AI-guided DVT Diagnosis in Primary Care
Author Information
Author(s): Kerstin Nothnagel, Alastair Hay, Jessica Watson, Jonathan Banks
Primary Institution: Bristol Medical School (PHS), Bristol, United Kingdom
Hypothesis
Can AI-guided point-of-care ultrasound (POCUS) accurately diagnose deep vein thrombosis (DVT) when performed by non-specialists in primary care?
Conclusion
The study will evaluate the accuracy and acceptability of AI-guided POCUS for DVT diagnosis in primary care settings.
Supporting Evidence
- The incidence of DVT is increasing as the global population ages.
- AI-guided POCUS could allow any healthcare professional to perform DVT scans.
- The study aims to assess the accuracy of AI-guided POCUS compared to standard ultrasound scans.
Takeaway
This study is looking at whether regular healthcare workers can use AI to help diagnose blood clots in people's legs, making it easier for patients to get checked without going to the hospital.
Methodology
The study will use a diagnostic test accuracy (DTA) approach and qualitative interviews to assess AI-guided POCUS in 500 individuals with suspected DVT.
Limitations
The study excludes housebound and frail patients and is conducted in a single geographical area, which may limit generalizability.
Participant Demographics
Participants will be recruited from primary care DVT clinics in the BNSSG region, with demographics such as age, sex, and postcode reported.
Statistical Information
Confidence Interval
95% confidence interval with a margin of error of ±5%
Digital Object Identifier (DOI)
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