Your browser doesn't support javascript.
loading
Machine learning-based models to predict one-year mortality among Chinese older patients with coronary artery disease combined with impaired glucose tolerance or diabetes mellitus.
Li, Yan; Guan, Lixun; Ning, Chaoxue; Zhang, Pei; Zhao, Yali; Liu, Qiong; Ping, Ping; Fu, Shihui.
Afiliação
  • Li Y; Department of Endocrinology, People's Hospital of Macheng City, Hubei, China.
  • Guan L; Hematology Department, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, China.
  • Ning C; Central Laboratory, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, China.
  • Zhang P; School of Life Science, Beijing Institute of Technology, Beijing, China.
  • Zhao Y; Central Laboratory, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, China. zhaoyl301@163.com.
  • Liu Q; Medical Care Center, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, China. liuqiong301hp@126.com.
  • Ping P; General Station for Drug and Instrument Supervision and Control, Joint Logistic Support Force of Chinese People's Liberation Army, Beijing, China. pingping301@126.com.
  • Fu S; Department of Cardiology, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, China. xiaoxiao091@126.com.
Cardiovasc Diabetol ; 22(1): 139, 2023 06 14.
Article em En | MEDLINE | ID: mdl-37316853
PURPOSE: An accurate prediction of survival prognosis is beneficial to guide clinical decision-making. This prospective study aimed to develop a model to predict one-year mortality among older patients with coronary artery disease (CAD) combined with impaired glucose tolerance (IGT) or diabetes mellitus (DM) using machine learning techniques. METHODS: A total of 451 patients with CAD combined with IGT and DM were finally enrolled, and those patients randomly split 70:30 into training cohort (n = 308) and validation cohort (n = 143). RESULTS: The one-year mortality was 26.83%. The least absolute shrinkage and selection operator (LASSO) method and ten-fold cross-validation identified that seven characteristics were significantly associated with one-year mortality with creatine, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and chronic heart failure being risk factors and hemoglobin, high density lipoprotein cholesterol, albumin, and statins being protective factors. The gradient boosting machine model outperformed other models in terms of Brier score (0.114) and area under the curve (0.836). The gradient boosting machine model also showed favorable calibration and clinical usefulness based on calibration curve and clinical decision curve. The Shapley Additive exPlanations (SHAP) found that the top three features associated with one-year mortality were NT-proBNP, albumin, and statins. The web-based application could be available at https://starxueshu-online-application1-year-mortality-main-49cye8.streamlitapp.com/ . CONCLUSIONS: This study proposes an accurate model to stratify patients with a high risk of one-year mortality. The gradient boosting machine model demonstrates promising prediction performance. Some interventions to affect NT-proBNP and albumin levels, and statins, are beneficial to improve survival outcome among patients with CAD combined with IGT or DM.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença da Artéria Coronariana / Intolerância à Glucose / Inibidores de Hidroximetilglutaril-CoA Redutases / Diabetes Mellitus Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença da Artéria Coronariana / Intolerância à Glucose / Inibidores de Hidroximetilglutaril-CoA Redutases / Diabetes Mellitus Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article