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Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients.Eur Radiol. 2021 Mar; 31(3):1770-1779.ER
Abstract
OBJECTIVE
To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19.
METHODS
This retrospective single-center study included adult patients presenting to the emergency department (ED) between February 25 and April 9, 2020, with SARS-CoV-2 infection confirmed on real-time reverse transcriptase polymerase chain reaction (RT-PCR). Initial CXRs obtained on ED presentation were evaluated by a deep learning artificial intelligence (AI) system and compared with the Radiographic Assessment of Lung Edema (RALE) score, calculated by two experienced radiologists. Death and critical COVID-19 (admission to intensive care unit (ICU) or deaths occurring before ICU admission) were identified as clinical outcomes. Independent predictors of adverse outcomes were evaluated by multivariate analyses.
RESULTS
Six hundred ninety-seven 697 patients were included in the study: 465 males (66.7%), median age of 62 years (IQR 52-75). Multivariate analyses adjusting for demographics and comorbidities showed that an AI system-based score ≥ 30 on the initial CXR was an independent predictor both for mortality (HR 2.60 (95% CI 1.69 - 3.99; p < 0.001)) and critical COVID-19 (HR 3.40 (95% CI 2.35-4.94; p < 0.001)). Other independent predictors were RALE score, older age, male sex, coronary artery disease, COPD, and neurodegenerative disease.
CONCLUSION
AI- and radiologist-assessed disease severity scores on CXRs obtained on ED presentation were independent and comparable predictors of adverse outcomes in patients with COVID-19.
TRIAL REGISTRATION
ClinicalTrials.gov NCT04318366 (https://clinicaltrials.gov/ct2/show/NCT04318366).
KEY POINTS
• AI system-based score ≥ 30 and a RALE score ≥ 12 at CXRs performed at ED presentation are independent and comparable predictors of death and/or ICU admission in COVID-19 patients. • Other independent predictors are older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. • The comparable performance of the AI system in relation to a radiologist-assessed score in predicting adverse outcomes may represent a game-changer in resource-constrained settings.
Links
MeSH
Age FactorsAgedArtificial IntelligenceCOVID-19ComorbidityCoronary Artery DiseaseDeep LearningEmergency Service, HospitalFemaleHospitalizationHumansIntensive Care UnitsItalyMaleMiddle AgedMortalityNeurodegenerative DiseasesPrognosisProportional Hazards ModelsPulmonary Disease, Chronic ObstructiveRadiographyRadiography, ThoracicRetrospective StudiesSARS-CoV-2Severity of Illness IndexSex FactorsTomography, X-Ray Computed
Pub Type(s)
Journal Article
Language
eng
PubMed ID
32945968