Emergence of unique hues from sparse coding of color in natural scenes.

BACKGROUND

Kümmell's disease is a severe post-traumatic vertebral osteonecrosis characterized by delayed collapse and kyphosis following osteoporotic vertebral compression fractures (OVCFs). The transition from acute fracture to nonunion remains poorly understood. Using a single-center retrospective cohort, we aimed to develop and validate a nomogram to predict Kümmell's disease in patients with acute OVCFs undergoing conservative management.

METHODS

We included 626 patients (aged ≥50 years) with acute or subacute OVCFs treated conservatively between January 2021 and October 2024, randomly partitioned into a training cohort (n=470) and a validation cohort (n=156). Demographic characteristics, metabolic profiles, medication history, and radiological parameters including MRI-based paraspinal muscle metrics were analyzed. LASSO regression-based feature selection identified candidate predictors from high-dimensional variables, followed by multivariate logistic regression to construct a nomogram.

RESULTS

Kümmell's disease developed in 12.6% of the training cohort and 10.9% of the validation cohort. Six independent predictors were identified. Diabetes mellitus (OR 40.61, 95% CI 7.80-211.34), prolonged bed rest >2 weeks (OR 9.69, 95% CI 3.92-23.93), and higher initial vertebral compression rate were risk factors. Anti-osteoporosis treatment (OR 0.02), higher lumbar bone mineral density, and greater relative cross-sectional area of the multifidus muscle were protective. The nomogram achieved an area under the curve of 0.938 (95% CI 0.906-0.970) in the training cohort and 0.882 (95% CI 0.784-0.980) in the validation cohort.

CONCLUSION

This nomogram integrates metabolic, biomechanical, and pharmacological factors to predict Kümmell's disease. Prolonged bed rest was associated with increased nonunion risk, while anti-osteoporosis pharmacotherapy and multifidus muscle integrity were protective. This tool may support precision risk stratification, guiding a shift from passive observation to active intervention for high-risk patients.