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This is a single-center, prospective study to be undertaken at University of Oregon, Portland, USA. The aim is to provide data on the clinical performance of ScanNav Anatomy PNB for identification of anatomical structures during UGRA scanning, in particular:
Background:
The American Society of Regional Anesthesia and Pain Medicine (ASRA) has published evidence-based assessment of ultrasound-guided regional anesthesia (Neal et al., 2010) concluding that ultrasound guidance is superior or equal to other non-ultrasound nerve localization techniques. A subsequent publication from ASRA (Neal et al., 2016), has strengthened their position of ultrasound guidance being superior than other methods, including for the reduction of local anesthetic systemic toxicity. However, ultrasound-guided regional anesthesia (UGRA) is a difficult technique to master. A key activity of UGRA is ultrasound image interpretation (Sites et al., 2009) which ScanNav Anatomy PNB is designed to support.
Methodology:
15 participants (anesthesiologists capable of independently performing UGRA) will be recruited to evaluate the performance and benefit of ScanNav Anatomy PNB device in person, by scanning 2 healthy models (n=1 BMI<30, n=1 BMI>=30 kg/m2).
The device performance and benefits will be ascertained once the scanning session for each block is complete by use of a structured questionnaire.
Data collection
- Participants and trainees will be asked to complete a structured questionnaire to assess the device performance and clinical benefits at the end of scanning for the block.
Data analysis:
The collected data and overall performance and benefits of ScanNav Anatomy PNB will be evaluated and summarized by presence and absence of ScanNav Anatomy PNB assistance, trainee and stratified by low/high BMI model.
Independent expert evaluation
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Participant | All 15 participants must be anesthesiologists who are competent to perform UGRA independently. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified and licensed Medical Doctor. |
| |
| Trainee | All 15 trainees must be healthcare practitioners who are licensed to perform UGRA. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified health practitioner |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Ultrasound scanning | Device | All participants will scan with and without device and trainee on 4 models. The order of the device assistance and models will be randomized between participants, but participant will always have exposure to device first before supervising the trainee. |
| Measure | Description | Time Frame |
|---|---|---|
| Obtaining the correct ultrasound view | Number of participants obtaining the correct ultrasound view [majority view, at least 8/15 participants in agreement] | 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Identifying anatomical structures | Number of participants identifying the correct anatomical structures in adult patients up to BMI 35 kg/m2 [majority view, at least 8/15 participants in agreement] | 6 months |
| Effect of supervision in anatomical structure identification |
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Participant Inclusion criteria
Participant exclusion criteria
Trainee Inclusion criteria
Trainee exclusion criteria
Models Inclusion Criteria
Model Exclusion Criteria
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Participants All participants must be anesthesiologists who are competent to perform UGRA independently. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified and licensed Medical Doctor.
Trainees All trainees must be healthcare practitioners who are licensed to perform UGRA. In order to be eligible for the study, participants must be a U.S. board-eligible/board-certified health practitioner.
Models 4 models will be selected carefully based on their BMI inclusion criteria.
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| Name | Affiliation | Role |
|---|---|---|
| Glenn Woodworth, MD | Oregon Health and Science University | Principal Investigator |
| James Bowness, MD | University of Oxford & Royal Gwent Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Oregon Health & Science University | Portland | Oregon | 97239 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35091395 | Derived | Bowness JS, El-Boghdadly K, Woodworth G, Noble JA, Higham H, Burckett-St Laurent D. Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia. Reg Anesth Pain Med. 2022 Jun;47(6):375-379. doi: 10.1136/rapm-2021-103368. Epub 2022 Jan 28. |
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|
Number of participants identifying the correct anatomical structures while being supervised in UGRA scanning [majority view, at least 8/15 participants in agreement] |
| 6 months |
| Measuring operator confidence | Number of participants with improved confidence [majority view, at least 8/15 participants in agreement] | 6 months |
| Number of errors in anatomy recognition by participants | Number of errors in anatomy recognition by participants [per class of safety critical structure, for all models] | 6 months |
| ID | Term |
|---|---|
| D014463 | Ultrasonography |
| ID | Term |
|---|---|
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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