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Development and internal validation of a nomogram for predicting postoperative bone nonunion in infectious
Wentao Zhao1, Lu Xing1, Yongrui Yang1
1Department of Orthopedics, Public Health Clinical Center Affiliated to Shandong University, Jinan City, Shandong Province, China.
Background:
Postoperative bone nonunion remains a major complication after instrumented fusion for infectious spondylitis, with substantially higher rates than in aseptic spinal surgery. Existingmodels lack validation and infection-specific predictors.
Purpose:
To develop and internally validate a nomogram for the perioperative prediction of postoperative bone nonunion ininfectious spondylitis patients.
Method:
This retrospective cohort study included 224 patients with infectious spondylitis undergoing posterior debridement and instrumented fusion (January 2020-December 2023). Patients were classified as union (n = 166) or nonunion (n = 58) by Bridwell grading on 12-month CT. After univariate screening, LASSO regression with the 1-SE criterion selected five predictors for multivariable logistic regression to construct the nomogram. Discrimination(AUC), calibration(Hosmer-Lemeshow test), and clinical utility(DCA) were assessed. Internal validation using 1,000 bootstrap resamples.
Results:
5predictors were incorporated: Lower Albumin (ALB) level, prolonged CRP normalization days, allogeneic bone graft materials, multilevel fusion and paravertebral abscess. The nomogram demonstrated excellent discrimination(AUC 0.936 ,95% CI: 0.896-0.975) and good calibration (p = 0.285). DCA indicated strongnet benefit across 2%-85% thresholds.Bootstrap validation (1,000 resamples) yieldedAUC0.94 (95% CI: 0.88-0.97) with excellent calibration (slope = 1.000, intercept ≈ 0.000, Emax = 0.061, Brier score = 0.077), confirmingminimal overfitting.
Conclusion:
A novel nomogram incorporating fiveperioperative predictors was developed and internally validated for early prediction of bone nonunion after fusion in infectious spondylitis, showing excellent discrimination, calibration, and clinical utility with minimal overfitting. External validation in larger multicenter cohorts is required beforeclinical application.