An Evaluation of the Long-Term Impact of Assistive AI on Anaesthetists' Ultrasound Scanning for UGRA

NCT05583032 | Completed

• 1 other identifier: IU2022_AG_10
• Study Type: observational
• Target: 58
• Locations: 1 country
• Sites: 1

Brief Summary

A randomised, blinded interventional prospective study evaluating the long-term impact of assistive artificial intelligence on anaesthetists' ultrasound scanning for regional anaesthesia.

Conditions

Ultrasound Imaging of Anatomical Structures

Keywords

ScanNav; Anatomy PNB

Outcome Measures

Primary Outcomes (1)

• Block identification (long-term)

  Identification of an appropriate block view by participant \[blinded expert's opinion; Y/N\] both with and without the use of ScanNav Anatomy PNB for ultrasound scanning (8 - 10 weeks after teaching)

  8-10 weeks

Secondary Outcomes (4)

• Block identification (immediate)

  Time 0

• Anatomy identification

  Time 0 and 8-10 weeks

• Participant confidence

  Time 0 and 8-10 weeks

• Overall scan performance

  Time 0 and 8-10 weeks

Study Arms (2)

ScanNav Anatomy PNB aided

Participants completing scans for regional anaesthesia with the aid of ScanNav Anatomy PNB.

Device: ScanNav Anatomy PNB

ScanNav Anatomy PNB unaided

Participants completing scans for regional anaesthesia without the aid of ScanNav Anatomy PNB.

Interventions

ScanNav Anatomy PNB DEVICE

AI-powered device that highlights anatomy of interest during ultrasound scans.

ScanNav Anatomy PNB aided

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

70 participants will be recruited to represent the intended user population (anaesthetists qualified to perform UGRA, but non-experts in the field of regional anaesthesia). Potential study participants will be identified by approaching professional anaesthesia/anaesthetics societies, networks (e.g., Wales Regional Anaesthesia Group - South).

You may qualify if:

• Anaesthetist in Stage 1 of UK Anaesthesia Core/Specialty Training (CT 1-3)
• Able to comprehend and sign the Informed Consent prior to enrolment in the study
• Available to travel and attend the study day in person

You may not qualify if:

• Aged \<18 years of age
• Unwilling or unable to provide informed consent
• Expert in UGRA (see definition above)

Sponsors & Collaborators

• IntelligentUltrasound Limited: lead

Study Sites (1)

UCH Education Centre

London, NW1 2PG, United Kingdom

Location

Related Publications (1)

• Kowa CY, Morecroft M, Macfarlane AJR, Burckett-St Laurent D, Pawa A, West S, Margetts S, Haslam N, Ashken T, Sebastian MP, Thottungal A, Womack J, Noble JA, Higham H, Bowness JS. Prospective randomized evaluation of the sustained impact of assistive artificial intelligence on anesthetists' ultrasound scanning for regional anesthesia. BMJ Surg Interv Health Technol. 2024 Oct 16;6(1):e000264. doi: 10.1136/bmjsit-2024-000264. eCollection 2024.

  PMID: 39430867 DERIVED

Study Officials

• James Bowness, Dr

  Intelligent Ultrasound

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 13, 2022
• First Posted: October 17, 2022
• Study Start: November 24, 2022
• Primary Completion: January 30, 2023
• Study Completion: July 30, 2023
• Last Updated: August 14, 2023

Record last verified: 2023-08

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)