gms | German Medical Science

16. Deutscher Kongress für Versorgungsforschung

Deutsches Netzwerk Versorgungsforschung e. V.

4. - 6. Oktober 2017, Berlin

External validation and update of the RICP – a multivariate model to predict chronic postoperative pain

Meeting Abstract

  • Tim Mathes - Institut für Forschung in der Operativen Medizin (Universität Witten/Herdecke gGmbH), Köln, Germany
  • Carolina Pape-Köhler - Köln, Germany
  • Eberhard Lux - Lünen, Germany
  • Edmund A.M. Neugebauer - Medizinische Hochschule Brandenburg, Neuruppin, Germany

16. Deutscher Kongress für Versorgungsforschung (DKVF). Berlin, 04.-06.10.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocP075

doi: 10.3205/17dkvf231, urn:nbn:de:0183-17dkvf2311

Veröffentlicht: 26. September 2017

© 2017 Mathes et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Background: Chronic postsurgical pain (CPSP) is a frequent postoperative complication with an incidence of 10–50% after general surgery. The development of chronic postsurgical pain (CPSP) is influenced by various factors. In order to identify patients at high risk for CPSP, the risk index for chronic pain (RICP) was developed.

Objective: The aim of this study was the external validation and update of the RICP.

Methods: To validate and update the RICP, we performed a prospective cohort study. Participants who underwent orthopedic surgery, general surgery, visceral surgery, and neurosurgery were included. The study was performed at two German centers. The outcome was CPSP at 6 months after surgery.

We validated the original RICP externally and performed a model update. Analysis was performed using logistic regression. We analyzed the discrimination and calibration of the model. Furthermore, the updated model was internally validated.

Results: We included 205 patients undergoing general, abdominal, thoracic, neuro, or orthopedic surgery as well as trauma patients. The mean age of participants was 51 years. CPSP was reported by 53.9% of participants.

The original RICP (preoperative pain in operating field, other CPSP, postoperative acute pain, capacity overload, and convalescence) showed a sensitivity of 0.708 and a specificity of 0.727.

The updated RICP (preoperative pain in operating field, other pain, postoperative acute pain, sex, marital status) yielded a sensitivity of 0.746 and a specificity of 0.726. The results were confirmed by the internal validation. In particular the pre- and postoperative pain measures showed high predictive ability all models.

Discussion: The original RICP is externally valid. The updated RICP showed high predictive ability and is internally valid. The results are limited by the small sample size and the large amount of missing outcome data.

Implications for practice: Precise information on the risk of CPSP can support early identification of patients with a high-risk of developing CPSP. This is important information for achieving timely and tailored pain management that might prevent chronification. A next step should be further external validation and the development of a Clinical Decision Support Tool as an application for modern technical devices (smartphones, tablets) that enables calculating the patients’ individual risk of developing chronic post-surgical pain easily but more precisely.