Predicting Acute Pain After Surgery: A Multivariate Analysis

Quentin Baca, MD, PhD; Florian Marti, MD, MSc; Beate Poblete, MD; Brice Gaudilliere, MD, PhD; Nima Aghaeepour, PhD; Martin S. Angst, MD


Annals of Surgery. 2021;273(2):289-298. 

In This Article

Abstract and Introduction


Objectives: To identify perioperative practice patterns that predictably impact postoperative pain.

Background: Despite significant advances in perioperative medicine, a significant portion of patients still experience severe pain after major surgery. Postoperative pain is associated with serious adverse outcomes that are costly to patients and society.

Methods: The presented analysis took advantage of a unique observational data set providing unprecedented detailed pharmacological information. The data were collected by PAIN OUT, a multinational registry project established by the European Commission to improve postoperative pain outcomes. A multivariate approach was used to derive and validate a model predictive of pain on postoperative day 1 (POD1) in 1008 patients undergoing back surgery.

Results: The predictive and validated model was highly significant (P = 8.9E-15) and identified modifiable practice patterns. Importantly, the number of nonopioid analgesic drug classes administered during surgery predicted decreased pain on POD1. At least 2 different nonopioid analgesic drug classes (cyclooxygenase inhibitors, acetaminophen, nefopam, or metamizol) were required to provide meaningful pain relief (>30%). However, only a quarter of patients received at least 2 nonanalgesic drug classes during surgery. In addition, the use of very short-acting opioids predicted increased pain on POD1, suggesting room for improvement in the perioperative management of these patients. Although the model was highly significant, it only accounted for a relatively small fraction of the observed variance.

Conclusion: The presented analysis offers detailed insight into current practice patterns and reveals modifications that can be implemented in today's clinical practice. Our results also suggest that parameters other than those currently studied are relevant for postoperative pain including biological and psychological variables.


Postoperative pain is associated with high individual and societal costs. One to two-thirds of patients suffer from moderate to severe pain after surgery, which is associated with adverse outcomes, including delirium, pulmonary and cardiac complications, and the development of persistent pain after surgery.[1–5] Opioid use and abuse patterns in conjunction with the treatment of postoperative pain also carry a high societal cost.[6–8]

The effective and safe management of postoperative pain is of high priority as highlighted by recent practice guidelines.[9] Robust strategies for identifying patients at risk for severe postoperative pain and devising practice patterns that mitigate this risk are critically needed. One approach is to take advantage of large and detailed observational studies including postoperative pain outcomes. In this context, multiple studies have reported correlates of postoperative pain.[10–12] However, an inherent limitation of correlates is uncertainty about their predictive power, robustness, and validity. As a result, many correlates are quite variable and in some instances, inconsistent across different studies.[11]

The aim of this study was to use a multivariate approach to infer a robust and predictive model of acute postoperative pain.[13] The data set used for this analysis was collected by PAIN OUT, a multicenter and multinational registry project established by the European Commission to provide feedback to health care providers and improve post-operative pain outcomes.[14,15] A unique and attractive feature of this data set is the very detailed pharmacological information relevant to the perioperative period, along with demographic and clinical data.[16,17] We selected a data set specific to spine surgery, as this is a major and frequently performed procedure associated with significant postoperative pain and morbidity.[1,3,18]