基于Logistic-Nomogram构建创伤性脊髓损伤预后预测模型

方芳; 张社敏; 戴志强; 谢亚丽; 谢佳芯

doi:10.16190/j.cnki.45-1211/r.2023.09.011

基于Logistic-Nomogram构建创伤性脊髓损伤预后预测模型

Construction of a prognosis prediction model for traumatic spinal cord injury based on Logical-Nomogram

摘要

摘要: 目的：基于多因素Logistic 回归分析创伤性脊髓损伤（TSCI）预后不良相关因素，构建Nomogram 预测模型并进行验证。方法：选取2020年3月至2022年9月中国人民解放军联勤保障部队第九二〇医院收治的250例TSCI患者为研究对象，按照7∶3比例随机分为训练组（n=175）和验证组（n=75）。分别于治疗前及治疗后6个月采用日本骨科学会（JOA）量表评估患者预后，以JOA评分改善率≥60%为预后良好组，改善率< 60%为预后不良组。采用单因素和多因素Logistic回归法分析预后不良的影响因素，根据影响因素构建Nomogram预测模型，并验证该模型预测效能及临床效用。结果：椎管侵占率≥50%、损伤严重程度为完全损伤、损伤至治疗时间≥8 h、外周血纤维蛋白原（FIB）水平降低、血清高迁移率族蛋白B1（HMGB1）和细胞核因子-κB（NF-κB）水平升高以及外周血中性粒细胞计数与淋巴细胞计数比值（NLR）增高均为预后不良的独立危险因素（P< 0.05）。Nomogram预测模型预测预后不良的曲线下面积（AUC）为0.944，且具有正向净收益。结论：椎管侵占率、损伤程度、治疗时间及外周血HMGB1、NF-κB、NLR、FIB水平均为TSCI患者预后不良的危险因素，基于上述因素构建的Nomogram模型对预后不良有较好预测效能，有助于临床筛查高危人群并制定治疗方案。

Abstract: Objective:To analyze the factors associated with poor prognosis of traumatic spinal cord injury(TSCI) based on multivariate Logistic regression analysis, and to construct and verify a Nomogram prediction model.Methods:A total of 250 TSCI patients admitted to the 920th Hospital of Joint Logistic Support Force of the Chinese People’s Liberation Army from March 2020 to September 2022 were selected as research objects, and randomly divided into training group (n=175) and verification group (n=75) according to a ratio of 7:3.The Japanese Orthopaedic Society (JOA) score was used to evaluate the prognosis of patients before treatment and 6 months after treatment.A JOA score improvement rate ≥60% was considered as good prognosis group, and a JOA score improvement rate < 60%was considered as poor prognosis group.The prognosis of the two groups at 6 months after treatment was statistically compared.Univariate and multivariate Logistic regression analysis were used to analyze the influencing factors of poor prognosis, and a Nomogram prediction model was established based on the influencing factors to verify the prediction efficacy and clinical efficacy of this model.Results:The spinal canal encroachment rate ≥50%, injury severity (complete injury), injury to treatment time ≥8 h, decreased peripheral blood fibrinogen (FIB) level, serum high mobility group protein B1(HMGB1) and nuclear factor κB (NF-κB) levels, and increased peripheral blood neutrophil count to lymphocyte count ratio (NLR) level were independent risk factors for poor prognosis (P< 0.05).The area under the curve(AUC)of the Nomogram prediction model for predicting poor prognosis was 0.944, and it had a positive net benefit.Conclusion:The spinal canal encroachment rate ≥50%, injury degree, treatment time, and peripheral blood HMGB1, NF-κB, NLR and FIB levels are risk factors for poor prognosis in patients with TSCI.The Nomogram model based on the above factors has good predictive efficacy for poor prognosis, which is helpful for clinical screening of high-risk groups and making treatment plans.

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