• Br J Anaesth · Mar 2004

    Model to describe the degree of twitch potentiation during neuromuscular monitoring.

    • D J Eleveld, A F Kopman, J H Proost, and J M K H Wierda.
    • Research Group for Experimental Anesthesiology and Clinical Pharmacology, PO Box 30001, 9700 RB Groningen, The Netherlands. d.j.eleveld@anest.azg.nl
    • Br J Anaesth. 2004 Mar 1;92(3):373-80.

    BackgroundNeuromuscular block is estimated by comparing the evoked peak twitch with a control value measured in the absence of neuromuscular block. In practice, this control value is often difficult to determine because repeated motor nerve stimulation enhances the evoked mechanical response of the corresponding muscle, resulting in an increased twitch response. This is known as twitch potentiation or the staircase phenomenon. It is probably the result of myosin light chain phosphorylation creating an increased twitch force for a given amount of Ca(2+) released at each action potential. Modelling of potentiation may improve studies of neuromuscular blocking agents using mechanomyography or accelerometry.MethodsWe used one- and two-exponential models to describe the degree of myosin light chain phosphorylation and associated twitch potentiation. These models were fitted to accelerographic twitch force measurements for various stimulation patterns and frequencies used in neuromuscular monitoring.ResultsFitting a two-exponential model to twitch data for various stimulation rates and patterns provides better prediction than a one-exponential model. A one-exponential model performs poorly when the stimulation rate varies during measurement.ConclusionsWe conclude that a two-exponential model can predict the degree of twitch potentiation for the stimulation patterns and frequencies tested more accurately than a one-exponential model. However, if only one stimulation frequency is used, a one-exponential model can provide good accuracy. We illustrate that such a potentiation model can improve the ability of pharmacodynamic-pharmacokinetic neuromuscular block models to predict twitch response in the presence of a neuromuscular blocking agent.

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