Literature DB >> 22497725

CYP2D6 poor metabolizer genotype and smoking predict severe postoperative pain in female patients on arrival to the recovery room.

Zongqi Yang1, Zhe Yang, Kristopher L Arheart, Richard Morris, Yanping Zhang, Yiliam Rodriguez, Chunyu Song, Melvin C Gitlin, Keith A Candiotti.   

Abstract

UNLABELLED: Recent studies have shown that CYP2D6 acts at critical steps for endogenous morphine biosynthesis. The present study assessed the contribution of CYP2D6 genetic polymorphisms, smoking, and other factors on acute severe postoperative pain (linear analog pain scores ≥8).
METHODS: Two hundred thirty-six female patients were found to have adequate information in a previously developed female surgical patient database to be included in this current analysis. Multiple logistic regression analysis was used to assess the predictors for acute severe postoperative pain. DNA had been previously extracted from blood samples in all patients and was genotyped by the Amplichip to determine the specific CYP2D6 genotypes.
RESULTS: It was noted that the incidence of acute severe postoperative pain (linear analog pain scores ≥8) was more frequent in patients with the CYP2D6 poor metabolizer (PM) genotype, 71%, compared with 28% in intermediate metabolizers (IMs), 26% in extensive metabolizers (EMs), and 27% in ultrarapid metabolizers (UMs). The overall association between metabolizer groups and severe postoperative pain was significant (P=0.023). PMs were significantly more likely to suffer from severe postoperative pain than IMs, EMs, and UMs (P=0.007, 0.002, and 0.050, respectively). There were no significant differences among IMs, EMs, and UMs. Additionally, it was noted that there was an increased frequency of acute severe postoperative pain in smokers vs nonsmokers (P=0.014).
CONCLUSION: This study demonstrated that female patients possessing the PM genotype of CYP2D6 and patients who smoke had a higher incidence of acute severe postoperative pain. Wiley Periodicals, Inc.

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Year:  2012        PMID: 22497725     DOI: 10.1111/j.1526-4637.2012.01296.x

Source DB:  PubMed          Journal:  Pain Med        ISSN: 1526-2375            Impact factor:   3.750


  10 in total

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6.  The ACTTION-APS-AAPM Pain Taxonomy (AAAPT) Multidimensional Approach to Classifying Acute Pain Conditions.

Authors:  Michael L Kent; Patrick J Tighe; Inna Belfer; Timothy J Brennan; Stephen Bruehl; Chad M Brummett; Chester C Buckenmaier; Asokumar Buvanendran; Robert I Cohen; Paul Desjardins; David Edwards; Roger Fillingim; Jennifer Gewandter; Debra B Gordon; Robert W Hurley; Henrik Kehlet; John D Loeser; Sean Mackey; Samuel A McLean; Rosemary Polomano; Siamak Rahman; Srinivasa Raja; Michael Rowbotham; Santhanam Suresh; Bernard Schachtel; Kristin Schreiber; Mark Schumacher; Brett Stacey; Steven Stanos; Knox Todd; Dennis C Turk; Steven J Weisman; Christopher Wu; Daniel B Carr; Robert H Dworkin; Gregory Terman
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  10 in total

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