| الوصف: |
Pernille Ravn,1 Rune Frederiksen,2 Anders P Skovsen,3 Lona L Christrup,1 Mads U Werner21Department of Drug Design and Pharmacology, University of Copenhagen, 2Multidisciplinary Pain Center, Neuroscience Center, Rigshospitalet, Copenhagen University Hospital, 3Department of Surgery, Koge Hospital, Copenhagen University Hospital, Copenhagen, DenmarkPurpose: The primary objective of the present study was to evaluate predictive parameters of the acute pain score during induction of an inflammatory heat injury.Patients and methods: Healthy volunteers (50 females/50 males) were included in the study. The predictive potential of gender, anthropometric (body surface area, body mass index), psychological (anxiety, depression, vulnerability), and psychophysical (quantitative sensory testing, conditioned pain modulation) variables in estimating the pain response to a validated heat injury (47°C, 7 minutes, area 12.5 cm2) were investigated. All assessments were made in duplicate sessions separated by 21 days (median).Results: There were three main findings in this study. First, a predictive model of pain sensitivity during the heat injury, including both genders and using multiple regression technique, could account for 28% of the variance (P < 0.0001), but gender-related differences in the final model could not be demonstrated. Second, the results confirmed significant gender-related differences in perception of electrical, pressure, and cold pressor stimuli (P < 0.002). Third, positive correlations between anthropometric data and pain perception during electrical and pressure stimuli were demonstrated (P < 0.001 and P < 0.005, respectively).Conclusion: The study demonstrated predictability of acute pain sensitivity, and although gender-related differences in pain perception were demonstrated, no gender-related differences in pain sensitivity could be shown. Interestingly, positive correlations between anthropometric data and pain perception were shown for the first time.Keywords: experimental pain, gender differences, healthy subjects, prediction, quantitative sensory testing |
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