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Differentiating between heat pain intensities: The combined effect of multiple autonomic parameters

Treister, Roia,b,*,1; Kliger, Markc,1; Zuckerman, Galitc; Aryeh, Itay Goorc,d; Eisenberg, Elona,b

doi: 10.1016/j.pain.2012.04.008

Summary Autonomic parameters differentiate between the presence and absence of pain; yet, their linear combination discriminates between pain intensities better than each parameter alone.

Although it is well known that pain induces changes in autonomic parameters, the extent to which these changes correlate with the experience of pain is under debate. The aim of the present study was to compare a combination of multiple autonomic parameters and each parameter alone in their ability to differentiate among 4 categories of pain intensity. Tonic heat stimuli (1 minute) were individually adjusted to induce no pain, low, medium, and high pain in 45 healthy volunteers. Electrocardiogram, photoplethysmogram, and galvanic skin response were recorded, and the following parameters were calculated: heart rate; heart rate variability—high frequency (0.15 to 0.4 Hz) spectral power; skin conductance level; number of skin conduction fluctuations; and photoplethysmographic pulse wave amplitude. A combination of parameters was created by fitting an ordinal cumulative logit model to the data and using linear coefficients of the model. Friedman test with post-hoc Wilcoxon test were used to compare between pain intensity categories for every parameter alone and for their linear combination. All of the parameters successfully differentiated between no pain and all other pain categories. However, none of the parameters differentiated between all 3 pain categories (i.e., low and medium; medium and high; low and high). In contrast, the linear combination of parameters significantly differentiated not only between pain and no pain, but also between all pain categories (P < .001 to .02). These results suggest that multiparameter approaches should be further investigated to make progress toward reliable autonomic-based pain assessment.

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

aThe Rappaport Faculty of Medicine, Technion–Israel Institute of Technology, Haifa, Israel

bInstitute of Pain Medicine, Rambam Health Care Campus, Haifa, Israel

cMedasense Biometrics Ltd., Ofakim, Israel

dPain Management Center, Sheba Medical Center, Tel Hashomer, Israel

*Corresponding author at: Pain Relief Unit, Rambam Medical Center, P.O.B. 9602, Haifa 31096, Israel. Tel.: +972 4 8542578; fax: +972 4 8542880.


1These authors contributed equally to this work.

Article history: Received 25 January 2012; Received in revised form 29 March 2012; Accepted 9 April 2012.

© 2012 Lippincott Williams & Wilkins, Inc.
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