Predicting poor postoperative acute pain outcome in adults: an international, multicentre database analysis of risk factors in 50,005 patients

• Published in: Pain reports 2020-07, Vol.5 (4), p.e831-e831
• Main Authors: Schnabel, Alexander, Yahiaoui-Doktor, Maryam, Meissner, Winfried, Zahn, Peter Konrad, Pogatzki-Zahn, Esther Miriam
• Format: Article
• Language: English
• Subjects: Acute and Perioperative
• ISSN: 2471-2531; 2471-2531
• DOI: 10.1097/PR9.0000000000000831

The aim of this study was to determine simple risk factors for severe pain intensity (≥7 points on a numeric rating scale [NRS]), to analyse their relation to other patient-reported outcome measures and to develop a simple prediction model. We used data from 50,005 patients from the PAIN-OUT project. Within a first data set (n = 33,667), relevant risk factors were identified by logistic binary regression analysis, assessed for additional patient-reported outcome measures beyond pain intensity and summed up for developing a simple risk score. Finally, sum of factors was plotted against postoperative pain outcomes within a validation data set (n = 16,338). Odds ratios (OR) for the following risk factors were identified: younger age (90 minutes, OR: 1.308), preoperative opioid intake (OR: 1.250), feeling anxious (OR: 1.239) and feeling helpless due to pain (OR: 1.198), and the country of the recruiting centre (OR: 1.919). Patients with ≥3 risk factors had more severe pain intensity scores, spent a longer time in severe pain, and wished to have received more pain treatment ( < 0.001). A simple risk score was created with 4 risk factors showing a moderate prediction level. Patients with ≥3 risk factors are at higher risk for poor postoperative acute pain outcome after surgery. Future studies using this score might show that preventive strategies might decrease pain intensity, pain-related postoperative dysfunction, and the development of chronic pain.