Experimentally induced pain and paresthesia respond differently to parameter changes of cuff-based compression in...

Neuropathic pain is a significant therapeutic challenge due to the co-occurrence with other neurological symptoms such as paresthesia. Human-based models such as cuff algometry can enhance our understanding of pain-paresthesia relationships. This experiment aimed to characterize (psychophysically) pain and paresthesia evoked by stimuli of different temporal and intensity parameters and to demonstrate the reliability of experimental induction of these two symptoms using cuff algometry. Forty participants, aged 18-35, were exposed to mechanical pressure stimuli at three intensities (100, 150, 200 mmHg) and three durations (90, 120, 150 s). Skin Conductance (SC) was continuously monitored, and participants rated pain and paresthesia in real-time using a computerized visual analog scale. The General Linear Model analysis revealed significant differences in paresthesia across all durations (p<0.01), but not all intensities, as paresthesia did not increase from 150 to 200 mmHg (p>0.05). Conversely, pain responses showed significant differences across all pressure intensities (p<0.05) but not durations, as pain did not increase from 90 to 120 and from 120 to 150 s (p>0.05). No interaction effects were found for either symptom. SC analysis showed no significant main or interaction effects. Intraclass correlation coefficients (ICCs) indicated moderate to excellent reliability for pain and paresthesia induction across different durations and intensities (ICC: 0.51-0.91), while SC showed poor to good reliability (ICC: 0.17-0.79). In conclusion, computerized cuff algometry seems to be an effective and reliable method for simultaneously inducing and assessing pain and paresthesia, revealing that these symptoms follow different patterns based on pressure duration and intensity. PERSPECTIVE: This study demonstrates that pain and paresthesia respond differently to varying intensities and durations of mechanical pressure, revealing their distinct psychophysical characteristics. This model can advance the understanding of neuropathic conditions and aid the development of more targeted therapeutic approaches for both pain and paresthesia.