[1]魏洁,张宁,李欣颢,等.重型颅脑损伤肠内营养喂养不耐受列线图预测模型的构建与评估[J].中国临床神经外科杂志,2024,29(10):599-604607.[doi:10.13798/j.issn.1009-153X.2024.10.006]
　WEI Jie,ZHANG Ning,LI Xin-hao,et al.Construction and evaluation of a nomogram model for prediction of enteral nutrition intolerance in patients with severe traumatic brain injury[J].,2024,29(10):599-604607.[doi:10.13798/j.issn.1009-153X.2024.10.006]
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重型颅脑损伤肠内营养喂养不耐受列线图预测模型的构建与评估()
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《中国临床神经外科杂志》[ISSN:1009-153X/CN:42-1603/TN]

卷:
29
期数:
2024年10期
页码:
599-604607
栏目:
论著
出版日期:
2024-10-30

文章信息/Info

Title:
Construction and evaluation of a nomogram model for prediction of enteral nutrition intolerance in patients with severe traumatic brain injury
文章编号:
1009-153X（2024）10-0599-06
作者:
魏洁; 张宁; 李欣颢; 王喜旺; 李克芬; 朱旭
056001河北，邯郸市中心医院神经外二科（魏洁、张宁、李欣颢、王喜旺、李克芬、朱旭）
Author(s):
WEI Jie;  ZHANG Ning;  LI Xin-hao;  WANG Xi-wang;  LI Ke-fen;  ZHU Xu
Department of Neurosurgery Ⅱ, Handan Central Hospital, Hebei 056001, China
关键词:
重型颅脑损伤; 肠内营养; 喂养不耐受; 危险因素; 列线图模型
Keywords:
Severe traumatic brain injury;  Enteral feeding intolerance;  Risk factors;  Nomogram model
分类号:
R 651.1+5
DOI:
10.13798/j.issn.1009-153X.2024.10.006
文献标志码:
A
摘要:
目的 探讨重型颅脑损伤肠内营养治疗过程中发生喂养不耐受（EFI）的影响因素，然后建立列线图预测模型并验证。方法 回顾性分析2019年1月至2023年1月收治的170例重型颅脑损伤的临床资料。结果 入院48 h内给予肠内营养治疗，52例发生EFI，发生率为30.6%（52/170）。多因素logistic回归分析显示，年龄较大、ICU住院时间长、低钾血症、高血糖、低GCS评分、使用机械通气、使用镇痛镇静药物是重型颅脑损伤肠内营养发生EFI的独立危险因素（P<0.05）。R软件程序包内建立并绘制列线图预测模型，绘制ROC曲线，计算曲线下面积为0.8659（95% CI 0.8072~0.9246），灵敏度为90.39%，特异度为66.95%；校准曲线与理想曲线基本重叠，Hosmer-Lemeshow拟合优度检验显示模型理想度较高；决策曲线分析显示阈概率范围为0.10~0.95时，模型表现为正的净效益，阈值范围较大，提示临床实用价值和获益度较高。结论 根据病人年龄、ICU住院时间、血钾、血糖、GCS评分、机械通气、镇痛镇静药物构建列线图模型预测重型颅脑损伤肠内营养发生EFI，具有较高的准确性和实用性。
Abstract:
Objective To investigate the risk factors of enteral feeding intolerance (EFI) during the enteral nutrition treatment for patients with severe traumatic brain injury (sTBI), and subsequently establish and validate a nomogram prediction model. Methods The clinical data of 170 patients with sTBI admitted from January 2019 to January 2023 were retrospectively analyzed. Results Enteral nutrition was administered within 48 hours of admission, and 52 patients developed EFI, with an incidence rate of 30.6% (52/170). Multivariate logistic regression analysis indicated that older age, prolonged ICU stay, hypokalemia, hyperglycemia, lower GCS score, mechanical ventilation, and the use of analgesic and sedative drugs were independent risk factors for EFI during enteral nutrition in patients with sTBI (P<0.05). A nomogram model was established using the R software, and the area under the curve of ROC was 0.8659 (95% CI 0.8072~0.9246), with a sensitivity of 90.39% and a specificity of 66.95%. The calibration curve was largely overlapping with the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test demonstrated a high degree of model ideality. Decision curve analysis revealed that when the threshold probability range was 0.10~0.95, the model exhibited a positive net benefit, with a wide threshold range, suggesting a high clinical practical value and benefit. Conclusion The nomogram model based on patient age, ICU stay, blood potassium level, blood glucose level, GCS score, mechanical ventilation, and the use of analgesic and sedative drugs for predicting EFI during enteral nutrition in patients with sTBI has high accuracy and practicality.

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备注/Memo

备注/Memo:
（2023-08-07收稿，2023-12-06修回）
通信作者：朱　旭，Email：1131352580@qq.com
更新日期/Last Update: 2024-10-30