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丙戊酸钠致神经重症患者高氨血症的危险因素分析及风险预测模型构建
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| 篇名： | 丙戊酸钠致神经重症患者高氨血症的危险因素分析及风险预测模型构建 |
| TITLE： | Analysis of risk factors for sodium valproate-induced hyperammonemia in neurocritical patients and construction of risk prediction model |
| 摘要： | 目的 探讨丙戊酸钠（VPA）致神经重症患者高氨血症的危险因素，并构建风险预测模型。方法回顾性收集2022年1月至2025年6月入住苏州大学附属第四医院重症医学科的172例使用VPA的神经重症患者的临床资料，根据血氨水平将其分为高血氨组（73例）和正常组（99例）。采用单因素分析及LASSO回归筛选预测变量，再通过多因素Logistic回归分析筛选独立因素并据此绘制列线图。采用受试者操作特征（ROC）曲线、校准曲线及决策曲线分析（DCA）评估模型预测性能。结果结合单因素分析及LASSO回归共筛选出体重指数（BMI）≥24.0kg/m2、合用苯二氮类药物、VPA血药浓度、血红蛋白、血清尿素、VPA日均剂量及白蛋白7个预测变量；多因素Logistic回归分析结果显示，合用苯二氮类药物、BMI≥24.0kg/m2、VPA血药浓度、白蛋白、血清尿素（比值比分别为1.615、1.538、1.623、1.942、0.637，95%置信区间分别为1.128～2.359、1.059～2.251、1.112～2.431、1.106～3.598、0.402～0.980）均与VPA致神经重症患者高氨血症显著相关（P＜0.05）。基于上述变量所建列线图预测模型的评估结果显示，测试集和验证集的ROC曲线下面积分别为0.810和0.844，校正曲线与实际曲线的趋势基本一致，应用该模型可提高临床净获益率。结论合用苯二氮类药物、BMI≥24.0kg/m2、高VPA血药浓度、高白蛋白是VPA致神经重症患者发生高氨血症的独立危险因素，而高血清尿素则是其独立保护因素；基于上述因素构建的风险预测模型的区分度、一致性、临床实用性均较好，可用于预测VPA致神经重症患者发生高氨血症的发生风险。 |
| ABSTRACT： | OBJECTIVE To investigate the risk factors for sodium valproate （VPA）-induced hyperammonemia in neurocritical patients， and to construct a risk prediction model. METHODS Clinical data were retrospectively collected from 172 neurocritical patients who received VPA treatment in the Department of Critical Care Medicine， the Fourth Affiliated Hospital of Soochow University from January 2022 to June 2025. Patients were divided into the hyperammonemia group （73 cases） and the normal group （99 cases） based on their blood ammonia levels. Univariate analysis and LASSO regression analysis were used to screen for predictive variables. Independent factors were identified through multivariate Logistic regression analysis， and a nomogram was constructed accordingly. The performance of the model was evaluated using receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis （DCA）. RESULTS Combination of univariate analysis and LASSO regression analysis screened out seven predictive variables： body mass index （BMI）≥24.0 kg/m 2 ， concomitant use of benzodiazepines， VPA blood concentration， hemoglobin， serum urea， average daily VPA dose， and albumin. Multivariate Logistic regression analysis showed that concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， VPA blood concentration， albumin and serum urea level （with odds ratios of 1.615， 1.538， 1.623， 1.942 and 0.637， respectively； 95% confidence intervals of 1.128-2.359， 1.059-2.251， 1.112-2.431， 1.106-3.598 and 0.402-0.980， respectively） were all significantly associated with VPA-induced hyperammonemia in neurocritical patients （ P ＜0.05）. The nomogram prediction model constructed based on these variables was evaluated， showing that the area under the ROC curve was 0.810 for the test set and 0.844 for the validation set. The calibration curves closely approximated t he actual curves， and the application of this model could improve the clinical net benefit. CONCLUSIONS Concomitant use of benzodiazepines， BMI≥24.0 kg/m 2 ， high VPA blood concentration and high albumin level are independent risk factors for VPA-induced hyperammonemia in neurocritical patients， while high serum urea level is an independent protective factor. The risk prediction model constructed based on these factors exhibits good discrimination， consistency， and clinical applicability， making it applicable for predicting the risk of VPA-induced hyperammonemia in neurocritical patients. |
| 期刊： | 2026年第37卷第08期 |
| 作者： | 徐婉；伍锦；毛娇娇；马晶晶；费姚 |
| AUTHORS： | XU Wan，WU Jin，MAO Jiaojiao，MA Jingjing，FEI Yao |
| 关键字： | 丙戊酸钠；高氨血症；风险预测模型；独立危险因素；LASSO回归分析；Logistic回归分析 |
| KEYWORDS： | sodium valproate； hyperammonemia； risk prediction model； independent risk factors； LASSO regression； Logistic |
| 阅读数： | 5 次 |
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