IF 3.2 3区 医学 Q1 NURSING Journal of Clinical Nursing Pub Date : 2025-01-30 DOI:10.1111/jocn.17660
Lijie Liu, Jin Li, Liting Hu, Xiaowei Cai, Xiaoyan Li, Yang Bai
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引用次数: 0

摘要

目的:构建并验证危重症患者肠内喂养最初 7 天内肠内喂养不耐受的预测模型:方法:回顾性队列研究:我们回顾了两个重症监护病房从 2015 年 1 月到 2023 年 8 月的医疗记录,通过单变量分析和逻辑回归分析建立了一个预测模型。通过判别、校准和决策曲线分析评估了模型的性能:本研究共涉及 471 名患者,肠内喂养不耐受发生率为 35.7%。预测模型由六个变量组成,即神经系统疾病、慢性胃肠道疾病、急性生理和慢性健康评估 II 评分、镇静剂、抑酸剂和血清白蛋白。该模型显示出强大的辨别能力、校准能力和临床净效益,表明利用现成变量进行实际应用的巨大潜力:结论:该模型在评估营养初始阶段肠内喂养不耐受风险方面具有很强的预测能力:提高临床医生的能力,减少肠内喂养不耐受的发生率,改善患者预后:影响:该预测模型显示出对有肠内喂养不耐受风险的危重病人的良好识别能力,有助于提供个性化护理:报告方法:TRIPOD + AI核对表:无患者或公众贡献。试验注册:https://www.chictr.org.cn/ ChiCTR2400090757。
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Development and Validation of a Prediction Model for Enteral Feeding Intolerance in Critical Ill Patients: A Retrospective Cohort Study.

Aim: To construct and validate a prediction model for enteral feeding intolerance in critically ill patients during the first 7 days of enteral feeding.

Design: A retrospective cohort study.

Methods: We reviewed the medical records of two intensive care units from January 2015 to August 2023, to develop a prediction model by univariate analysis and logistic regression analysis. Model's performance was evaluated through discrimination, calibration and decision curve analysis.

Results: This study involved a total of 471 patients, with an enteral feeding intolerance incidence rate of 35.7%. The prediction model comprised six variables, namely neurological disease, chronic gastrointestinal disease, Acute Physiological and Chronic Health Assessment II score, sedatives, acid suppressants and serum albumin. The model showed robust discrimination, calibration and clinical net benefit, indicating significant potential for practical application with readily available variables.

Conclusions: The model demonstrated strong predictive performance in assessing the risk of enteral feeding intolerance during the early stage of nutrition initiation.

Implications for the profession and/or patient care: Enhancing clinicians' capacity to reduce the incidence of enteral feeding intolerance and improve patient outcomes.

Impact: The prediction model shows a good capacity to discriminate critically ill patients at risk of enteral feeding intolerance, is helpful to provide personalised care.

Reporting method: TRIPOD + AI checklist.

Patient or public contribution: No patient or public contribution.

Trial registration: https://www.chictr.org.cn/ ChiCTR2400090757.

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来源期刊
CiteScore
6.40
自引率
2.40%
发文量
0
审稿时长
2 months
期刊介绍: The Journal of Clinical Nursing (JCN) is an international, peer reviewed, scientific journal that seeks to promote the development and exchange of knowledge that is directly relevant to all spheres of nursing practice. The primary aim is to promote a high standard of clinically related scholarship which advances and supports the practice and discipline of nursing. The Journal also aims to promote the international exchange of ideas and experience that draws from the different cultures in which practice takes place. Further, JCN seeks to enrich insight into clinical need and the implications for nursing intervention and models of service delivery. Emphasis is placed on promoting critical debate on the art and science of nursing practice. JCN is essential reading for anyone involved in nursing practice, whether clinicians, researchers, educators, managers, policy makers, or students. The development of clinical practice and the changing patterns of inter-professional working are also central to JCN''s scope of interest. Contributions are welcomed from other health professionals on issues that have a direct impact on nursing practice. We publish high quality papers from across the methodological spectrum that make an important and novel contribution to the field of clinical nursing (regardless of where care is provided), and which demonstrate clinical application and international relevance.
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