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DOI 10.1016/j.jtbi.2011.09.016

Медицинская библиотека · Journal of theoretical biology · 2011

Evaluation of red blood cell labelling methods based on a statistical model for red blood cell survival.

Korell Julia, Coulter Carolyn V, Duffull Stephen B

Оценочное исследованиеСтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

The aim of this work is to compare different labelling methods that are commonly used to estimate the lifespan of red blood cells (RBCs), e.g. in anaemia of renal failure, where the effect of treatment with erythropoietin depends on the lifespan of RBCs. A previously developed model for the survival time of RBCs that accounts for plausible physiological processes of RBC destruction was used to simulate ideal random and cohort labelling methods for RBCs, as well as the flaws associated with these methods (e.g. reuse of label and loss of the label from the surviving RBCs). Random labelling with radioactive chromium and cohort labelling using heavy nitrogen were considered. Blood sampling times were determined for RBC survival studies using both labelling methods by applying the theory of optimal design. It was assessed whether the underlying parameter values of the model are estimable from these studies, and the precision of the parameter estimates were calculated. In theory, parameter estimation would be possible for both types of ideal labelling methods without flaws. However, flaws associated with random labelling are significant and not all parameters controlling RBC survival in the model can be estimated with good precision. In contrast, cohort labelling shows good precision in the parameter estimates even in the presence of reuse and prolonged incorporation of the label. A model based analysis of RBC survival studies is recommended in future to account for limitations in methodology as well as likely causes of RBC destruction.

Для цитирования: Korell Julia, Coulter Carolyn V, Duffull Stephen B. Evaluation of red blood cell labelling methods based on a statistical model for red blood cell survival.. Journal of theoretical biology. 2011. DOI: 10.1016/j.jtbi.2011.09.016.

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