Journal
CHINESE MEDICAL JOURNAL
Volume 130, Issue 16, Pages 1926-1931Publisher
MEDKNOW PUBLICATIONS & MEDIA PVT LTD
DOI: 10.4103/0366-6999.211878
Keywords
Electroencephalogram; Pain; Wavelet Algorithm
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Background: The current pain assessment methods are strongly subjective and easily affected by outside influences, and there is an urgent need to develop a reliable objective and quantitative pain-monitoring indicator. The aim of this study was to evaluate the feasibility of using Pain index (Pi) to assess pain symptoms in pain patients. Methods: Subjects were enrolled from patients seeking treatment at Pain Medicine Center of China Medical University Aviation General Hospital from October 2015 to December 2016, such as postherpetic neuralgia, spinal cord injury, femoral head necrosis, lumbar disc herniation, trigeminal neuralgia, complex regional pain syndrome, perineal pain, phantom limb pain, etc., (pain group, n = 111), as well as healthy volunteers without subjective pain (control group, n = 100). The subjective pain symptoms in pain patients were evaluated by Pi and visual analogue scale/numerical rating scales (VAS/NRS), respectively, and the relationship between them was analyzed using single factor correlation analysis and multiple factor regression analysis. Results: Pi levels in the pain group were significantly higher than those of the control group (t = 6.273, P< 0.001), the correlation analysis of Pi and VAS/NRS score in the pain group showed that the Pearson correlation coefficient was 0.797 (P < 0.001); After adjusted for types of pain, pain sites, medication, gender, and age, Pi was found to be independently correlated to VAS/NRS score (P < 0.001). Conclusions: Pi significantly correlates with VAS/NRS score, might be used to evaluate the subjective pain symptoms in patients and has good research and application value as an objective pain assessment tool.
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