138 Y. El Dsouki and I. Condello: J Extra Corpor Technol 2025, 57, 137--146
in cardiac surgery, emphasizing the crucial role of technology in advancing medical practice and patient care.
Materials and methods
A narrative review was conducted to support the development of the proposed algorithm. We searched PubMed with Boolean combinations of terms:“ Oxygen Delivery,”“ Cardiopulmonary Bypass,”“ Temperature Management,”“ Automated Systems,” and“ Patient Safety.” The initial search yielded 152 articles. After screening abstracts and full texts using predefined inclusion criteria, 34 articles were shortlisted. A final selection of 12 core studies was made. A PRISMA-style flowchart illustrating the study selection process is shown in Figure 1.
Inclusion criteria
Peer-reviewed articles on CPB temperature management and automation.
Studies highlight the impact of automated systems on patient safety and procedure efficacy.
Exclusion criteria
Non-English articles.
Irrelevant topics outside the automated systems in CPB.
Figure 1. PRISMA flow chart.
Oxygen Delivery( DO 2) Targets: These are set according to the metabolic demands adjusted for temperature, crucial for supporting organ function under varying thermal conditions [ 9, 10 ].
Cooling and Warming Rate Limits: Predefined limits ensure that temperature changes occur within safe gradients to prevent thermal shock and other temperaturerelated complications. 2. Automated cooling protocol
Selection of literature
Twelve principal articles were identified, aligning closely with our algorithm’ s focus areas and the goals of enhancing CPB through automation.
Ethical considerations
Although IRB approval is not applicable, the manuscript discusses the ethical implications of automation, including human oversight, accountability, training, and alarm fatigue. Future work should include input from clinicians and ethicists.
Algorithm design
The algorithm orchestrates a series of steps designed to maintain optimal thermal conditions, based on dynamic input parameters and controlled feedback mechanisms( Figure 1).
1. Input parameters
Target Core Temperature: Defined by the perfusionist based on specific surgical requirements, ensuring the algorithm adapts to the varying needs of each procedure.
Initial Patient Temperature: Measurements are taken from multiple sites( arterial, venous, esophageal, nasopharyngeal, bladder) to establish a comprehensive baseline before initiating temperature control [ 7, 8 ].
Initiate cooling when the target temperature is below a predefined threshold( e. g., 32 ° C), controlling the rate based on the initial and target temperatures over the specified time periods [ 11 ].
Dynamically adjust HCU settings to modulate the temperature, ensuring efficient cooling while maintaining safe temperature gradients( DT) between blood and HCU.
Continuous monitoring of peripheral temperatures to ensure uniform cooling across all body areas [ 12 ].
Adapt flow rates and oxygen delivery in response to lowered metabolic demands during cooling, choosing between pH-stat and alpha-stat strategies as per institutional protocols( Figure 2) [ 1, 2 ].
3. Monitoring phase
Real-time monitoring of arterial, venous, and core temperatures, along with the efficiency of the heat exchange system [ 4, 5 ].
Maintain metabolic support by balancing DO 2 and consumption( VO 2) and monitor CO 2 production to prevent acidosis.
4. Automated rewarming protocol
Gradually rewarm the patient once surgical conditions permit, using controlled HCU temperature settings calculated to prevent rapid temperature increases.