Preload optimization using "starling curve" generation during shock resuscitation: can it be done?

Area of Science:

• Critical Care Medicine
• Trauma Surgery
• Cardiovascular Physiology

Background:

• Preload-directed resuscitation is standard in U.S. trauma centers.
• Patients unresponsive to initial shock treatment require further optimization.
• The Starling curve method assesses optimal preload using pulmonary capillary wedge pressure (PCWP) and cardiac index (CI).

Purpose of the Study:

• To evaluate the feasibility of preload optimization using a Starling curve algorithm in trauma resuscitation.
• To analyze patient demographics and resuscitation parameters associated with the need for preload optimization.

Main Methods:

• Retrospective analysis of 147 trauma patients undergoing a standardized resuscitation protocol.
• Application of a Starling curve algorithm involving sequential fluid boluses and PCWP-CI measurements.
• Data collected on patient age, resuscitation time, fluid administration, and hemodynamic parameters.

Main Results:

• 34% of patients required preload optimization; the algorithm was completed in 72% of these cases.
• Preload optimization increased PCWP from 18 to 25 mmHg and CI from 3.2 to 4.5 L/min m(-2).
• Optimal preload was determined at PCWP of 24 mmHg and CI of 4.8 L/min m(-2), requiring an average of 4 fluid boluses (1.6 L).

Conclusions:

• Starling curve-guided preload optimization is feasible in intensive care unit (ICU) shock resuscitation.
• Patients requiring optimization showed hemodynamic compromise earlier in resuscitation.
• A potential disadvantage is the risk of tissue edema due to elevated and maintained high PCWP.