A novel ultrasound-based vein visualization technology can better detect optimal peripheral veins when compared to...

Peripheral intravenous catheter (PIVC) failure prior to therapy completion is a major issue. Technology to identify more suitable veins for cannulation is essential to improve successful insertion and reduce post-insertion complications and avoidable costs.

The experimental study was designed to compare vessel selection for cannulation when using a novel ultrasound-based vein visualization prototype versus traditional landmark technique.

Three clinicians competent in cannulation (CCC) used landmark technique to select and mark a vein indicated for short peripheral catheter (SPC) placement on each arm of the 12 patients recruited (24 arms). This process was repeated using the vein visualization prototype. A blinded Vascular Access Specialist (VAS) evaluated each marked site using ultrasound (GE Logiq S7). Vessel cannulation suitability was rated on a 5-point Likert (⩾3 considered suitable). Ethics approval was obtained (SMHS HREC RGS0000006930).

Landmark-selected veins were deemed suitable less often (52.2% vs 78.3%; p = 0.08) than prototype-selected veins and had lower average suitability scores (2.57 vs 3.22; p = 0.03). Landmark technique selected veins from various sites: hand (4.3%), wrist (17.4%), mid-forearm (73.9%), and antecubital fossa (4.3%), whereas the prototype predominantly selected mid-forearm veins (95.7%). Landmark-selected veins were significantly shallower (1.83 mm vs 2.61 mm; p = 0.03) than prototype-selected veins, however the diameter of these veins were not significantly different between the two techniques (2.20 mm vs 2.72 mm; p = 0.05). Both techniques detected veins with 95.8% sensitivity.

The prototype outperformed the landmark technique by visualizing non-palpable, non-visible vessels. The veins identified were larger and optimally located in the mid-forearm, both attributes linked to fewer complications and improved first-time insertion success. Future prototype refinement will include ergonomic improvements and clinical data to enhance performance.