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RESEARCH PRODUCT

Machine Learning to Predict In-Hospital Mortality in COVID-19 Patients Using Computed Tomography-Derived Pulmonary and Vascular Features

Giovanni Di LeoFrancesco DolciGiovanni MauriDomenico ZagariaEdoardo SegaliniPietro DannaMarina CodariIlaria VicentinAngelo SpinazzolaMarco AlìFrancesco SardanelliAlessio PaschèFilippo PesapaneSilvia TresoldiFrancesco SecchiAngelo VanzulliCarmelo MessinaDomenico AlbanoValeria TombiniLorenzo MonfardiniVeronica MagniSerena CarrieroDominik FleischmannDominik FleischmannMassimo CressoniLuca Maria SconfienzaNicola FlorSalvatore GittoClaudio BnàAlexis Elias MalavazosRiccardo FoàRoberto ArioliEmanuele AvolaGianmarco Della PepaGiovanni LeatiAndrea CozziSimone SchiaffinoMaurizio CariatiZeno Falaschi

subject

Medicine (miscellaneous)X-ray computedtomography030204 cardiovascular system & hematologyMachine learningcomputer.software_genreArticlelung030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicinepulmonary arterymedicine.arterymedicinesupport vector machinecomputerUnivariate analysisLungbusiness.industryRArea under the curveCOVID-19Emergency departmentneural networksmachine learningmedicine.anatomical_structureRadiological weaponPulmonary arteryMann–Whitney U testMedicineprognosisArtificial intelligenceTomographybusinesscomputer

description

Pulmonary parenchymal and vascular damage are frequently reported in COVID-19 patients and can be assessed with unenhanced chest computed tomography (CT), widely used as a triaging exam. Integrating clinical data, chest CT features, and CT-derived vascular metrics, we aimed to build a predictive model of in-hospital mortality using univariate analysis (Mann–Whitney U test) and machine learning models (support vectors machines (SVM) and multilayer perceptrons (MLP)). Patients with RT-PCR-confirmed SARS-CoV-2 infection and unenhanced chest CT performed on emergency department admission were included after retrieving their outcome (discharge or death), with an 85/15% training/test dataset split. Out of 897 patients, the 229 (26%) patients who died during hospitalization had higher median pulmonary artery diameter (29.0 mm) than patients who survived (27.0 mm, p &lt

yearjournalcountryeditionlanguage
2021-06-01Journal of Personalized Medicine
https://doi.org/10.3390/jpm11060501