Factors influencing postoperative pain catastrophizing in patients with lower limb trauma and development of a nomogram prediction model.

OBJECTIVE

This study aimed to examine the determinants of postoperative pain catastrophizing among surgical patients with lower limb trauma and to develop a nomogram for individualized risk prediction.

METHODS

Data encompassing demographic characteristics, Injury Severity Score (ISS), preoperative Numerical Rating Scale (NRS) for pain, Hospital Anxiety and Depression Scale (HADS) scores, and Fear-Avoidance Beliefs Questionnaire (FABQ) scores were collected. The level of pain catastrophizing was measured postoperatively using the Pain Catastrophizing Scale (PCS). The total sample of 320 patients was randomly allocated into a training set (n = 224) and a validation set (n = 96) at a 7:3 ratio. Independent factors identified through logistic regression analysis were utilized to construct a nomogram. The model's predictive performance was assessed via receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).

RESULTS

Educational attainment at college level or above served as a protective factor. In contrast, higher scores on the NRS, ISS, HADS, and FABQ were significant risk factors. The nomogram exhibited robust discriminative ability, with area under the curve (AUC) values of 0.850 (95% CI: 0.797-0.904) in the training set and 0.815 (95% CI: 0.718-0.911) in the validation set. Calibration analysis indicated good fit, and DCA confirmed favorable clinical net benefit across a range of threshold probabilities.

CONCLUSION

The incidence of postoperative pain catastrophizing is considerable among patients with lower limb trauma and is influenced by multiple factors including trauma severity, educational level, anxiety/depression, fear-avoidance beliefs, and pain intensity. The constructed nomogram prediction model, based on independent influencing factors, exhibits good discrimination, calibration, and clinical utility, effectively predicting the risk of postoperative pain catastrophizing.