A Temperature-Adjusted Algorithm for Predicting Critical Indexed Oxygen Delivery (DO₂i) During Cardiopulmonary Bypass

Indexed oxygen delivery (DO₂i) is a critical parameter in cardiopulmonary bypass (CPB) management. Traditional goal-directed perfusion (GDP) protocols use fixed DO₂i thresholds, typically derived from normothermic conditions. However, these static values do not account for the temperature-dependent reduction in metabolic rate during hypothermia, potentially leading to perfusion mismatches.

This work presents a temperature-adjusted DO₂i (taDO₂i) algorithm designed to adapt oxygen delivery targets during CPB dynamically. The model is grounded in established physiological principles describing the effect of temperature on oxygen consumption. A quadratic regression approach was used to synthesize this behavior into a continuous function, which incorporates core temperature and body surface area (BSA) to provide individualized DO₂i targets.

The taDO₂i model closely aligns with known physiological behavior across a range of temperatures. It reduces the risk of overperfusion during hypothermia and underperfusion during rewarming, offering more accurate perfusion guidance than linear approximations or fixed thresholds. The model is suitable for integration into perfusion software or electronic health records, allowing real-time application.

This temperature-adjusted algorithm provides a physiologically sound and computationally simple tool for optimizing oxygen delivery during CPB. It supports individualized perfusion management and represents a valuable evolution of current GDP strategies. Prospective clinical validation is recommended.