A novel nomogram for predicting risk of malnutrition in patients with heart failure

Jian Liu; Shengjia Xu; Jiurui Wang; Jing Liu; Zeping Yan; Qian Liang; Xiaorong Luan

doi:10.3389/fcvm.2023.1162035

A novel nomogram for predicting risk of malnutrition in patients with heart failure

Front Cardiovasc Med. 2023 Mar 23:10:1162035. doi: 10.3389/fcvm.2023.1162035. eCollection 2023.

Authors

Jian Liu¹, Shengjia Xu², Jiurui Wang¹, Jing Liu¹, Zeping Yan^{1

3}, Qian Liang¹, Xiaorong Luan⁴

Affiliations

¹ School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, China.
² The First Clinical College, Shandong University, Jinan, China.
³ University of Health and Rehabilitation Sciences, Qingdao, China.
⁴ School of Nursing and Rehabilitation, Shandong University/Department of Infection Control, Qilu Hospital, Shandong University, Jinan, China.

Abstract

Background and aims: This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model.

Methods and results: A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included. Patients were divided into a malnutrition group and a normal nutrition group based on the Society's recommended AND-ASPEN standard. Logistic regression was used to analyze the independent risk factors for malnutrition. A new prediction model of nomogram was constructed based on the risk factors, and its fit and prediction performance were evaluated. Of 433 patients, 66 (15.2%) had malnutrition and 367 (84.8%) had normal nutrition, Logistic regression analyses showed that the risk factors for malnutrition were total protein, hemoglobin, triglyceride, and glucose levels. The regression model based on the above four variables showed an area under the curve of 0.858. The novel nomogram model had a sensitivity of 78.5% and a specificity of 77.3%. After 2000 bootstrap resampling iterations, AUC was 0.852.

Conclusions: The novel nomogram model can predict the odds of malnutrition in patients with heart failure at the early stage of admission, and can provide a reference for nursing staff to optimize nutritional care for inpatient with heart failure and to develop a discharge nutritional care plan.

Keywords: China; heart failure; malnutrition; nomogram; prevention.

Grants and funding

This study was sponsored by the Natural Science Foundation of Shandong Province (No. ZR2020MG071), and the Scientific research project of Chinese Nursing Association (No. ZHKY201922).