Evidence map›Paper›PMID 39370709›Full record

ArticleClinical and translational medicine2024

Prediction of COVID-19 severity using machine learning.

Kanita Karaduzovic-Hadziabdic, Muhamed Adilovic, Lu Zhang, Andrew I Lumley, Pranay Shah, Muhammad Shoaib, Venkata Satagopam, Prashant Kumar Srivastava, Costanza Emanueli, Simona Greco and 21 more

Abstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical and translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

31 authors.

Kanita Karaduzovic-HadziabdicFaculty of Engineering and Natural Sciences, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
Muhamed AdilovicFaculty of Engineering and Natural Sciences, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina.
Lu ZhangBioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg.
Andrew I LumleyCardiovascular Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
Pranay ShahDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Muhammad ShoaibLuxembourg Center for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
Venkata SatagopamLuxembourg Center for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
Prashant Kumar SrivastavaNational Heart and Lung Institute, Imperial College London, London, UK.
Costanza EmanueliNational Heart and Lung Institute, Imperial College London, London, UK.
Simona GrecoMolecular Cardiology Laboratory, IRCCS Policlinico San Donato, Milan, Italy.
Alisia MadèMolecular Cardiology Laboratory, IRCCS Policlinico San Donato, Milan, Italy.
Teresa PadroCardiovascular Program-ICCC, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU); CIBERCV; Autonomous University of Barcelona, Barcelona, Spain.
Pedro DomingoCardiovascular Program-ICCC, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU); CIBERCV; Autonomous University of Barcelona, Barcelona, Spain.
Mitja LustrekDepartment of Intelligent Systems, Jozef Stefan Institute, Ljubljana, Slovenia.
Markus ScholzGroup Genetical Statistics and Biomathematical Modelling, Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
Maciej RosolowskiGroup Genetical Statistics and Biomathematical Modelling, Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
Marko JordanDepartment of Intelligent Systems, Jozef Stefan Institute, Ljubljana, Slovenia.
Bettina BenczikCardiometabolic and HUN-REN-SU System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
Bence ÁggCardiometabolic and HUN-REN-SU System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
Péter FerdinandyCardiometabolic and HUN-REN-SU System Pharmacology Research Group, Department of Pharmacology and Pharmacotherapy, Semmelweis University, Budapest, Hungary.
Andrew H BakerCentre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, UK.
Guy FagherazziDeep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
Markus OllertDepartment of Infection and Immunity, Luxembourg Institute of Health, Esch-Sur-Alzette, Luxembourg.
Joanna MichelFiralis SA, Huningue, France.
Gabriel SanchezFiralis SA, Huningue, France.
Hüseyin FiratFiralis SA, Huningue, France.
Timo BrandenburgerDepartment of Anesthesiology, University Hospital Düsseldorf, Heinrich-Heine University Duesseldorf, Moorenstr, Germany.
Fabio MartelliMolecular Cardiology Laboratory, IRCCS Policlinico San Donato, Milan, Italy.ORCID 0000-0002-8624-7738
Lina BadimonCardiovascular Program-ICCC, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU); CIBERCV; Autonomous University of Barcelona, Barcelona, Spain.ORCID 0000-0002-9162-2459
Yvan DevauxCardiovascular Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.ORCID 0000-0002-5321-8543
COVIRNA consortium (www.covirna.eu)

Funding

André Losch Fondation"Befektetés a jövőbe" NKFIH 2020-1.1.6-JÖVŐ-2021-00013European Regional Development Fund, FEDER, convention 2018-04-026-21European Union RRF-2.3.1-21-2022-00003Fonds National de la Recherche Luxembourg C14/BM/8225223Fonds National de la Recherche Luxembourg C17/BM/11613033Fonds National de la Recherche Luxembourg COVID-19/2020-1/14719577/miRCOVIDFonds National de la Recherche Luxembourg Predi-COVID/14716273Heart Foundation-Daniel Wagner of Luxembourg,Horizon 2020 Framework Programme 101016072HUN-REN Hungarian Research NetworkMinistero della Salute POS T4 CAL.HUB.RIA cod. T4-AN-09Ministero della Salute RF-2019-12368521Ministero della Salute Ricerca Corrente 2024 1.07.128Ministry for Innovation and Technology / National Research Development and Innovation Fund 2020-1.1.5-GYORSÍTÓSÁVMinistry of Higher Education and Research, LuxembourgNext Generation EU, PNRR M6C2 Inv. 2.1 PNRR-MAD-2022-12375790 and PNRR/2022/C9/MCID/I8 FibroThera
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

COVID-19Machine LearningSeverity of Illness IndexFemaleHumansMaleMiddle AgedSARS-CoV-2

Identifiers

PMID39370709
PMCPMC11456675

What Socratic 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 Socratic graph.