Girish M Nair1, David H Birnie1, Glen L Sumner2, Andrew D Krahn3, Jeffrey S Healey4, Pablo B Nery1, Eli Kalfon5, Atul Verma6, Felix Ayala-Paredes7, Benoit Coutu8, Giuliano Becker9, François Philippon10, John Eikelboom4, Roopinder K Sandhu2, John Sapp11, Richard Leather12, Derek Yung12, Bernard Thibault13, Christopher S Simpson14, Kamran Ahmad15, Marcio Sturmer16, Katherine Kavanagh2, Eugene Crystal17, George A Wells1, Vidal Essebag16. 1. Arrhythmia Service, Division of Cardiology, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada. 2. Department of Medicine, University of Calgary, Libin Cardiovascular Institute, Calgary, AB, Canada. 3. Department of Medicine, University of British Columbia, Vancouver, BC, Canada. 4. Division of Cardiology, Department of Medicine, McMaster University, Hamilton Health Sciences, Population Health Research Institute, Hamilton, ON, Canada. 5. Department of Medicine, Galilee Medical Center, Nahariya, Israel. 6. Department of Medicine, Southlake Regional Health Center, University of Toronto, Toronto, ON, Canada. 7. Department of Medicine, Universite de Sherbrooke, Sherbrooke, QC, Canada. 8. Department of Medicine, Centre Hospitalier de l'Universite de Montreal, Hopital Hotel-Dieu, Montreal, QC, Canada. 9. Department of Medicine, McGill University Health Center, Montreal, QC, Canada. 10. Department of Medicine, Quebec Heart Institute, Sainte-Foy, QC, Canada. 11. Department of Medicine, QEII Health Sciences Centre, Halifax, Nova Scotia, Canada. 12. Scarborough Health Network, University of Toronto, Toronto, ON, Canada. 13. Division of Cardiology, Department of Medicine, Montreal Heart Institute Montreal, QC, Canada. 14. Department of Medicine, Queen's University, Kingston, ON, Canada. 15. Department of Medicine, University of Toronto, Toronto, ON, Canada. 16. Division of Cardiology, Department of Medicine, University of Calgary, Libin Cardiovascular Institute, Calgary, AB, Canada. 17. Department of Medicine, Sunnybrook Health Sciences Center, University of Toronto, Toronto, ON, Canada.
Abstract
AIMS: Post-operative pain following cardiac implantable electronic device (CIED) insertion is associated with patient dissatisfaction, emotional distress, and emergency department visits. We sought to identify factors associated with post-operative pain and develop a prediction score for post-operative pain. METHODS AND RESULTS: All patients from the BRUISE CONTROL-1 and 2 trials were included in this analysis. A validated Visual Analogue Scale (VAS) was used to assess the severity of pain related to CIED implant procedures. Patients were asked to grade the most severe post-operative pain, average post-operative pain, and pain on the day of the first post-operative clinic. Multivariable regression analyses were performed to identify predictors of significant post-operative pain and to develop a pain-prediction score. A total of 1308 patients were included. Multivariable regression analysis found that the presence of post-operative clinically significant haematoma {CSH; P value < 0.001; odds ratio (OR) 3.82 [95% confidence interval (CI): 2.37-6.16]}, de novo CIED implantation [P value < 0.001; OR 1.90 (95% CI: 1.47-2.46)], female sex [P value < 0.001; OR 1.61 (95% CI: 1.22-2.12)], younger age [<65 years; P value < 0.001; OR 1.54 (95% CI: 1.14-2.10)], and lower body mass index [<20 kg/m2; P value < 0.05; OR 2.05 (95% CI: 0.98-4.28)] demonstrated strong and independent associations with increased post-operative pain. An 11-point post-operative pain prediction score was developed using the data. CONCLUSION: Our study has identified multiple predictors of post-operative pain after CIED insertion. We have developed a prediction score for post-operative pain that can be used to identify individuals at risk of experiencing significant post-operative pain. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: Post-operative pain following cardiac implantable electronic device (CIED) insertion is associated with patient dissatisfaction, emotional distress, and emergency department visits. We sought to identify factors associated with post-operative pain and develop a prediction score for post-operative pain. METHODS AND RESULTS: All patients from the BRUISE CONTROL-1 and 2 trials were included in this analysis. A validated Visual Analogue Scale (VAS) was used to assess the severity of pain related to CIED implant procedures. Patients were asked to grade the most severe post-operative pain, average post-operative pain, and pain on the day of the first post-operative clinic. Multivariable regression analyses were performed to identify predictors of significant post-operative pain and to develop a pain-prediction score. A total of 1308 patients were included. Multivariable regression analysis found that the presence of post-operative clinically significant haematoma {CSH; P value < 0.001; odds ratio (OR) 3.82 [95% confidence interval (CI): 2.37-6.16]}, de novo CIED implantation [P value < 0.001; OR 1.90 (95% CI: 1.47-2.46)], female sex [P value < 0.001; OR 1.61 (95% CI: 1.22-2.12)], younger age [<65 years; P value < 0.001; OR 1.54 (95% CI: 1.14-2.10)], and lower body mass index [<20 kg/m2; P value < 0.05; OR 2.05 (95% CI: 0.98-4.28)] demonstrated strong and independent associations with increased post-operative pain. An 11-point post-operative pain prediction score was developed using the data. CONCLUSION: Our study has identified multiple predictors of post-operative pain after CIED insertion. We have developed a prediction score for post-operative pain that can be used to identify individuals at risk of experiencing significant post-operative pain. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Michael E Robinson; Erin A Dannecker; Steven Z George; John Otis; James W Atchison; Roger B Fillingim Journal: J Pain Date: 2005-07 Impact factor: 5.820
Authors: Roger B Fillingim; Timothy J Ness; Toni L Glover; Claudia M Campbell; Barbara A Hastie; Donald D Price; Roland Staud Journal: J Pain Date: 2005-02 Impact factor: 5.820