Although significant progress has been made in recent years in the field of pain modulation, information regarding patients' pain modulation profiles remains largely research-bound and is not yet easily accessible in clinical settings. The aim of this study was to develop and validate a model for estimating pain modulation profiles - including temporal summation of pain (TSP) and conditioned pain modulation (CPM) - using easily accessible measures. This study included 347 pain-free individuals and 108 with chronic pain. TSP was induced via tonic heat pain stimulations, while CPM was evaluated using pressure pain thresholds (CPM-PPT) and tonic heat pain stimulations (CPM-HPS) as test stimuli, with the cold pressor test as the conditioning stimulus. Independent variables included demographic, psychological, and physiological measures. A LASSO regression with cross-validation was used to identify key independent. For TSP, the model explained 40% of the variance, incorporating factors such as monoamines and blood pressure. For CPM, the CPM-HPS model performed best, accounting for 35% of the variance, with blood pressure, sex and pain catastrophizing identified as important predictors. Overall, these results indicate that TSP and CPM can be partially estimated using readily accessible measures, but high prediction error currently limits their clinical applicability.
Vincenot et al. (Thu,) studied this question.
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