Risk factors for malnutrition in ulcerative colitis complicated with pyoderma gangrenosum and construction of a lasso regression-based prediction model.
10.12122/j.issn.1673-4254.2025.03.09
- Author:
Lin SHEN
1
;
Cuihao SONG
1
;
Congmin WANG
2
;
Xi GAO
3
;
Junhong AN
4
;
Chengxin LI
1
;
Bin LIANG
5
;
Xia LI
6
Author Information
1. Department of Dermatology, First Medical Center of PLA General Hospital, Beijing 100853, China.
2. Department of Dermatology, Seventh Medical Center of PLA General Hospital, Beijing 100010, China.
3. Department of Traditional Chinese Medicine, University Town Hospital Affiliated to Chongqing Medical University, Chongqing 401331, China.
4. Department of Plastic Surgery, First Hospital of Shanxi Medical University, Taiyuan 030032, China.
5. Department of Dermatology, PLA Air Force Medical Center, Beijing 100142, China.
6. Department of Rehabilitation, First Medical Center of PLA General Hospital, Beijing 100853, China.
- Publication Type:Journal Article
- Keywords:
nutritional risk;
prediction model;
pyoderma gangrenosum;
ulcerative colitis
- MeSH:
Humans;
Colitis, Ulcerative/complications*;
Malnutrition/etiology*;
Risk Factors;
Pyoderma Gangrenosum/complications*;
Female;
Male;
Adult;
Nomograms;
Middle Aged;
Nutritional Status;
Regression Analysis
- From:
Journal of Southern Medical University
2025;45(3):514-521
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVES:To explore the risk factors for malnutrition in patients with ulcerative colitis complicated with pyoderma gangrenosum and establish a nutritional risk prediction model for these patients.
METHODS:A total of 277 patients with ulcerative colitis complicated with pyoderma gangrenosum treated from 2019 to 2024 were divided into malnutrition group (n=185) and normal nutrition group (n=92) according to whether malnutrition occurred. The data of 25 potential related factors pertaining to general demography, living and eating habits, and disease-related data were compared between the two groups. Lasso regression was used to screen the risk factors, and a nomogram model was established based on the screened factors and its prediction performance was assessed.
RESULTS:The patients in the malnutrition group and normal nutrition group showed significant differences in 21 factors including gender, age, education level, BMI, place of residence, course of disease, and SAS language score (P<0.05). Lasso regression analysis identified 6 factors associated with malnutrition in these patients, namely the duration of ulcerative colitis, activity of ulcerative colitis, duration of pyoderma gangrenosum, number of chronic diseases, SAS score, and sleep quality. The nomogram prediction model established based on these 6 factors had an AUC of 0.992 (95% CI: 0.984-1.000) for predicting malnutrition in these patients, and its application in 14 clinical cases achieved an accuracy rate of 100%.
CONCLUSIONS:The duration of ulcerative colitis, activity of colitis, duration of pyoderma gangrenosum, number of chronic diseases, anxiety, and sleep quality are closely related with malnutrition in patients with ulcerative colitis complicated by pyoderma gangrenosum, and the nomogram prediction model based on these factors can provide assistance for predicting malnutrition in these patients.
