The incremental value of computed tomography of COVID-19 pneumonia in predicting ICU admission
| Autor: | Giovanni Luca Dedola, Vittorio Miele, M. Betti, Edoardo Cavigli, Federico Giannelli, Maurizio Bartolucci, L. Fedeli, A. Taddeucci, Massimo Edoardo Di Natale, Germana Allescia, Michele Trezzi, Lorenzo Nicola Mazzoni, Diletta Cozzi, Alessio Baldini, Daniela Matarrese, Adriano Viviani, Sandro Santini, Guglielmo Consales, Mario Mascalchi, Sara Bicchi, Azienda Ospedaliero-Universitaria Careggi, Roberto Carpi, Letizia Vannucchi, D. Aquilini, Alessandra Bindi, S. Busoni, Chiara Zini, Matteo Benelli, Chiara Pozzessere, S. Mazzocchi, Pamela Lotti, Luca Bernardi |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Lung medicine.diagnostic_test Coronavirus disease 2019 (COVID-19) business.industry Computed tomography medicine.disease Triage Intensive care unit Icu admission law.invention Pneumonia medicine.anatomical_structure law Radiological weapon Emergency medicine medicine business |
| DOI: | 10.1101/2021.01.08.20249041 |
| Popis: | RationaleTriage is crucial for patient’s management and estimation of the required Intensive Care Unit (ICU) beds is fundamental for Health Systems during the COVID-19 pandemic.ObjectiveTo assess whether chest Computed Tomography (CT) of COVID-19 pneumonia has an incremental role in predicting patient’s admission to ICU.MethodsWe performed volumetric and texture analysis of the areas of the affected lung in CT of 115 outpatients with COVID-19 infection presenting to the Emergency Room with dyspnea and unresponsive hypoxyemia. Admission blood laboratory including lymphocyte count, serum lactate dehydrogenase, D-dimer and C-Reactive Protein and the ratio between the arterial partial pressure of oxygen and inspired oxygen were collected. By calculating the areas under the receiver-operating characteristic curves (AUC), we compared the performance of blood laboratory-arterial gas analyses features alone and combined with the CT features in two hybrid models (Hybrid radiological and Hybrid radiomics)for predicting ICU admission. Following a machine learning approach, 63 patients were allocated to the training and 52 to the validation set.Measurements and Main ResultsTwenty-nine (25%) of patients were admitted to ICU. The Hybrid radiological model comprising the lung %consolidation performed significantly (p=0.04) better in predicting ICU admission in the validation (AUC=0.82; 95%Confidence Interval 0.68-0.95) set than the blood laboratory-arterial gas analyses features alone (AUC=0.71; 95%Confidence Interval 0.56-0.86). A risk calculator for ICU admission was derived and is available at:https://github.com/cgplab/covidappConclusionsThe volume of the consolidated lung in CT of patients with COVID-19 pneumonia has a mild but significant incremental value in predicting ICU admission. |
| Databáze: | OpenAIRE |
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