Risk factors analysis and risk prediction model establishment for heterotopic ossification after open reduction and...

To identify independent risk factors for heterotopic ossification (HO) after open reduction and internal fixation (ORIF) of distal humeral fractures, and to construct and validate a clinically applicable risk prediction model.

This retrospective cohort study included 826 patients with distal humeral fractures who underwent ORIF in 3 Grade A tertiary hospitals. Multi-dimensional baseline data were collected. The primary outcome was the occurrence of HO within 6 months after surgery. Potential risk factors were screened by univariate analysis and multivariate Logistic regression. The model was internally validated using Bootstrap resampling (1,000 iterations) to estimate the mean area under the receiver operating characteristic curve (AUC), and temporally validated using a cohort of 186 patients enrolled from the same tertiary hospital (temporal external validation). Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the model's performance. A nomogram was also constructed for visualization.

The overall incidence of postoperative HO was 23.7%. Age ≥ 60 years, high-energy injury, comminuted fracture, extensive intraoperative soft tissue dissection, postoperative immobilization ≥ 4 weeks and postoperative infection were independent risk factors (all P < 0.001). The internal validation AUC of the model was 0.846, and the external validation AUC was 0.823. The calibration was good (Hosmer-Lemeshow test, P = 0.610). When the risk threshold was between 8 and 75%, the clinical net benefit of the model was superior to traditional strategies. The nomogram could intuitively predict the risk of HO.

This study identified the core risk factors for HO. The established prediction model can serve as a preliminary risk-stratification tool for HO. Further prospective studies and geographically distinct external validation are still needed before this model can be applied in routine clinical practice.