Why the study?
Does a linear combination of multiple autonomic parameters improve the ability to differentiate between heat pain intensities compared to individual parameters in healthy volunteers?
Does a linear combination of multiple autonomic parameters improve the ability to differentiate between heat pain intensities compared to individual parameters in healthy volunteers?
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A multiparameter approach combining autonomic responses can reliably differentiate between varying intensities of heat pain, outperforming single-parameter assessments.
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 (1minute) 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 0.4Hz) 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.
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Treister et al. (2012) studied this question.
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