Monitoring healthcare providers’ cognitive workload during surgical procedures can provide insight into the dynamic changes of mental states that may affect patient clinical outcomes. The role of cognitive factors influencing both technical and non-technical skill are increasingly being recognized, especially as the opportunities to unobtrusively collect accurate and sensitive data are improving. Applying sensors to capture these data in a complex real-world setting such as the cardiac surgery operating room, however, is accompanied by myriad social, physical, and procedural constraints. The goal of this study was to investigate the feasibility of overcoming logistical barriers in order to effectively collect multi-modal psychophysiological inputs via heart rate (HR) and near-infrared spectroscopy (NIRS) acquisition in the real-world setting of the operating room. The surgeon was outfitted with HR and NIRS sensors during aortic valve surgery, and validation analysis was performed to detect the influence of intra-operative events on cardiovascular and prefrontal cortex changes. Signals collected were significantly correlated and noted intra-operative events and subjective self-reports coincided with observable correlations among cardiovascular and cerebral activity across surgical phases. The primary novelty and contribution of this work is in demonstrating the feasibility of collecting continuous sensor data from a surgical team member in a real-world setting.

All eight filter coatings altered the blood components to varying degrees. Selection of the most effective filter, in conjunction with a heparin-bonded circuit for CPB, may decrease the intraoperative foreign-surface activation of blood cells.

Traditionally, blood flow rates on cardiopulmonary bypass are based primarily on a formula that matches cardiac index to the patient’s body surface area (BSA). However, Ranucci and associates in the Goal-Directed Perfusion Trial (GIFT) trial have shown that coupling the BSA with delivery of oxygen (DO2), known as goal-directed perfusion (GDP), may be a safer approach to determine appropriate blood flows. The objective of this study was to create a GDP reference tool that would allow perfusionists to quickly determine the lowest acceptable blood flow needed to provide a patient of any BSA with a satisfactory DO2 without the need for additional dedicated technology. We approached this problem by deriving a formula for flow (L/min), based on BSA, oxygen content of the blood, and a minimum DO2 of 280 mL·min−1m−2. A quick reference GDP chart was created based on the derived formula, requiring only the patient’s BSA and hemoglobin level to determine a safe minimum flow rate. The proposed tool allows any cardiac surgery center to adopt the GDP technique, even in the absence of instantaneous DO2 monitoring equipment.

No abstract

During cardiac surgery there is an unmet need for safe transfer of responsibility for patient oxygenation back and forth from the anesthesia to the perfusion teams. Prior to cardiopulmonary bypass (CPB), lung ventilation is performed by the anesthesia machine ventilator and is the responsibility of the anesthesia team. During CPB, lung ventilation is halted and oxygenation is performed by the CPB oxygenator and perfusion team This recurrent transfer throughout the procedure introduces the rare but serious possibility of a “never event”, resulting in the patient’s lungs not being ventilated upon stopping the CPB and potentially leading to catastrophic hypoxemia. Monitors and alarms on the anesthesia and bypass machines would not be useful when the other device is operating so they are routinely put into a standby mode until needed. Consequently, in the event that the handoff is missed, there are no alarms to catch the situation. To solve this unmet need, we propose a novel interoperable, context-aware system capable of detecting and acting if this rare situation occurs. Our system is built on the open-source OpenICE framework, allowing it to seamlessly work with a variety of ventilator and bypass machines.