Using Digital Biomarkers for Objective Assessment of Perfusionists' Workload and Acute Stress During Cardiac Surgery

A randomized controlled trial on evaluating clinician-supervised generative AI for decision support

BACKGROUND

The integration of generative artificial intelligence (AI) as clinical decision support systems (CDSS) into telemedicine presents a significant opportunity to enhance clinical outcomes, yet its application remains underexplored.

OBJECTIVE

This study investigates the efficacy of one of the most common generative AI tools, ChatGPT, for providing clinical guidance during cardiac arrest scenarios.

METHODS

We examined the performance, cognitive load, and trust associated with traditional methods (paper guide), autonomous ChatGPT, and clinician-supervised ChatGPT, where a clinician supervised the AI recommendations. Fifty-four subjects without medical backgrounds participated in randomized controlled trials, each assigned to one of three intervention groups: paper guide, ChatGPT, or supervised ChatGPT. Participants completed a standardized CPR scenario using an Augmented Reality (AR) headset, and performance, physiological, and self-reported metrics were recorded.

MAIN FINDINGS

Results indicate that the Supervised-ChatGPT group showed significantly higher decision accuracy compared to the paper guide and ChatGPT groups, although the scenario completion time was longer. Physiological data showed a reduced LF/HF ratio in the Supervised-ChatGPT group, suggesting potentially lower cognitive load. Trust in AI was also highest in the supervised condition. In one instance, ChatGPT suggested a risky option, highlighting the need for clinician supervision.

CONCLUSION

Our findings highlight the potential of supervised generative AI to enhance decision-making accuracy and user trust in emergency healthcare settings, despite trade-offs with response time. The study underscores the importance of clinician oversight and the need for further refinement of AI systems to improve safety. Future research should explore strategies to optimize AI supervision and assess the implementation of these systems in real-world clinical settings.

A novel multimodal, intraoperative cognitive workload assessment of cardiac surgery team members

OBJECTIVE

To characterize cognitive workload (CWL) of cardiac surgery team members in a real-world setting during coronary artery bypass grafting (CABG) surgery using providers' heart rate variability (HRV) data as a surrogate measure of CWL.

METHODS

HRV was collected from the surgeon, anesthesiologist, perfusionist, and scrub nurse, and audio/video recordings were made during isolated, nonemergency CABG surgeries (n = 27). Eight surgical phases were annotated by trained researchers, and HRV was calculated for each phase.

RESULTS

Significant differences in CWL were observed within a given role across surgical phases. Results are reported as predicted probability (95% confidence interval [CI]). CWL was significantly higher for anesthesiologists during "preparation and induction" (0.57; 95% CI, 0.42-0.71) and "anastomoses" (0.44; 95% CI, 0.30-0.58) compared to other phases, and the same held for nurses during the "opening" (0.51; 95% CI, 0.37-0.65) and "postoperative" (0.68; 95% CI, 0.42-0.86) phases. Additional significant differences were observed between roles within a given surgical phase. For example, surgeons had significantly higher CWL during "anastomoses" (0.81; 95% CI, 0.69-0.89) compared to all other phases, and the same was true of perfusionists during the "opening" (0.79; 95% CI, 0.66-0.88) and "prebypass preparation" (0.50; 95% CI, 0.36-0.64) phases.

CONCLUSIONS

Our innovative analysis demonstrates that CWL fluctuates across surgical procedures by role and phase, which may reflect the distribution of primary tasks. This corroborates earlier findings from self-report measures. The data suggest that team-wide, peak CWL during a phase decreases from early phases of surgery through initiation of cardiopumonary bypass (CPB), rises during anastomosis, and decreases after termination of CPB. Knowledge of these trends could encourage the adoption of behaviors to enhance team dynamics and performance.