Distinguishing between pain intensity and pain resolution: Using acute post-surgical pain trajectories to predict chronic post-surgical pain


Althaus, Astrid ; Arránz Becker, Oliver ; Neugebauer, Edmund



DOI: https://doi.org/10.1002/j.1532-2149.2013.00385.x
URL: http://onlinelibrary.wiley.com/doi/10.1002/j.1532-...
Dokumenttyp: Zeitschriftenartikel
Erscheinungsjahr: 2014
Titel einer Zeitschrift oder einer Reihe: European Journal of Pain : EJP
Band/Volume: 18
Heft/Issue: 4
Seitenbereich: 513-521
Ort der Veröffentlichung: Oxford [u.a.]
Verlag: Wiley-Blackwell
ISSN: 1090-3801 , 1532-2149
Sprache der Veröffentlichung: Englisch
Einrichtung: Außerfakultäre Einrichtungen > MZES - Arbeitsbereich A
Fachgebiet: 300 Sozialwissenschaften, Soziologie, Anthropologie
Abstract: Background: High intensity of acute post-surgical pain is one of the strongest predictors for chronic post-surgical pain (CPSP). We investigated the predictive power of acute post-surgical pain trajectories and the interplay of pain trajectories and diverse psychosocial risk factors in the development of CPSP.<br> Methods: Data from 199 patients were examined using latent growth curve analysis by means of structural equation modelling. This analytical approach was used to explicitly test the mediating role of acute pain trajectories within the association between preoperative psychosocial vulnerability factors and CPSP.<br> Results: Both initial pain intensity and pain resolution during the first five post-operative days independently contributed to the prediction of CPSP 6 months after surgery. In terms of vulnerability, anxiety and depression had clear but opposing effects on post-operative pain trajectories. Whereas depressive patients exhibited impaired pain resolution, patients with high anxiety showed better rates of pain resolution after surgery. Both effects on acute pain resolution extended to chronic pain 6 months after surgery.<br> Conclusions: In this study, we demonstrated that going beyond conventional one-time measurements of acute pain by modelling pain trajectories may substantially enhance research on pain chronification in two ways: First, pain trajectories bear great potential to improve the prediction of CPSP. Second, they represent a meaningful link between psychosocial vulnerability and CPSP because they can be used to uncover mechanisms by which psychosocial vulnerability unfolds. The reported findings suggest that the incidence of CPSP may be reduced by optimizing post-operative pain monitoring.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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