Automated feedback in central venous catheterisation training

Central venous catheterisation (CVC) is a critical skill in medical practice for some specialties, specifically in fields like anaesthesiology, emergency medicine and intensive care, where CVC placement is commonly required. The study focused on addressing the challenges in learning central venous catheterisation, particularly in reducing learner discomfort and enhancing procedural efficiency. A significant barrier faced by learners is fear and lack of awareness regarding arterial puncture, a common complication during CVC. This fear can lead to increased anxiety and decreased confidence, ultimately hindering skill acquisition. Despite the advantages of simulation-based training, students often struggle with locating central veins due to unfamiliarity with proper needle handling and maintaining constant negative pressure. These challenges not only increase the time required to perform the procedure but also amplify the cognitive load on learners, further impacting their ability to master the technique.

To address these challenges, an automated feedback device, EpiFaith® CV, was introduced during CVC simulation training. This device, designed to automate aspiration and provide visual feedback for detecting pressures above 30 mmHg, aimed to mitigate the identified barriers. A cross-over randomised controlled trial involving 32 medical students during their anaesthesiology clinical rotation was conducted to evaluate the impact of this device on learning efficacy and confidence. Student satisfaction was measured using surveys administered before and after the training. These surveys used a Likert scale to capture self-reported comfort, familiarity and overall satisfaction with both the procedure and the devices used. Moreover, the time to locate veins and the total procedure time were recorded and analysed.

The introduction of automated-feedback syringe resulted in a noticeable decrease in student discomfort and a significant increase in both familiarity with and comfort during the procedure. Students reported higher satisfaction levels with the automated-feedback syringe compared with the traditional syringe. Notably, there was a trend toward reduction in the time required to locate veins and complete the procedure when using the automated-feedback device. Furthermore, students who initially used the automated-feedback syringe demonstrated improved efficiency with the conventional syringe subsequently, compared to those who started with the conventional syringe.

These findings suggest that the automated feedback device can enhance the CVC training experience for medical students, echoing its promising use in cardiopulmonary resuscitation training. In the CPR context, feedback devices like metronomes and systems such as Skillmeter Anne and Q-CPR have improved skills by providing real-time metrics on chest compression and ventilation. These devices have been tested in both training and clinical scenarios, demonstrating improvements in CPR skill acquisition and retention during CPR training and performance.¹ This study's preliminary results support the potential of the automated-feedback device to improve learning outcomes in medical education, particularly in procedural skill acquisition. Further investigation into clinical performance will be conducted to assess the effectiveness of the automated-feedback device in enhancing clinical skill acquisition and retention.

Maintaining sterile techniques during CVC is critical for preventing contamination and reducing infection risks. Sterile gloves, proper attire and adherence to aseptic principles are essential for preserving a sterile field during invasive procedures. While the video demonstrated the use of the automated-feedback device, the absence of sterile gloves was a deviation from clinical standards. Additionally, ultrasound guidance is crucial for minimising complications and ensuring accurate needle placement. Future training protocols should integrate both sterile technique and real-time ultrasound guidance to better reflect clinical practice standards.

Yun-Yi Tsai: Validation; visualization; investigation; data curation; conceptualization; methodology; writing – original draft. Chun-Hsien Fu: Validation; conceptualization. Hui-Hsun Huang: Supervision; resources. Kuang-Cheng Chan: Supervision; resources. Pei-Lin Lin: Supervision; resources. Man-Ling Wang: Conceptualization; methodology; funding acquisition; resources; formal analysis; project administration.

The authors declared there was no conflict of interest.