Data-Driven Identification of Long-Term Glycemia Clusters and Their Individualized Predictors in Finnish Patients with Type 2 Diabetes.

Piia Lavikainen,Gunjan Chandra,Pekka Siirtola,Satu Tamminen,Anusha T Ihalapathirana,Juha Röning,Tiina Laatikainen,Janne Martikainen

Clinical epidemiology（2023）

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摘要

Heterogeneity in long-term glycemic control can be predicted with confidence by utilizing information from previous HbA1c levels, fasting plasma glucose, duration of T2D, and use of antidiabetic medications. In future, the expected development of HbA1c could be predicted based on the patient's unique risk factors offering a practical tool for clinicians to support treatment planning.

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关键词

HbA1c,SHAP,cluster,machine learning,type 2 diabetes

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