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Predicted pain in pediatric surgical procedures

R. Manworren,A. Pantaleao,R. Bradshaw,M. Lee, J. Thomson,C. Rader,M. Misra, R. Weiss, A. Tsai, G. Ruano

The Journal of Pain(2015)

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摘要
Efforts to identify predictors of children’s post-surgical pain and effectiveness of therapeutic interventions has been limited by documentation available from retrospective chart reviews. The purpose of this study was to advance our understanding of predictors of acute post-surgical pain and transition to persistent pain in children. Pre-operatively, patients and their parents were asked to predict the severity of the patients’ pain after surgery on a 0-10 numeric rating scale. This score was compared to the patient’s mean reported pain scores during their first 72 hours of hospital stay as documented in the patient’s medical record. Patients underwent surgical correction (n=31) of pectus-excavatum by thorascopic approach (Nuss procedure) or adolescent idiopathic scoliosis with spinal fusion. Patients were primarily male (54.8%), Caucasian (80.6%), with mean age of 15.62 (σ= 2.57) years, and received spinal fusions (61.3%). Patients mean predicted pain score was 6.91 (σ= 1.65) with parents’ mean predicted pain score 8.07 (σ= 1.87). Using a paired samples t-test, we found there was a statistically significant difference between patients’ predicted pain scores and parents’ predicted pain scores (t= -3.15, p= 0.004). We also found there was a statistically significant difference between patients’ predicted pain scores and mean post-surgical pain scores (t= 8.77, p= 0.00), as well as parents’ predicted pain scores and mean post-surgical pain scores (t= 10.496, p= 0.00). Research by Logan & Rose (2005) suggested adolescents’ post-surgical pain may be interpreted as a self-fulfilling prophecy. We were unable to duplicate their results in this sample. Analysis of other potential predictors including pre-operative anxiety, pain catastrophizing, and genetic biomarkers for pain sensitivity and alterations in analgesic metabolism is necessary to develop a parsimonious predictive model of pediatric post-surgical pain.
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pain,procedures
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