Development and validation of a point‐of‐care nursing mobile tool to guide the diagnosis of malnutrition in hospitalized adult patients: a multicenter, prospective cohort study
Nan Lin,
Xueyan Zhou,
Weichang Chen,
Chengyuan He,
Xiaoxuan Wang,
Yuhao Wei,
Zhiwen Long,
Tao Shen,
Lingyu Zhong,
Chan Yang,
Tingting Dai,
Hao Zhang,
Hubing Shi,
Xuelei Ma
Affiliations
Nan Lin
Department of Biotherapy Cancer Center West China Hospital, Sichuan University Chengdu China
Xueyan Zhou
Department of Biotherapy State Key Laboratory of Biotherapy, Frontiers Science Center for Disease‐related Molecular Network, West China Hospital, and Key Laboratory of Bio‐Resource and Eco‐Environment of Ministry of Education, College of Life Sciences, Sichuan University Chengdu Sichuan China
Weichang Chen
State Key Laboratory of Oral DiseasesNational Clinical Research Center for Oral Diseases, Sichuan UniversityChengdu China
Chengyuan He
Recovery Plus Clinic Chengdu China
Xiaoxuan Wang
Department of Biotherapy Cancer Center West China Hospital, Sichuan University Chengdu China
Yuhao Wei
Department of Biotherapy Cancer Center West China Hospital, Sichuan University Chengdu China
Zhiwen Long
Recovery Plus Clinic Chengdu China
Tao Shen
Department of Colorectal Surgery The Third Affiliated Hospital of Kunming Medical University/Yunnan Tumor Hospital Kunming China
Lingyu Zhong
Department of Clinical NutritionHospital of Chengdu Office of People’s Government of Tibetan Autonomous RegionChengdu China
Chan Yang
Division of Endocrinology and Metabolism State Key Laboratory of Biotherapy, West China Hospital, Sichuan University Chengdu China
Tingting Dai
Department of Clinical Nutrition West China Hospital, Sichuan University Chengdu China
Hao Zhang
Division of Pancreatic Surgery Department of General Surgery West China Hospital, Sichuan University Chengdu China
Hubing Shi
Laboratory of Integrative MedicineClinical Research Center for Breast, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and Collaborative Innovation CenterChengdu Sichuan China
Xuelei Ma
Department of Biotherapy Cancer Center West China Hospital, Sichuan University Chengdu China
Abstract Malnutrition is a prevalent and severe issue in hospitalized patients with chronic diseases. However, malnutrition screening is often overlooked or inaccurate due to lack of awareness and experience among health care providers. This study aimed to develop and validate a novel digital smartphone‐based self‐administered tool that uses facial features, especially the ocular area, as indicators of malnutrition in inpatient patients with chronic diseases. Facial photographs and malnutrition screening scales were collected from 619 patients in four different hospitals. A machine learning model based on back propagation neural network was trained, validated, and tested using these data. The model showed a significant correlation (p < 0.05) and a high accuracy (area under the curve 0.834–0.927) in different patient groups. The point‐of‐care mobile tool can be used to screen malnutrition with good accuracy and accessibility, showing its potential for screening malnutrition in patients with chronic diseases.
