已发表论文

建立基于列线图的老年髋部骨折患者术前营养不良风险预测模型

 

Authors Li YP, Xu M, Xie HF, Zhu YC

Received 9 September 2024

Accepted for publication 18 December 2024

Published 30 December 2024 Volume 2024:17 Pages 6177—6186

DOI https://doi.org/10.2147/JMDH.S487495

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Scott Fraser

Yi-Ping Li,1 Mei Xu,1 Hao-Fen Xie,2 Ying-Chun Zhu1 

1Department of Orthopaedic Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, 315010, People’s Republic of China; 2Department of Nursing, First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, 315010, People’s Republic of China

Correspondence: Hao-Fen Xie, Department of Nursing, First Affiliated Hospital of Ningbo University, No. 59 Liuting Street, Haishu District, Ningbo, Zhejiang, 315010, People’s Republic of China, Tel +86 13867889859, Email xhaofen3049@163.com

Objective: To evaluate the risk factors contributing to preoperative malnutrition in elderly patients with hip fractures.
Methods: The study retrospectively analysed clinical data from 182 elderly patients aged 60 years or older with hip fractures. Nutritional status was assessed according to the Global Leadership Initiative on Malnutrition diagnostic criteria, and risk factors associated with malnutrition were identified through univariate and logistic regression analyses. Based on the findings, a nomogram was developed, and a calibration curve model was constructed. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve. Finally, the model was validated using an independent cohort of 78 patients.
Results: Data analysis revealed that among the 182 elderly patients with hip fractures, 76 were men and 106 were women, with a mean age of 75.77 ± 8.66 years. The fractures included 135 femoral neck fractures and 47 intertrochanteric fractures. Malnutrition was identified in 39.01% (71/182) of the patients. Independent risk factors for malnutrition included age, body mass index, the number of comorbidities, haemoglobin level and serum albumin level. A nomogram model incorporating these indicators was developed, demonstrating robust predictive performance, with an area under the ROC curve of 0.886 (95% confidence interval: 0.809– 0.962).
Conclusion: It is anticipated that the proposed model will serve as a valuable tool for the timely and accurate clinical identification of malnutrition risk in elderly patients with hip fractures.

Keywords: malnutrition, older adults, hip fracture, prediction model