Literature DB >> 15179128

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

Alan B Marr1, Frederick A Moore, R Matthew Sailors, Alicia Valdivia, John H Selby, Rosemary A Kozar, Christine S Cocanour, Bruce A McKinley.   

Abstract

Preload-directed resuscitation is the standard of care in U.S. trauma centers. As part of our standardized protocol for traumatic shock resuscitation, patients who do not respond to initial interventions of hemoglobin replacement and fluid volume loading have optimal preload determined using a standardized algorithm to generate a "Starling curve." We retrospectively analyzed data from 147 consecutive resuscitation protocol patients during the 24 months ending August 2002. Fifty (34%) of these patients required preload optimization, of which the optimization algorithm was completed in 36 (72%). The average age of those who required preload optimization was 44 +/- 3 years vs. 34 +/- 1 years for patients who did not. Execution of the algorithm caused PCWP to increase from 18 +/- 1 mmHg to a maximum of 25 +/- 2 mmHg and CI to increase from 3.2 +/- 0.1 L/min m(-2) to 4.5 +/- 0.4 L/min m(-2). Algorithm logic determined PCWP = 24 +/- 2 to be optimal preload at the maximum CI = 4.8 +/- 0.4, and as the volume loading threshold for the remaining time of the resuscitation process. Starling curve preload optimization was begun 6.5 +/- 0.8 h after start of the resuscitation protocol and required 36 +/- 5 min and 4 +/- 0.4 fluid boluses (1.6 +/- 0.2 L). Comparison of early response of those patients who required preload optimization and those who did not indicated hemodynamic compromise apparent in the 1st 4 h of standardized resuscitation. We conclude that preload optimization using sequential fluid bolus and PCWP-CI measurement to generate a Starling curve is feasible during ICU shock resuscitation, but that there is the disadvantage that increasing and maintaining high PCWP may contribute to problematic tissue edema.

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Year:  2004        PMID: 15179128     DOI: 10.1097/00024382-200404000-00002

Source DB:  PubMed          Journal:  Shock        ISSN: 1073-2322            Impact factor:   3.454


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