Response to Yang and Riva-Cambrin

Abstract

We thank the colleagues Yang and Riva-Cambrin for their comments 11 related to our recently published database analysis. 9 The main aim of our article 9 was to identify risk factors and (if possible) to develop a clinically easy to use risk score relevant for acute pain after surgery. We used the largest multicenter international PAIN OUT database for this research question 13 because we aimed to identify risk factors not limited to one specific surgery nor to one institution in a specific country. Furthermore, because the clinical relevance of pain intensity as the most important patient-reported outcome measure (PROM) in postoperative pain has been criticized, 6,8,10 we also examined other, possibly more important, PROMs such as "time spent in severe pain" or "wished to have received more pain treatment"; these PROMs are assessed in PAIN OUT by using the validated IPO questionnaire that has been translated into many different languages. 7,13 Logistic binary regression and exploratory factor analysis enabled us to develop a very easy to use prediction model with a decent (but still not perfect) predictive value, which was thereafter validated in a second cohort.Of course, besides the clear advantages (like the extremely high number of data sets available, very strict and therefore comparable data assessment, multicenter approach, multicultural approach, and clinical relevant PROMs beyond pain intensity), such an approach still has a number of limitations. We therefore definitively agree to some of the criticisms by Yang and Riva-Cambrin that we discussed in detail and would like to refer to our article where we clearly refer to these limitations. First, we discussed 9 that data collection was (only)Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.