Development, validation and utility of a simulation model of the nociceptive flexion reflex threshold. Issue 3 (March 2018)

• Record Type: Journal Article
• Authors: Jurth, Carlo; Dörig, Teresa M.; Lichtner, Gregor; Golebiewski, Anna; Jakuscheit, Axel; von Dincklage, Falk
• Is Part Of: Clinical neurophysiology. Volume 129:Issue 3(2018:Mar.)
• Page Start: 572
• Page End: 583
• Publication Date: 2018-03
• Subjects: NFR nociceptive flexion reflex -- NFRT nociceptive flexion reflex threshold -- SRP stimulus reflex probability; Nociceptive flexion reflex -- Reflex threshold -- Computer simulation -- NFR -- Pain measurement; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2017.11.030
• Languages: English
• ISSNs: 1388-2457

Abstract

Highlights: The simulation is a valid tool to measure NFRT estimation algorithms' accuracies. The accuracy of NFRT estimation algorithms depends on the NFRT variability. The dynamic staircase algorithm is the most precise NFRT estimation algorithm. Abstract: Objective: A variety of algorithms is used for nociceptive flexion reflex threshold (NFRT) estimation, but their estimation accuracy is unknown. We developed a computer based simulation model of the NFRT to quantify and compare the accuracy of available estimation algorithms. Methods: This simulation model is based on basic characteristics of the NFRT and specified by data collected from 60 healthy volunteers. We validated the model by comparing simulated data with data obtained independently in another volunteer population. The model was used to quantify the accuracy of previously published NFRT estimation algorithm for three NFRT variabilities representing sensory deprivation, distraction and general anaesthesia. Results: The dynamic staircase algorithm obtained most accurate NFRT estimates during all NFRT variabilities. The number of stimuli applied can be chosen higher to increase estimate precision or lower to reduce measurement time. Conclusions: Our simulation model is a valid tool to measure the accuracy of NFRT estimation algorithms. It can be applied to analyse and develop algorithms. The dynamic staircase algorithm shows the highest precision in NFRT estimation and is recommended for NFRT studies. Significance: Using optimized NFRT estimation algorithms increases precision in clinical and experimental NFRT studies and might therefore reduce the measurement effort necessary.