The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, People's Republic of China.
Sci Rep. 2023 Jun 17;13(1):9816. doi: 10.1038/s41598-023-36992-7.
The ossification of the posterior longitudinal ligament (OPLL) in the cervical spine is commonly observed in degenerative changes of the cervical spine. Early detection of cervical OPLL and prevention of postoperative complications are of utmost importance. We gathered data from 775 patients who underwent cervical spine surgery at the First Affiliated Hospital of Guangxi Medical University, collecting a total of 84 variables. Among these patients, 144 had cervical OPLL, while 631 did not. They were randomly divided into a training cohort and a validation cohort. Multiple machine learning (ML) methods were employed to screen the variables and ultimately develop a diagnostic model. Subsequently, we compared the postoperative outcomes of patients with positive and negative cervical OPLL. Initially, we compared the advantages and disadvantages of various ML methods. Seven variables, namely Age, Gender, OPLL, AST, UA, BMI, and CHD, exhibited significant differences and were used to construct a diagnostic nomogram model. The area under the curve (AUC) values of this model in the training and validation groups were 0.76 and 0.728, respectively. Our findings revealed that 69.2% of patients who underwent cervical OPLL surgery eventually required elective anterior surgery, in contrast to 86.8% of patients who did not have cervical OPLL. Patients with cervical OPLL had significantly longer operation times and higher postoperative drainage volumes compared to those without cervical OPLL. Interestingly, preoperative cervical OPLL patients demonstrated significant increases in mean UA, age, and BMI. Furthermore, 27.1% of patients with cervical anterior longitudinal ligament ossification (OALL) also exhibited cervical OPLL, whereas this occurrence was only observed in 6.9% of patients without cervical OALL. We developed a diagnostic model for cervical OPLL using the ML method. Our findings indicate that patients with cervical OPLL are more likely to undergo posterior cervical surgery, and they exhibit elevated UA levels, higher BMI, and increased age. The prevalence of cervical anterior longitudinal ligament ossification was also significantly higher among patients with cervical OPLL.
颈椎后纵韧带骨化(OPLL)在颈椎退行性变中较为常见。早期发现颈椎 OPLL 并预防术后并发症至关重要。我们收集了广西医科大学第一附属医院 775 例颈椎手术患者的数据,共收集了 84 个变量。其中 144 例患者患有颈椎 OPLL,631 例患者没有。他们被随机分为训练队列和验证队列。我们采用多种机器学习(ML)方法筛选变量,并最终开发了一个诊断模型。随后,我们比较了颈椎 OPLL 阳性和阴性患者的术后结果。首先,我们比较了各种 ML 方法的优缺点。有 7 个变量,即年龄、性别、OPLL、AST、UA、BMI 和 CHD,表现出显著差异,并用于构建诊断列线图模型。该模型在训练组和验证组中的曲线下面积(AUC)值分别为 0.76 和 0.728。我们的研究结果表明,69.2%接受颈椎 OPLL 手术的患者最终需要择期前路手术,而没有颈椎 OPLL 的患者则为 86.8%。与没有颈椎 OPLL 的患者相比,患有颈椎 OPLL 的患者手术时间明显更长,术后引流量更高。有趣的是,术前颈椎 OPLL 患者的平均 UA、年龄和 BMI 显著增加。此外,27.1%的颈椎前纵韧带骨化(OALL)患者也伴有颈椎 OPLL,而在没有颈椎 OALL 的患者中,这一发生率仅为 6.9%。我们使用 ML 方法开发了颈椎 OPLL 的诊断模型。我们的研究结果表明,患有颈椎 OPLL 的患者更有可能接受后路颈椎手术,并且他们的 UA 水平较高,BMI 较高,年龄较大。颈椎前纵韧带骨化在伴有颈椎 OPLL 的患者中也更为常见。