New AI Model Predicts Chronic Pain Risk After Calcaneal Fracture Surgery, finds study

Key Findings

• Many predictive variables such as those linked to increase lifetime risk of chronic pain include the following:

•Body Mass Index (BMI): Higher BMI was associated with an increased risk (OR: 1.10, 95% CI: 1.02–1.19, P=0.014).

• Operative Duration: Longer surgical time increased the likelihood of chronic pain (OR: 1.01, 95% CI: 1.00–1.02, P=0.019).

• Surgical Approach: The type of surgical technique used influenced postoperative pain outcomes.

• Böhler Angle: Higher Böhler angles were linked to a higher risk (OR: 1.03, 95% CI: 1.00–1.06, P=0.025).

• The predictive model demonstrated good discrimination in both the development cohort (AUC: 0.691, 95% CI: 0.63–0.75) and the validation cohort (AUC: 0.655, 95% CI: 0.56–0.77). Calibration plots confirmed strong agreement between predicted and observed outcomes.

The study authors concluded that the predictive model is a valid medium for chronic pain risk assessment after calcaneal fracture surgery. It provides the practitioner with an individualized assessment of the patient while including significant risk factors whereby more targeted interventions for recovery and quality of life are possible.

Reference:

Zhai, S., Zhang, S., Ma, X. et al. Development of a predictive model for post-surgical chronic pain: a retrospective analysis of calcaneal fracture patients. BMC Musculoskelet Disord 26, 173 (2025).https://doi.org/10.1186/s12891-025-08428-y