糖尿病分型新视野——基于临床表现向基于病因分子机制转变OA北大核心CSTPCD

The classification of diabetes is undergoing a significant transformation.As advancements in medical technology and a deeper understanding of its etiology,traditional classification methods based on clinical characteristics and insulin dependency are increasingly revealing their limitations.In recent years,the integration of genomic,epigenetic,and metabolomic technologies,combined with the application of big data analytics and machine learning in disease classification,has propelled diabetes classification towards enhanced precision and personalization.These cutting-edge technologies elucidate the intricate pathophysiological mechanisms and exten-sive heterogeneity inherent in diabetes,offering novel methodologies for early diagnosis,individualized treatment,and prognostic evaluation.This paradigm shift not only deepens the comprehension of diabetes complexity but also holds the potential to provide more precise and efficacious therapeutic interventions for patients.Consequently,this marks a historic transition from simplistic,clinically-based classification systems to sophisticated,molecular mechanism-based paradigms in diabetes classification.