ArticleQuantitative imaging in medicine and surgery2026
A predictive model integrating three-dimensional displacement for osteonecrosis of femoral head following femoral neck fractures: a retrospective cohort study.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Fracture displacement is a recognized risk factor for osteonecrosis of the femoral head (ONFH) after femoral neck fractures (FNFs), yet the relationship between ONFH and three-dimensional (3D) displacement has not been clearly quantified. This study aims to develop a computed tomography-based method to measure 3D displacement at the FNF site and to build a predictive model that integrates these parameters. Methods: We retrospectively analyzed 302 FNF patients treated with closed reduction and internal fixation within 3 years. Univariate analysis and multivariable logistic regression were used to assess the association between ONFH and multiple variables, including 3D displacement. The prediction model for ONFH was evaluated using receiver operating characteristic curve, a nomogram, calibration curve, and decision curve analysis (DCA). Results: During the 3-year follow-up period, ONFH was identified in 68 cases (incidence rate 22.5%). Univariate analysis showed that Garden classification, age, time to surgery, osteoporosis, comminution, fixation removal, and displacement parameters (vertical, separation, and comprehensive) were significantly associated with ONFH (P<0.05). Multivariable logistic analysis confirmed that vertical displacement, separation displacement, age, and time to surgery were independent predictors [P<0.05; odds ratio (95% confidence interval): 1.20 (1.01-1.42), 1.19 (1.08-1.30), 0.92 (0.88-0.95), 1.87 (1.41-2.49), respectively]. The model showed an area under the curve >0.91, sensitivity >81%, specificity >89%, and a Youden index of 0.769. Calibration curves showed good agreement between predicted and actual probabilities (Hosmer-Lemeshow test, P>0.05), while DCA indicated clinical usefulness within a risk threshold of 0.10-0.90. In the nomogram, separation displacement contributed the highest score. Conclusions: ONFH is related to factors such as Garden classification, age, time to surgery, osteoporosis, comminuted status, fixation removal, and vertical, separation, and comprehensive displacement. Among these, age, time to surgery, and vertical and separation displacement are independent risk factors. The predictive model that incorporates 3D displacement can quantify the risk of postoperative ONFH and shows good predictive ability in FNF patients. However, further external validation is still required.
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