老年重症脑卒中病人再喂养综合征风险预测模型的构建和验证

doi:10.3969/j.issn.1003-9198.2025.08.018

摘要/Abstract

摘要： 目的探讨老年重症脑卒中病人再喂养综合征(RFS)的风险因素,并构建列线图预测模型。方法采用便利抽样法选取2023年8月至2024年9月南京市第一医院收治的老年重症脑卒中病人作为调查对象,根据是否发生RFS分为RFS组和非RFS组。收集病人一般资料情况、营养风险评估量表2022(NRS2002)评分、肠内营养耐受性评分及NIHSS得分。采用多因素logistic回归分析RFS的独立相关因素,并构建列线图预测模型,通过ROC曲线、校准曲线以及Hosmer-Lemeshow(HL)拟合优度检验评价模型的性能。结果共纳入253例病人,其中54例发生RFS,发生率为21.34％。再喂养中补充蛋白质、再喂养前血清白蛋白浓度低、NRS2002评分高、肠内营养耐受性评分高、BMI<18.5是老年重症脑卒中病人发生RFS的独立危险因素(P＜0.05)。预测模型ROC曲线下面积为0.897(95%CI:0.835~0.958),约登指数为0.714,敏感度为0.940,特异度为0.774。HL检验显示模型拟合度较高,校准曲线显示较好的一致性。结论该列线图模型具有良好的拟合度和较高的预测性能,临床护理人员应重点关注BMI＜18.5,再喂养中额外补充蛋白质、再喂养前血清白蛋白浓度较低、营养状况和肠内营养耐受性差的老年病人,并根据病人的预测概率采取针对性的干预措施。

关键词: 重症, 脑卒中, 老年人, 再喂养综合征, 风险预测模型

Abstract: Objective To explore the risk factors of refeeding syndrome (RFS) in the elderly patients with severe stroke, and to construct a risk prediction model to guide clinical assessment. Methods Convenience sampling was used to enroll the elderly patients with severe stroke admitted to Nanjing First Hospital from August 2023 to September 2024 in the study. The participants were divided into RFS group and non-RFS group based on RFS occurrence, and their general information, and the scores of nutrition risk screening (NRS) 2002, enteral nutrition (EN) tolerance, and National Institutes of Health Stroke Scale (NIHSS)were collected.Multiple logistic regression analysis was used to investigate the influencing factors of RFS, and a prediction model for RFS was developed.The performance of the model was evaluated by receiver operating characteristic (ROC) curve, calibration curve and Hosmer-Lemeshow (HL) fit goodness test. Results A total of 253 patients were enrolled, and 54(21.34%) of them presented with RFS. Protein supplementation during refeeding, pre-refeeding serum level of albumin, NRS2002 score, EN tolerance score, and BMI<18.5 were independent influencing factors for RFS in the elderly patients with severe stroke (P<0.05). The area under the ROC curve of the predictive model was 0.897 (95% CI :0.835－0.958), with a maximum Youden index of 0.714, sensitivity of 0.940, and specificity of 0.774. The HL test showed a high degree of model fit, and the calibration curve showed good consistency. Conclusions The model shows good fit and high predictive performance. Clinical nursing staff should focus on elderly patients with BMI<18.5, additional protein supplementation during refeeding, low pre-refeeding serum albumin concentration and elevated NRS2002 score or EN tolerance score.

Key words: severe illness, stroke, aged, refeeding syndrome, risk prediction model

中图分类号:

R743.3

薄磊, 胡樱, 陆敏. 老年重症脑卒中病人再喂养综合征风险预测模型的构建和验证[J]. 实用老年医学, 2025, 39(8): 842-846.

BO Lei, HU Ying, LU Min. Construction and validation of a risk prediction model for refeeding syndrome in elderly patients with severe stroke[J]. Practical Geriatrics, 2025, 39(8): 842-846.

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