Temporal summation of second pain: Variability in responses to a fixed protocol

Authors


  • Funding sources

    This work was supported by grants from the National Institutes of Health to Dr. Robinson (R01 DE013208), to Dr. George (AT002796), and to Dr. Bishop (AR54331-4). Support provided to Dr. Bialosky by the National Institutes of Health T-32 Neural Plasticity Research Training Fellowship (T32HD043730).

  • Conflicts of interest

    Authors have no conflicts of interest to declare.

Correspondence

Michael E. Robinson

E-mail: merobin@phhp.ufl.edu

Abstract

Background

Temporal summation of second pain (TSSP) is relevant for the study of central sensitization, and refers to increased pain evoked by repetitive stimuli at a constant intensity. While the literature reports on participants whose pain ratings increase with successive stimuli, response to a TSSP protocol can be variable. The aim of this study was to characterize the full range of responses to a TSSP protocol in pain-free adults.

Method

Three hundred twelve adults received a train of brief, repetitive heat stimuli at a fixed temperature and rated the intensity of second pain after each pulse. TSSP response (Δ in pain ratings) was quantified using the most common methods in the literature, and response groups were formed: TSSP (Δ > 0), no change (Δ = 0), and temporal decrease in second pain (TDSP) (Δ < 0). A cluster analysis was performed on the Δ values to empirically derive response groups.

Results

Depending on how TSSP response was quantified, 61–72% of the sample demonstrated TSSP, 11–28% had no change in pain ratings and 0–20% demonstrated TDSP. The cluster analysis found that the majority (59%) of participants fell in the no change cluster, 29% clustered into the TSSP group and 12% in the TDSP cluster.

Conclusions

Using a fixed thermal paradigm, pain-free adults exhibit substantial variability in response to a TSSP protocol not well characterized by group-mean slopes. Studies are needed to determine TSSP response patterns in clinical samples, identify predictors of response and determine the clinical implications of response variability.

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