ArticleJournal of clinical medicine2023
Establishment and Validation of Predictive Model of Tophus in Gout Patients.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Deciphering the predictors of endometrial nonbenign lesions in asymptomatic postmenopausal women via explainable machine learning.Menopause (New York, N.Y.) · 2026Article
- Status, challenges, and prospects of artificial intelligence application in gout diagnosis and treatment, drug research and development, and disease monitoring.Frontiers in medicine · 2026Review
- Article
- The Progress of Gout Prediction Models Based on Multi-source Data.Current rheumatology reviews · 2026Review
- Early Identification of Endometrial Malignancy in Postmenopausal Women with Asymptomatic Endometrial Thickening: A Novel Explainable Machine Learning Model.International journal of medical sciences · 2026Article
- Preoperative serum Raman spectroscopy and machine learning for predicting postoperative acute kidney injury after acute type A aortic dissection.Renal failure · 2025Article
- Kiesselbach's area nasal septal gouty tophus with an integrated "3 + 2" diagnostic algorithm: a case report.Journal of medical case reports · 2025Article
- Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study.Scientific reports · 2025Article
- Gamma-Glutamyl Transferase Plus Carcinoembryonic Antigen Ratio Index: A Promising Biomarker Associated with Treatment Response to Neoadjuvant Chemotherapy for Patients with Colorectal Cancer Liver Metastases.Current oncology (Toronto, Ont.) · 2025Article
- Risk Factors for Postoperative Pain in Pterygium Surgery Patients.Journal of pain research · 2025Article
- Machine learning-based prediction of response to Ustekinumab with Crohn's disease.Therapeutic advances in gastroenterology · 2025Article
- Clinical Model Based on DR3 Promoter Methylation for Predicting Short-Term Mortality in Patients with Acute-on-Chronic Hepatitis B Liver Failure.International journal of general medicine · 2025Article
- Construction and validation of a predictive model for lymph node metastasis in patients with papillary thyroid carcinoma.Frontiers in endocrinology · 2025Article
- A nomogram model based on tumor necrosis factor-like ligand 1A(TL1A) and death receptor-3(DR3) promoter methylation for predicting 90-day prognosis in patients with HBV-associated acute-on-chronic liver failure.Frontiers in molecular biosciences · 2025Article
- Exploring Immunological Determinants and Constructing a Predictive Model for for Diagnosis of Gout: Insights Into Immune Biomarkers.Journal of inflammation research · 2025Article
- The role of cognitive function in predicting metabolic risk in schizophrenia: a multi-model comparison incorporating clinical features.Frontiers in psychiatry · 2025Article
- Interpretable machine learning for the prediction of death risk in patients with acute diquat poisoning.Scientific reports · 2024Article
- Country-specific determinants for COVID-19 case fatality rate and response strategies from a global perspective: an interpretable machine learning framework.Population health metrics · 2024Article
- Development of an interpretable machine learning model associated with genetic indicators to identify Yin-deficiency constitution.Chinese medicine · 2024Article
- Advanced gastrointestinal stromal tumor: reliable classification of imatinib plasma trough concentration via machine learning.BMC cancer · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
(1) Background: A tophus is a clinical manifestation of advanced gout, and in some patients could lead to joint deformities, fractures, and even serious complications in unusual sites. Therefore, to explore the factors related to the occurrence of tophi and establish a prediction model is clinically significant. (2) Objective: to study the occurrence of tophi in patients with gout and to construct a predictive model to evaluate its predictive efficacy. (3) Methods: The clinical data of 702 gout patients were analyzed by using cross-sectional data of North Sichuan Medical College. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze predictors. Multiple machine learning (ML) classification models are integrated to analyze and identify the optimal model, and Shapley Additive exPlanations (SHAP) interpretation was developed for personalized risk assessment. (4) Results: Compliance of urate-lowering therapy (ULT), Body Mass Index (BMI), course of disease, annual attack frequency, polyjoint involvement, history of drinking, family history of gout, estimated glomerular filtration rate (eGFR), and erythrocyte sedimentation rate (ESR) were the predictors of the occurrence of tophi. Logistic classification model was the optimal model, test set area under curve (AUC) (95% confidence interval, CI): 0.888 (0.839-0.937), accuracy: 0.763, sensitivity: 0.852, and specificity: 0.803. (5) Conclusions: We constructed a logistic regression model and explained it with the SHAP method, providing evidence for preventing tophus and guidance for individual treatment of different patients.
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