ArticleScientific reports2024
Development and validation of predictive nomogram for postoperative non-union of closed femoral shaft fracture.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Performance of prediction models for delayed union and nonunion after fracture: a systematic review and meta-analysis.BMC musculoskeletal disorders · 2026Pooled it
- Development and internal validation of a nomogram for predicting postoperative bone nonunion in infectious spondylitis: a retrospective cohort study.Annals of medicine · 2026Article
- Development and validation of a nomogram for predicting postoperative bone nonunion in spinal tuberculosis patients.Frontiers in surgery · 2026Article
- Risk factors and a predictive nomogram for nonunion following intramedullary nailing of femoral shaft fractures.BMC musculoskeletal disorders · 2025Article
- Functional mechanism and clinical implications of lncRNA NEAT1 in traumatic fractures and their correlation with delayed healing.Journal of orthopaedic surgery and research · 2025Article
- A Scoring System for Predicting Nonunion After Intramedullary Nailing of Femoral Shaft Fractures.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Closed femoral shaft fracture is caused by high-energy injuries, and non-union exists after operation, which can significantly damage patients' body and mind. This study aimed to explore the factors influencing postoperative non-union of closed femoral shaft fractures and establish a predictive nomogram. Patients with closed femoral shaft fractures treated at Hebei Medical University Third Hospital between January 2015 and December 2021 were retrospectively enrolled. A total of 729 patients met the inclusion criteria; of them, those treated in 2015-2019 comprised the training cohort (n = 617), while those treated in 2020-2021 comprised the external validation cohort (n = 112). According to multivariate logistic regression analysis, complex fractures, bone defects, smoking, and postoperative infection were independent risk factors. Based on the factors, a predictive nomogram was constructed and validated. The C-indices in training and external validation cohorts were 0.818 and 0.781, respectively; and the C-index of internal validation via bootstrap resampling was 0.804. The Hosmer-Lemeshow test showed good fit of the nomogram (P > 0.05) consistent with the calibration plot results. The clinical effectiveness was best at a threshold probability of 0.10-0.40 in decision curve analysis. The risk prediction for patients with fractures using this nomogram may aid targeted prevention and rehabilitation programs.
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