Constructing a nomogram model for patients with cervical spondylotic myelopathy

This study aims to construct a nomogram to predict the prognosis of patients with cervical spondylotic myelopathy (CSM). This study included 358 patients diagnosed with cervical spondylotic myelopathy. We collected serological indicators of patients at admission, including routine blood tests, biochemical tests, liver and kidney function, coagulation function and other laboratory tests. We used t-test, rank-sum test, chi-square test or Fisher test for inter-group comparison. We used univariate and multivariate logistic regression analysis to obtain independent predictors of poor prognosis of patients, and constructed the independent predictors into a nomogram using R language, and verified the predictive performance of the nomogram. The results showed that Platelets (PLT) (1.005 [1.001, 1.009], p = 0.021), Albumin (ALB) (0.891 [0.818, 0.97], p = 0.008), Aspartate aminotransferase (AST) (1.031 [1.002, 1.061], p = 0.035), Alanine aminotransferase (ALT) (0.958 [0.92, 0.998], p = 0.037), and Fibrinogen (FIB) (0.654 [0.464, 0.921], p = 0.015) were independent predictors. Good prediction performance with modest errors was shown by the nomogram in both the training and validation groups. ALB, AST, ALT, FIB, and PLT at admission may be independent predictors of the efficacy of ACDF in CSM patients. The nomogram constructed with these factors has good predictive performance. Serological indicators can be used as a supplement to cervical spine-related imaging indicators, allowing clinicians to better complete the admission diagnosis and treatment process and preoperative evaluation process, so that more postoperative patients can benefit.