李和平,丁战敏,张醒,等.颅脑损伤患者营养不良的危险因素及预测模型分析[J].中华物理医学与康复杂志,2025,47(11):1011-1016
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| 颅脑损伤患者营养不良的危险因素及预测模型分析 |
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| DOI：10.3760/cma.j.cn421666-20240317-00199 |
| 中文关键词: 颅脑损伤 营养不良 预测模型 危险因素 吞咽障碍 |
| 英文关键词: Traumatic brain injury Malnutrition Prediction models Risk factors Dysphagia |
| 基金项目:中国康复医学会2023年科研立项项目（KFKT-2023-31）；2024年河南省科技厅重点研发专项（241111310600） |
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| 中文摘要: |
| 目的 探讨颅脑损伤患者营养不良的危险因素并构建预测模型以评估患者营养不良的风险。 方法 回顾性收集374例颅脑损伤患者的临床资料信息，根据其营养状况将患者分为营养不良组（220例）和对照组（154例），分别采用单因素方差分析和多因素Logistic回归分析患者营养不良的独立危险因素，并根据这些危险因素构建风险预测模型，采用受试者工作特征曲线（ROC）评价该风险模型对颅脑损伤患者营养不良的预测价值。 结果 入选患者中，共有220例患者（58.8%）发生营养不良。多因素Logistic回归分析显示，导致颅脑损伤患者营养不良的独立危险因素包括年龄≥60岁、肺部感染、吞咽障碍、认知障碍、格拉斯哥昏迷量表（GCS）评分≤8分、改良Barthel指数（MBI）评分≤40分（P＜0.05）；ROC曲线分析提示，风险预测模型的曲线下面积（AUC）为0.924（95%CI：0.896，0.951），敏感度为0.868，特异度为0.857，表明该风险模型的预测性能较好。 结论 年龄≥60岁、肺部感染、吞咽障碍、认知障碍、GCS评分≤8分、MBI评分≤40分是颅脑损伤患者营养不良的独立危险因素，基于上述危险因素构建的风险模型对颅脑损伤患者是否发生营养不良具有较好的预测价值。 |
| 英文摘要: |
| Objective To explore the risk factors for malnutrition after a traumatic brain injury and to construct a model which usefully predicts that risk. Methods This was a retrospective study of 374 patients with a craniocerebral injury for whom the relevant clinical data were available. Based on their nutritional status, they were stratified into a malnutrition group (n=220) and a control group (n=154). Univariate and multivariate logistic regressions were evaluated seeking to identify the independent risk factors associated with malnutrition, and a prediction model was constructed based on the results. The model′s discrimination ability and accuracy were assessed using a receiver operating characteristics (ROC) curve. Results A total of 220 patients (58.8%) developed malnutrition. Multifactorial logistic regression analysis showed that the independent risk factors for malnutrition were: age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8, or a Barthel index ≤40. In the ROC curve analysis, the area under the curve quantifying the model′s ability to predict malnutrition was 0.924 (95%CI: 0.896, 0.951), with a sensitivity of 0.868 and a specificity of 0.857, indicating its good prediction performance. Conclusions Age ≥60 years, pulmonary infection, dysphagia, cognitive impairment, a GCS score ≤8 or a Barthel index ≤40 are independent predictors of malnutrition after a traumatic brain injury. The prediction model constructed based on those risk factors has demonstrated useful predictive power for malnutrition. |
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