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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., (Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: To reanalyze scoring criteria for automatic detection of nociceptive flexion reflexes (NFRs) in electromyography (EMG) recordings and to improve detection accuracy by accounting for multiple characteristics of the recordings, such as baseline noise level or sampling rate., Methods: Single scoring criteria for the NFR were reanalyzed and validated against an independent data set. To account for influences on the single scoring criteria, such as the baseline noise, multivariate classification models were derived., Results: Reanalysis of single scoring criteria yielded significantly lower threshold values than previously reported. The threshold value of the best-performing single scoring criterion, the NFR Interval Peak z score, was found to be strongly dependent on the level of baseline noise and the EMG sampling rate. Multivariate classification models could reduce the number of incorrectly classified recordings in an independent data set by 25% to 37% compared with the best-performing single scoring criterion., Discussion: The automatic detection of reflex responses in electromyograms can be significantly improved by including multiple reflex, baseline, and EMG characteristics into a classification model. These findings should help to improve the accuracy of currently used standard measurement algorithms and algorithms engineered toward specific properties, such as short measurements or less induced pain for the patients.

The nociceptive flexion reflex (NFR) is a widely used tool to investigate spinal nociception for scientific and diagnostic purposes, but its clinical use is currently limited due to the painful measurement procedure, especially restricting its applicability for patients suffering from chronic pain disorders. Here we introduce a less painful algorithm to assess the NFR threshold. Application of this new algorithm leads to a reduction of subjective pain ratings by over 30% compared to the standard algorithm. We show that the reflex threshold estimates resulting from application of the new algorithm can be used interchangeably with those of the standard algorithm after adjusting for the constant difference between the algorithms. Furthermore, we show that the new algorithm can be applied at shorter interstimulus intervals than are commonly used with the standard algorithm, since reflex threshold values remain unchanged and no habituation effects occur when reducing the interstimulus interval for the new algorithm down to 3s. Finally we demonstrate the utility of the new algorithm to investigate the modulation of nociception through different states of attention. Taken together, the here presented new algorithm could increase the utility of the NFR for investigation of nociception in subjects who were previously not able to endure the measurement procedure, such as chronic pain patients., (Copyright © 2015 Elsevier B.V. All rights reserved.)

AbstractObjectivesMethodsResultsConclusionThe nociceptive flexion reflex (NFR) and its threshold are frequently used to investigate spinal nociception in humans. Since this threshold (NFRT) is a probabilistic measure, specific algorithms are used for NFRT estimation based on the stochastic occurrence of reflexes at different stimulus intensities. We used a validated simulation model of the NFR to investigate the amount of NFRT measurement variability induced by different estimation algorithms in a steady setting of reduced external influences.We simulated the behavior of different estimation algorithms in subjects with an artificially steady baseline NFRT variability (standard deviation: 0 mA) or low baseline NFRT variability (standard deviation: 0.156 mA), equaling a quiet experimental setting. The obtained data were analyzed for NFRT measurement variability caused by the algorithms compared to the baseline variability reflecting other physiological influences.The standard deviation of the NFRT estimated by the different algorithms ranged between 0.381 and 3.464 mA with 96.8% to 99.6% of the measurement variability attributed to the algorithm used. Out of the investigated algorithms the dynamic staircase algorithm was most precise.The NFRT measurement variability observed during quiet and steady experimental sessions is mostly caused by the properties of the estimation algorithms, due to the probabilistic nature of the reflex occurrence. Our results give reference for choosing the optimal estimation algorithm to improve measurement precision. [ABSTRACT FROM AUTHOR]

Drug-induced unconsciousness is an essential component of general anesthesia, commonly attributed to attenuation of higher-order processing of external stimuli and a resulting loss of information integration capabilities of the brain. In this study, we investigated how the hypnotic drug propofol at doses comparable to those in clinical practice influences the processing of somatosensory stimuli in the spinal cord and in primary and higher-order cortices. Using nociceptive reflexes, somatosensory evoked potentials and functional magnet resonance imaging (fMRI), we found that propofol abolishes the processing of innocuous and moderate noxious stimuli at low to medium concentration levels, but that intense noxious stimuli evoked spinal and cerebral responses even during deep propofol anesthesia that caused profound electroencephalogram (EEG) burst suppression. While nociceptive reflexes and somatosensory potentials were affected only in a minor way by further increasing doses of propofol after the loss of consciousness, fMRI showed that increasing propofol concentration abolished processing of intense noxious stimuli in the insula and secondary somatosensory cortex and vastly increased processing in the frontal cortex. As the fMRI functional connectivity showed congruent changes with increasing doses of propofol – namely the temporal brain areas decreasing their connectivity with the bilateral pre-/postcentral gyri and the supplementary motor area, while connectivity of the latter with frontal areas is increased – we conclude that the changes in processing of noxious stimuli during propofol anesthesia might be related to changes in functional connectivity. [ABSTRACT FROM AUTHOR]

Background: Monitoring of pain and nociception in critical care patients unable to self-report pain remains a challenge, as clinical signs are neither sensitive nor specific. Available technical approaches are limited by various constraints. We investigated the electroencephalogram (EEG) for correlates that precede or coincide with behavioural nociceptive responses to noxious stimulation.Methods: In this retrospective study, we analysed frontal EEG recordings of 64 critical care patients who were tracheally intubated and ventilated before, during, and after tracheal suctioning. We investigated EEG power bands for correlates preceding or coinciding with behavioural responses (Behavioural Pain Scale ≥7). We applied the Mann-Whitney U-test to calculate corresponding P-values.Results: Strong behavioural responses were preceded by higher normalised power in the 2.5-5 Hz band (+17.1%; P<0.001) and lower normalised power in the 0.1-1.5 Hz band (-10.5%; P=0.029). After the intervention, strong behavioural responses were associated with higher normalised EEG power in the 2.5-5 Hz band (+16.6%; P=0.021) and lower normalised power in the 8-12 Hz band (-51.2%; P=0.037) CONCLUSIONS: We observed correlates in EEG band power that precede and coincide with behavioural responses to noxious stimulation. Based on previous findings, some of the power bands could be linked to processing of nociception, arousal, or sedation effects. The power bands more closely related to nociception and arousal could be used to improve monitoring of nociception and to optimise analgesic management in critical care patients.Clinical Trial Registration: DRKS00011206. [ABSTRACT FROM AUTHOR]