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Developing and validating a nomogram for predicting cervical disc resorption after posterior cervical single
Dechen Yu1, Xiongfei Cao1, Kangkang Su1
1Department of Orthopedics, The First Affiliated Hospital of Air Force Medical University, Xi'an, China.
Purpose:
For patients with multilevel degenerative cervical myelopathy caused by cervical spinal stenosis involving ≥ 3 intervertebral segments, cervical disc resorption (CDR) may be observed following posterior cervical single open-door laminoplasty (PCSOL). CDR has been associated with a lower observed rate of secondary anterior decompression; however, this association does not establish causality, and the predictive factors for CDR remain unclear.
Methods:
Data from 266 patients who underwent PCSOL at the authors' institution between June 2016 and June 2022, were retrospectively analyzed. Least absolute shrinkage and selection operator (LASSO) regression was used to identify predictors of postoperative CDR and to construct a predictive model. Internal validation was performed using bootstrap resampling (n = 1000 iterations). The discriminative ability, calibration, and clinical utility of the model were assessed according to the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA), respectively.
Results:
CDR occurred in 122 of 266 patients (45.9%). LASSO regression identified 5 potential predictors: sex, age, course of disease, C2-7 Cobb angle, and T1 slope. A nomogram incorporating these factors was developed and demonstrated good discriminative ability (AUC 0.839 [95% confidence interval 0.791-0.886]). The calibration curve indicated good agreement between predicted and observed probabilities (Hosmer-Lemeshow test P-value = 0.415). DCA confirmed the clinical utility of this nomogram.
Conclusion:
For patients with multilevel degenerative cervical myelopathy involving ≥ 3 segments, a nomogram capable of identifying patients at probability of CDR after PCSOL was developed and validated. This model provides clinicians with a theoretical basis for optimizing treatment strategies.