Ghauri Muhammad S, Rajkumar Sujay, Stone Lauren E, Kelly Michael P, Iyer Rajiv R, Bauer Jennifer, Ames Christopher P, Newton Peter O, Gonda David D, Levy Michael L, Ravindra Vijay M
School of Medicine, California University of Science and Medicine, Colton, CA, USA.
School of Medicine, Drexel University College of Medicine, Philadelphia, PA, USA.
Global Spine J. 2025 May 26:21925682251344928. doi: 10.1177/21925682251344928.
Study DesignRetrospective cohort study.ObjectivesPreoperative risk stratification using frailty is common for adults but difficult to apply to pediatric populations. We aimed to identify risk factors indicating physiologic vulnerability and predict perioperative complications in children with neuromuscular scoliosis (NMS) and to create a prediction model for physiological vulnerability (PV-5).MethodsPatients with NMS were identified from the American College of Surgeons National Surgical Quality Improvement Program Pediatric database. The 9442 patients identified were randomly divided into training and testing cohorts. Univariate and multivariable logistic regression were performed; variables significantly associated with complications were evaluated using the Akaike information criterion and area under the curve. Significant variables received weighted scores, and a patient-specific prediction model was generated and evaluated using the Brier score.ResultsPatients with central nervous system abnormality (OR 1.32 [95%CI 1.13-1.53]), hematologic disorder (OR 1.40 [1.06-1.85]), congenital malformation (OR 1.30 [1.1-1.54]), nutritional support (OR 2.21 [1.91-2.57]), and preoperative wound infection (OR 2.3 [1.4-3.76]) were more likely to develop complications after spinal fusion surgery. PV-5 scores were calculated from these risk factors to generate a prediction model. PV-5 scores of 1 (OR: 2.0 [1.27-3.43], < 0.004), 2 (OR: 2.75 [1.63-4.64], < 0.001), 3 (OR: 3.67 [2.18-6.19], < 0.001), 4 (OR: 4.09 [2.39-6.99], < 0.001), and 5+ (OR: 3.58 [1.35-9.47], = 0.01) predicted greater complication risk than PV-5 of zero (accuracy = 89.65%, Brier score = 0.09).ConclusionsUsing factors associated with complications in children with NMS undergoing spinal fusion surgery, we created a prediction model to illustrate physiologic vulnerability and morbidity. Our model serves as a foundation for further body system-specific investigation.
研究设计
回顾性队列研究。
目的
使用衰弱进行术前风险分层在成人中很常见，但难以应用于儿科人群。我们旨在确定表明生理脆弱性的风险因素，并预测神经肌肉性脊柱侧弯（NMS）患儿的围手术期并发症，并创建一个生理脆弱性预测模型（PV-5）。
方法
从美国外科医师学会国家外科质量改进计划儿科数据库中识别出NMS患者。将识别出的9442例患者随机分为训练组和测试组。进行单因素和多因素逻辑回归分析；使用赤池信息准则和曲线下面积评估与并发症显著相关的变量。对显著变量给予加权评分，并生成患者特异性预测模型，使用Brier评分进行评估。
结果
中枢神经系统异常（比值比[OR]1.32[95%置信区间（CI）1.13-1.53]）、血液系统疾病（OR 1.40[1.06-1.85]）、先天性畸形（OR 1.30[1.1-1.54]）、营养支持（OR 2.21[1.91-2.57]）和术前伤口感染（OR 2.3[1.4-3.76]）的患者在脊柱融合手术后发生并发症的可能性更大。根据这些风险因素计算PV-5评分以生成预测模型。PV-5评分为1（OR：2.0[1.27-3.43]，P<0.004）、2（OR：2.75[1.63-4.64]，P<0.001）、3（OR：3.67[2.18-6.19]，P<0.001）、4（OR：4.09[2.39-6.99]，P<0.001）和5+（OR：3.58[1.35-9.47]，P = 0.01）预测的并发症风险高于PV-5为零的情况（准确率=89.65%，Brier评分=0.09）。
结论
利用接受脊柱融合手术的NMS患儿并发症相关因素，我们创建了一个预测模型来说明生理脆弱性和发病率。我们的模型为进一步针对特定身体系统的研究奠定了基础。
