Reduced Endurance Duration of Cervical Paraspinal Extensors Serves as an Independent Risk Factor for Axial Symptoms After Laminoplasty in Cervical Spondylotic Myelopathy Patients: A Prospective Study

Prospective observational study. To investigate the impact of paraspinal extensor endurance duration on the development of axial symptoms (AS) following laminoplasty (LP). AS is a common complication after LP. Although various factors, including cervical paraspinal extensors, have been implicated in its occurrence, the relationship between paraspinal extensor endurance duration and AS remains unexplored. Muscle endurance duration is a widely used indicator of muscle function and may offer predictive value. Patients with cervical spondylotic myelopathy (CSM) who underwent LP were included. Based on the presence or absence of AS at six months postoperatively, patients were divided into AS and non-AS groups. A custom-designed device was used to measure paraspinal extensor endurance duration. Demographic data, radiographic parameters, and patient-reported outcome measures (PROMs) were collected. Intergroup comparisons and multivariate logistic regression analyses were performed to identify risk factors for AS. A total of 105 patients were enrolled, with 61 (58.1%) in the non-AS group and 44 (41.9%) in the AS group. The non-AS group demonstrated significantly longer preoperative endurance duration ( P <0.001). No significant differences were observed in preoperative sagittal alignment or paraspinal muscle morphology. The non-AS group had lower preoperative VAS-neck and NDI scores ( P =0.002 and 0.006, respectively). Logistic regression identified endurance duration as the sole independent predictor of AS (odds ratio=0.975, P =0.003). The receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.740, with an optimal cutoff of 42 seconds (sensitivity: 75.4%, specificity: 63.6%). Reduced paraspinal extensor endurance duration is an independent risk factor for AS after LP, demonstrating moderate predictive accuracy.