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Patient hydration: a major source of laboratory uncertainty.

作者信息

Ritchie Robert F, Ledue Thomas B, Craig Wendy Y

机构信息

Foundation for Blood Research, Scarborough, ME 04070-0190, USA.

出版信息

Clin Chem Lab Med. 2007;45(2):158-66. doi: 10.1515/CCLM.2007.052.

Abstract

Movement of body water from compartment to compartment during any time period is attributable to forces active within and upon each space. The result of these forces leads to transfer of water between intravascular and extravascular compartments, as well as shifts between extracellular and intracellular spaces. The importance of these shifts and of the associated mechanism was described by Ernest Starling in 1896 in very much the same manner as it is viewed today. The end result of fluid transfer and its physiological and laboratory consequences has not been fully appreciated. Despite awareness that fluid shifts can affect laboratory analytical results, little recent investigation has addressed the problem in the routine clinical laboratory. Thus, the potential for significant misinterpretation remains. For example, it is known that individual laboratory test values can vary widely, depending on many factors including the subject's posture during and immediately before phlebotomy, leading to significant changes in the interpretation of blood analyte values. Furthermore, a variety of ubiquitous environmental effects have additional impact on fluid distribution and thus on test values. In other words, patient hydration status is a major pre-analytical variable that needs to be addressed by the clinical laboratory. The need to adjust data for patient hydration status is especially important in the case of colloid analytes for which the dynamic range includes a narrow "gray zone" where hydration changes of a few percentage points can change the clinical implications. The crucial importance of this adjustment is underscored by the fact that neither the testing laboratory nor the clinician are aware of this unseen circumstance and are thus compelled to work with data that do not necessarily reflect the clinical situation.

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