Artificial Intelligence - SARS-CoV-2 (COVID-19) Risk Evaluation
AI-SCoRE
1 other identifier
observational
2,000
1 country
1
Brief Summary
The management of COVID-19 patients in overwhelmed hospital facing the pandemic is a clinical challenge. The improvement of decision making may allow a better allocation of available resources and a better treatment of patients at higher risk. Chest CT has been widely adopted for COVID-19 pneumonia diagnosis. Several experiences documented the capability of Artificial Intelligence to improve and fasten COVID-19 pneumonia detection, mainly using chest X-ray. Aim of the present study was to develop and validate an Artificial Intelligence approach integrating clinical and imaging data (automatically extracted through the adoption of dedicated neural networks) for the creation of a cloud platform capable of performing automatic patients risk stratification. Such an approach could be used for triage of COVID-19 patients in the emergency department, with the aim to improve healthcare personnel decision-making and allocation of resources during health emergencies.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Feb 2020
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 16, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 30, 2020
CompletedFirst Submitted
Initial submission to the registry
April 6, 2021
CompletedFirst Posted
Study publicly available on registry
April 8, 2021
CompletedStudy Completion
Last participant's last visit for all outcomes
June 30, 2021
CompletedMay 1, 2025
April 1, 2025
8 months
April 6, 2021
April 29, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis.
9 months
Secondary Outcomes (1)
Validation of the developed AI platform on italian second wave of Covid-19 patients
3 months
Study Arms (2)
COVID-19 first wave patients
1700 patients retrospectively enrolled in 15 Italian hospitals from 16/2/2020 to 29/4/2020.
COVID-19 second wave patients
300 patients prospectively enrolled in IRCCS San Raffaele Hospital from 19/10/2020 to 31/12/2020.
Eligibility Criteria
Patients with confirmed SARS-CoV-2 infection with RT-PCR who performed non contrast chest CT scan within 72 hours after admission to the emergency department
You may qualify if:
- confirmed SARS-CoV-2 infection with RT-PCR
- non contrast chest CT scan performed within 72 hours after admission to the emergency department
You may not qualify if:
- age \< 18 ys
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- IRCCS San Raffaelelead
- Regione Lombardiacollaborator
- Orobix Srlcollaborator
- Microsoft Corporationcollaborator
- ASST Bergamo Estcollaborator
- Centro Cardiologico Monzinocollaborator
- NVIDIA Corporationcollaborator
- PORINI Srlcollaborator
Study Sites (1)
IRCCS San Raffaele
Milan, 20132, Italy
Related Publications (19)
Emanuel EJ, Persad G, Upshur R, Thome B, Parker M, Glickman A, Zhang C, Boyle C, Smith M, Phillips JP. Fair Allocation of Scarce Medical Resources in the Time of Covid-19. N Engl J Med. 2020 May 21;382(21):2049-2055. doi: 10.1056/NEJMsb2005114. Epub 2020 Mar 23. No abstract available.
PMID: 32202722BACKGROUNDCiceri F, Castagna A, Rovere-Querini P, De Cobelli F, Ruggeri A, Galli L, Conte C, De Lorenzo R, Poli A, Ambrosio A, Signorelli C, Bossi E, Fazio M, Tresoldi C, Colombo S, Monti G, Fominskiy E, Franchini S, Spessot M, Martinenghi C, Carlucci M, Beretta L, Scandroglio AM, Clementi M, Locatelli M, Tresoldi M, Scarpellini P, Martino G, Bosi E, Dagna L, Lazzarin A, Landoni G, Zangrillo A. Early predictors of clinical outcomes of COVID-19 outbreak in Milan, Italy. Clin Immunol. 2020 Aug;217:108509. doi: 10.1016/j.clim.2020.108509. Epub 2020 Jun 12.
PMID: 32535188BACKGROUNDPatel D, Kher V, Desai B, Lei X, Cen S, Nanda N, Gholamrezanezhad A, Duddalwar V, Varghese B, Oberai AA. Machine learning based predictors for COVID-19 disease severity. Sci Rep. 2021 Feb 25;11(1):4673. doi: 10.1038/s41598-021-83967-7.
PMID: 33633145BACKGROUNDPalmisano A, Scotti GM, Ippolito D, Morelli MJ, Vignale D, Gandola D, Sironi S, De Cobelli F, Ferrante L, Spessot M, Tonon G, Tacchetti C, Esposito A. Chest CT in the emergency department for suspected COVID-19 pneumonia. Radiol Med. 2021 Mar;126(3):498-502. doi: 10.1007/s11547-020-01302-y. Epub 2020 Nov 9.
PMID: 33165767BACKGROUNDPark JH, Lee SG, Ahn S, Kim JY, Song J, Moon S, Cho H. Strategies to prevent COVID-19 transmission in the emergency department of a regional base hospital in Korea: From index patient until pandemic declaration. Am J Emerg Med. 2021 Aug;46:247-253. doi: 10.1016/j.ajem.2020.07.056. Epub 2020 Jul 24.
PMID: 33059986BACKGROUNDAi T, Yang Z, Hou H, Zhan C, Chen C, Lv W, Tao Q, Sun Z, Xia L. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020 Aug;296(2):E32-E40. doi: 10.1148/radiol.2020200642. Epub 2020 Feb 26.
PMID: 32101510BACKGROUNDWehbe RM, Sheng J, Dutta S, Chai S, Dravid A, Barutcu S, Wu Y, Cantrell DR, Xiao N, Allen BD, MacNealy GA, Savas H, Agrawal R, Parekh N, Katsaggelos AK. DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set. Radiology. 2021 Apr;299(1):E167-E176. doi: 10.1148/radiol.2020203511. Epub 2020 Nov 24.
PMID: 33231531BACKGROUNDSchalekamp S, Huisman M, van Dijk RA, Boomsma MF, Freire Jorge PJ, de Boer WS, Herder GJM, Bonarius M, Groot OA, Jong E, Schreuder A, Schaefer-Prokop CM. Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19. Radiology. 2021 Jan;298(1):E46-E54. doi: 10.1148/radiol.2020202723. Epub 2020 Aug 13.
PMID: 32787701BACKGROUNDCheng FY, Joshi H, Tandon P, Freeman R, Reich DL, Mazumdar M, Kohli-Seth R, Levin M, Timsina P, Kia A. Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients. J Clin Med. 2020 Jun 1;9(6):1668. doi: 10.3390/jcm9061668.
PMID: 32492874BACKGROUNDLiang W, Yao J, Chen A, Lv Q, Zanin M, Liu J, Wong S, Li Y, Lu J, Liang H, Chen G, Guo H, Guo J, Zhou R, Ou L, Zhou N, Chen H, Yang F, Han X, Huan W, Tang W, Guan W, Chen Z, Zhao Y, Sang L, Xu Y, Wang W, Li S, Lu L, Zhang N, Zhong N, Huang J, He J. Early triage of critically ill COVID-19 patients using deep learning. Nat Commun. 2020 Jul 15;11(1):3543. doi: 10.1038/s41467-020-17280-8.
PMID: 32669540BACKGROUNDMonaco CG, Zaottini F, Schiaffino S, Villa A, Della Pepa G, Carbonaro LA, Menicagli L, Cozzi A, Carriero S, Arpaia F, Di Leo G, Astengo D, Rosenberg I, Sardanelli F. Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study. Eur Radiol Exp. 2020 Dec 15;4(1):68. doi: 10.1186/s41747-020-00195-w.
PMID: 33319321BACKGROUNDWong HYF, Lam HYS, Fong AH, Leung ST, Chin TW, Lo CSY, Lui MM, Lee JCY, Chiu KW, Chung TW, Lee EYP, Wan EYF, Hung IFN, Lam TPW, Kuo MD, Ng MY. Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19. Radiology. 2020 Aug;296(2):E72-E78. doi: 10.1148/radiol.2020201160. Epub 2020 Mar 27.
PMID: 32216717BACKGROUNDChorath A, Choi Y, Turkbey EB, Ahlman MA, Sibley CT, Liu S, Bluemke DA, Sandfort V. Coronary CT Angiography and Carotid MRI Improve Phenotyping of Disease Extent Compared with ACC/AHA Risk Score Alone. Radiol Cardiothorac Imaging. 2020 Feb 27;2(1):e190068. doi: 10.1148/ryct.2020190068.
PMID: 32715300BACKGROUNDNeri E, Miele V, Coppola F, Grassi R. Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology. Radiol Med. 2020 May;125(5):505-508. doi: 10.1007/s11547-020-01197-9. Epub 2020 Apr 29.
PMID: 32350794BACKGROUNDBai HX, Wang R, Xiong Z, Hsieh B, Chang K, Halsey K, Tran TML, Choi JW, Wang DC, Shi LB, Mei J, Jiang XL, Pan I, Zeng QH, Hu PF, Li YH, Fu FX, Huang RY, Sebro R, Yu QZ, Atalay MK, Liao WH. Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT. Radiology. 2020 Sep;296(3):E156-E165. doi: 10.1148/radiol.2020201491. Epub 2020 Apr 27.
PMID: 32339081BACKGROUNDLi L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q, Cao K, Liu D, Wang G, Xu Q, Fang X, Zhang S, Xia J, Xia J. Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy. Radiology. 2020 Aug;296(2):E65-E71. doi: 10.1148/radiol.2020200905. Epub 2020 Mar 19.
PMID: 32191588BACKGROUNDGiannini F, Toselli M, Palmisano A, Cereda A, Vignale D, Leone R, Nicoletti V, Gnasso C, Monello A, Manfrini M, Khokhar A, Sticchi A, Biagi A, Turchio P, Tacchetti C, Landoni G, Boccia E, Campo G, Scoccia A, Ponticelli F, Danzi GB, Loffi M, Muri M, Pontone G, Andreini D, Mancini EM, Casella G, Iannopollo G, Nannini T, Ippolito D, Bellani G, Franzesi CT, Patelli G, Besana F, Costa C, Vignali L, Benatti G, Sverzellati N, Scarnecchia E, Lombardo FP, Anastasio F, Iannaccone M, Vaudano PG, Pacielli A, Baffoni L, Gardi I, Cesini E, Sperandio M, Micossi C, De Carlini CC, Spreafico C, Maggiolini S, Bonaffini PA, Iacovoni A, Sironi S, Senni M, Fominskiy E, De Cobelli F, Maggioni AP, Rapezzi C, Ferrari R, Colombo A, Esposito A. Coronary and total thoracic calcium scores predict mortality and provides pathophysiologic insights in COVID-19 patients. J Cardiovasc Comput Tomogr. 2021 Sep-Oct;15(5):421-430. doi: 10.1016/j.jcct.2021.03.003. Epub 2021 Mar 11.
PMID: 33744175BACKGROUNDEsposito A, Palmisano A, Toselli M, Vignale D, Cereda A, Rancoita PMV, Leone R, Nicoletti V, Gnasso C, Monello A, Biagi A, Turchio P, Landoni G, Gallone G, Monti G, Casella G, Iannopollo G, Nannini T, Patelli G, Di Mare L, Loffi M, Sergio P, Ippolito D, Sironi S, Pontone G, Andreini D, Mancini EM, Di Serio C, De Cobelli F, Ciceri F, Zangrillo A, Colombo A, Tacchetti C, Giannini F. Chest CT-derived pulmonary artery enlargement at the admission predicts overall survival in COVID-19 patients: insight from 1461 consecutive patients in Italy. Eur Radiol. 2021 Jun;31(6):4031-4041. doi: 10.1007/s00330-020-07622-x. Epub 2020 Dec 23.
PMID: 33355697BACKGROUNDUfuk F, Demirci M, Sagtas E, Akbudak IH, Ugurlu E, Sari T. The prognostic value of pneumonia severity score and pectoralis muscle Area on chest CT in adult COVID-19 patients. Eur J Radiol. 2020 Oct;131:109271. doi: 10.1016/j.ejrad.2020.109271. Epub 2020 Sep 9.
PMID: 32942198BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Antonio Esposito, MD
IRCCS San Raffaele
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Associate Professor
Study Record Dates
First Submitted
April 6, 2021
First Posted
April 8, 2021
Study Start
February 16, 2020
Primary Completion
September 30, 2020
Study Completion
June 30, 2021
Last Updated
May 1, 2025
Record last verified: 2025-04
Data Sharing
- IPD Sharing
- Will not share