesia and Intensive Care, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Alberto MantovaniIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy; The William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
Paola MorelliInfectious Diseases Unit, Hospital Health Direction, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Federica TordatoInfectious Diseases Unit, Hospital Health Direction, IRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy.
Cecilia GarlandaIRCCS Humanitas Research Hospital, 20089, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, 20072, Pieve Emanuele, Milan, Italy. Electronic address: cecilia.garlanda@humanitasresearch.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 clinical course is highly variable and secondary infections contribute to COVID-19 complexity. Early detection of secondary infections is clinically relevant for patient outcome. Procalcitonin (PCT) and C-reactive protein (CRP) are the most used biomarkers of infections. Pentraxin 3 (PTX3) is an acute phase protein with promising performance as early biomarker in infections. In patients with COVID-19, PTX3 plasma concentrations at hospital admission are independent predictor of poor outcome. In this study, we assessed whether PTX3 contributes to early identification of co-infections during the course of COVID-19.

methodsWe analyzed PTX3 levels in patients affected by COVID-19 with (n = 101) or without (n = 179) community or hospital-acquired fungal or bacterial secondary infections (CAIs or HAIs).

findingsPTX3 plasma concentrations at diagnosis of CAI or HAI were significantly higher than those in patients without secondary infections. Compared to PCT and CRP, the increase of PTX3 plasma levels was associated with the highest hazard ratio for CAIs and HAIs (aHR 11.68 and 24.90). In multivariable Cox regression analysis, PTX3 was also the most significant predictor of 28-days mortality or intensive care unit admission of patients with potential co-infections, faring more pronounced than CRP and PCT.

interpretationPTX3 is a promising predictive biomarker for early identification and risk stratification of patients with COVID-19 and co-infections.

fundingDolce & Gabbana fashion house donation; Ministero della Salute for COVID-19; EU funding within the MUR PNRR Extended Partnership initiative on Emerging Infectious Diseases (Project no. PE00000007, INF-ACT) and MUR PNRR Italian network of excellence for advanced diagnosis (Project no. PNC-E3-2022-23683266 PNC-HLS-DA); EU MSCA (project CORVOS 860044).

Indexed as

BiomarkersCoinfectionCOVID-19C-Reactive ProteinSARS-CoV-2Serum Amyloid P-ComponentAgedAged, 80 and overBacterial InfectionsFemaleHumansMaleMiddle AgedMycosesPentraxinsProcalcitoninBiomarkersC-Reactive ProteinPentraxinsProcalcitoninSerum Amyloid P-ComponentBiomarkerCommunity-acquired infectionsCOVID-19Hospital-acquired infectionsPTX3

Identifiers

PMID38908098
PMCPMC11245991

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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.