PROTEUS Study : A Prospective Randomized Controlled Trial Evaluating the Use of Artificial Intelligence in Stress Echocardiography
Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved..
BACKGROUND: Stress echocardiography (SE) is one of the most commonly used diagnostic imaging tests for coronary artery disease (CAD) but requires clinicians to visually assess scans to identify patients who may benefit from invasive investigation and treatment. EchoGo Pro provides an automated interpretation of SE based on artificial intelligence (AI) image analysis. In reader studies, use of EchoGo Pro when making clinical decisions improves diagnostic accuracy and confidence. Prospective evaluation in real world practice is now important to understand the impact of EchoGo Pro on the patient pathway and outcome.
METHODS: PROTEUS is a randomized, multicenter, 2-armed, noninferiority study aiming to recruit 2,500 participants from National Health Service (NHS) hospitals in the UK referred to SE clinics for investigation of suspected CAD. All participants will undergo a stress echocardiogram protocol as per local hospital policy. Participants will be randomized 1:1 to a control group, representing current practice, or an intervention group, in which clinicians will receive an AI image analysis report (EchoGo Pro, Ultromics Ltd, Oxford, UK) to use during image interpretation, indicating the likelihood of severe CAD. The primary outcome will be appropriateness of clinician decision to refer for coronary angiography. Secondary outcomes will assess other health impacts including appropriate use of other clinical management approaches, impact on variability in decision making, patient and clinician qualitative experience and a health economic analysis.
DISCUSSION: This will be the first study to assess the impact of introducing an AI medical diagnostic aid into the standard care pathway of patients with suspected CAD being investigated with SE.
TRIAL REGISTRATION: Clinicaltrials.gov registration number NCT05028179, registered on 31 August 2021; ISRCTN: ISRCTN15113915; IRAS ref: 293515; REC ref: 21/NW/0199.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:263 |
---|---|
Enthalten in: |
American heart journal - 263(2023) vom: 15. Sept., Seite 123-132 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Woodward, Gary [VerfasserIn] |
---|
Links: |
---|
Themen: |
Journal Article |
---|
Anmerkungen: |
Date Completed 14.08.2023 Date Revised 15.08.2023 published: Print-Electronic ClinicalTrials.gov: NCT05028179 ISRCTN: ISRCTN15113915 Citation Status MEDLINE |
---|
doi: |
10.1016/j.ahj.2023.05.003 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM356953092 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM356953092 | ||
003 | DE-627 | ||
005 | 20231226071540.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.ahj.2023.05.003 |2 doi | |
028 | 5 | 2 | |a pubmed24n1189.xml |
035 | |a (DE-627)NLM356953092 | ||
035 | |a (NLM)37192698 | ||
035 | |a (PII)S0002-8703(23)00114-X | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Woodward, Gary |e verfasserin |4 aut | |
245 | 1 | 0 | |a PROTEUS Study |b A Prospective Randomized Controlled Trial Evaluating the Use of Artificial Intelligence in Stress Echocardiography |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 14.08.2023 | ||
500 | |a Date Revised 15.08.2023 | ||
500 | |a published: Print-Electronic | ||
500 | |a ClinicalTrials.gov: NCT05028179 | ||
500 | |a ISRCTN: ISRCTN15113915 | ||
500 | |a Citation Status MEDLINE | ||
520 | |a Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved. | ||
520 | |a BACKGROUND: Stress echocardiography (SE) is one of the most commonly used diagnostic imaging tests for coronary artery disease (CAD) but requires clinicians to visually assess scans to identify patients who may benefit from invasive investigation and treatment. EchoGo Pro provides an automated interpretation of SE based on artificial intelligence (AI) image analysis. In reader studies, use of EchoGo Pro when making clinical decisions improves diagnostic accuracy and confidence. Prospective evaluation in real world practice is now important to understand the impact of EchoGo Pro on the patient pathway and outcome | ||
520 | |a METHODS: PROTEUS is a randomized, multicenter, 2-armed, noninferiority study aiming to recruit 2,500 participants from National Health Service (NHS) hospitals in the UK referred to SE clinics for investigation of suspected CAD. All participants will undergo a stress echocardiogram protocol as per local hospital policy. Participants will be randomized 1:1 to a control group, representing current practice, or an intervention group, in which clinicians will receive an AI image analysis report (EchoGo Pro, Ultromics Ltd, Oxford, UK) to use during image interpretation, indicating the likelihood of severe CAD. The primary outcome will be appropriateness of clinician decision to refer for coronary angiography. Secondary outcomes will assess other health impacts including appropriate use of other clinical management approaches, impact on variability in decision making, patient and clinician qualitative experience and a health economic analysis | ||
520 | |a DISCUSSION: This will be the first study to assess the impact of introducing an AI medical diagnostic aid into the standard care pathway of patients with suspected CAD being investigated with SE | ||
520 | |a TRIAL REGISTRATION: Clinicaltrials.gov registration number NCT05028179, registered on 31 August 2021; ISRCTN: ISRCTN15113915; IRAS ref: 293515; REC ref: 21/NW/0199 | ||
650 | 4 | |a Randomized Controlled Trial | |
650 | 4 | |a Multicenter Study | |
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
700 | 1 | |a Bajre, Mamta |e verfasserin |4 aut | |
700 | 1 | |a Bhattacharyya, Sanjeev |e verfasserin |4 aut | |
700 | 1 | |a Breen, Maria |e verfasserin |4 aut | |
700 | 1 | |a Chiocchia, Virginia |e verfasserin |4 aut | |
700 | 1 | |a Dawes, Helen |e verfasserin |4 aut | |
700 | 1 | |a Dehbi, Hakim-Moulay |e verfasserin |4 aut | |
700 | 1 | |a Descamps, Tine |e verfasserin |4 aut | |
700 | 1 | |a Frangou, Elena |e verfasserin |4 aut | |
700 | 1 | |a Fazakarley, Carol-Ann |e verfasserin |4 aut | |
700 | 1 | |a Harris, Victoria |e verfasserin |4 aut | |
700 | 1 | |a Hawkes, Will |e verfasserin |4 aut | |
700 | 1 | |a Hewer, Oliver |e verfasserin |4 aut | |
700 | 1 | |a Johnson, Casey L |e verfasserin |4 aut | |
700 | 1 | |a Krasner, Samuel |e verfasserin |4 aut | |
700 | 1 | |a Laidlaw, Lynn |e verfasserin |4 aut | |
700 | 1 | |a Lau, Jonathan |e verfasserin |4 aut | |
700 | 1 | |a Marwick, Tom |e verfasserin |4 aut | |
700 | 1 | |a Petersen, Steffen E |e verfasserin |4 aut | |
700 | 1 | |a Piotrowska, Hania |e verfasserin |4 aut | |
700 | 1 | |a Ridgeway, Ged |e verfasserin |4 aut | |
700 | 1 | |a Ripley, David P |e verfasserin |4 aut | |
700 | 1 | |a Sanderson, Emily |e verfasserin |4 aut | |
700 | 1 | |a Savage, Natalie |e verfasserin |4 aut | |
700 | 1 | |a Sarwar, Rizwan |e verfasserin |4 aut | |
700 | 1 | |a Tetlow, Louise |e verfasserin |4 aut | |
700 | 1 | |a Thompson, Ben |e verfasserin |4 aut | |
700 | 1 | |a Thulborn, Samantha |e verfasserin |4 aut | |
700 | 1 | |a Williamson, Victoria |e verfasserin |4 aut | |
700 | 1 | |a Woodward, William |e verfasserin |4 aut | |
700 | 1 | |a Upton, Ross |e verfasserin |4 aut | |
700 | 1 | |a Leeson, Paul |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t American heart journal |d 1945 |g 263(2023) vom: 15. Sept., Seite 123-132 |w (DE-627)NLM000012270 |x 1097-6744 |7 nnns |
773 | 1 | 8 | |g volume:263 |g year:2023 |g day:15 |g month:09 |g pages:123-132 |
856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.ahj.2023.05.003 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 263 |j 2023 |b 15 |c 09 |h 123-132 |