Risk factors and prediction model of renal dysfunction in patients with inflammatory bowel disease: a retrospective cohort study.
9 affiliations
- 1Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310003, China.
- 2Internal Medicine Residency Program, Rochester General Hospital, 1425 Portland Avenue, Rochester, New York, USA.
- 3Department of Gastroenterology, Wenling Hospital of Wenzhou Medical University (The First People's Hospital of Wenling), Wenling, Zhejiang, China.
- 4Department of Gastroenterology, Haining People's Hospital, Haining, Zhejiang, China.
- 5Department of Gastroenterology, Affiliated Hospital of Shaoxing University, Shaoxing, Zhejiang, China.
- 6Department of Gastroenterology, Shangyu People's Hospital of Shaoxing, Shangyu, Zhejiang, China.
- 7Zhejiang Herymed Technology Co., LTD, Hangzhou, China.
- 8Hithink Flush Information Network Co., LTD, Hangzhou, China.
- 9Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310003, China. [email protected].
Abstract
Background
Previous studies have identified the association between inflammatory bowel disease (IBD) and its renal complications, but specific risk factors and predictive models remain underexplored.Aims
To identify the risk factors for renal dysfunction in IBD patients and to develop a clinical model for the early detection of high-risk individuals.Methods
This retrospective cohort study enrolled 769 patients diagnosed with IBD from a tertiary hospital for model training and internal validation, and 298 patients from four other hospitals for external validation. A Cox regression model incorporating seven selected variables, identified through LASSO regression, was developed to determine independent risk factors, and its performance was subsequently validated in both internal and external cohorts.Results
Multivariate analysis identified seven independent predictors of renal insufficiency [estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m²], including osteoporosis (HR: 1.77; P = 0.024), baseline eGFR (HR: 0.29; P < 0.001), baseline high-density lipoprotein (HDL) (HR: 0.52; P = 0.033), baseline C-reactive protein (CRP) (HR: 1.00; P = 0.09), biologic therapy (HR: 0.57; P = 0.011), enteral nutrition (HR: 1.86; P = 0.007), and intestinal surgery (HR: 1.64; P = 0.01). A predictive model was developed with a C-index of 0.719 for predicting renal insufficiency and 0.739 for predicting chronic kidney disease (eGFR < 60 mL/min/1.73 m²).Conclusions
Predictors of renal dysfunction in IBD patients included osteoporosis, eGFR, HDL, CRP, biologic therapy, enteral nutrition, and intestinal surgery. Our predictive model can effectively identify IBD populations at high risk for renal dysfunction at an early stage.
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BibTeX
@article{zhou2026risk,
title = {{Risk factors and prediction model of renal dysfunction in patients with inflammatory bowel disease: a retrospective cohort study.}},
author = {Yide Zhou and Kefang Sun and Xia Chen and Xian Shen and Junyin Chen and Liying Wang and Chunxiao Chen and Huogen Wang and Yidong Wan and Liping Yang and Lan Li},
journal = {BMC gastroenterology},
year = {2026},
month = jul,
doi = {10.1186/s12876-026-05147-z},
url = {https://europepmc.org/article/MED/42907758},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Risk factors and prediction model of renal dysfunction in patients with inflammatory bowel disease: a retrospective cohort study.
AU - Yide Zhou
AU - Kefang Sun
AU - Xia Chen
AU - Xian Shen
AU - Junyin Chen
AU - Liying Wang
AU - Chunxiao Chen
AU - Huogen Wang
AU - Yidong Wan
AU - Liping Yang
AU - Lan Li
PY - 2026
DA - 2026/07/01
JO - BMC gastroenterology
DO - 10.1186/s12876-026-05147-z
UR - https://europepmc.org/article/MED/42907758
AB - Background Previous studies have identified the association between inflammatory bowel disease (IBD) and its renal complications, but specific risk factors and predictive models remain underexplored.Aims To identify the risk factors for renal dysfunction in IBD patients and to develop a clinical model for the early detection of high-risk individuals.Methods This retrospective cohort study enrolled 769 patients diagnosed with IBD from a tertiary hospital for model training and internal validation, and 298 patients from four other hospitals for external validation. A Cox regression model incorporating seven selected variables, identified through LASSO regression, was developed to determine independent risk factors, and its performance was subsequently validated in both internal and external cohorts.Results Multivariate analysis identified seven independent predictors of renal insufficiency [estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m²], including osteoporosis (HR: 1.77; P = 0.024), baseline eGFR (HR: 0.29; P < 0.001), baseline high-density lipoprotein (HDL) (HR: 0.52; P = 0.033), baseline C-reactive protein (CRP) (HR: 1.00; P = 0.09), biologic therapy (HR: 0.57; P = 0.011), enteral nutrition (HR: 1.86; P = 0.007), and intestinal surgery (HR: 1.64; P = 0.01). A predictive model was developed with a C-index of 0.719 for predicting renal insufficiency and 0.739 for predicting chronic kidney disease (eGFR < 60 mL/min/1.73 m²).Conclusions Predictors of renal dysfunction in IBD patients included osteoporosis, eGFR, HDL, CRP, biologic therapy, enteral nutrition, and intestinal surgery. Our predictive model can effectively identify IBD populations at high risk for renal dysfunction at an early stage.
SN - 1471-230X
ER -