Construction and regional application of an integrated model for early screening and tiered management of chronic kidney disease.

Background: Chronic kidney disease (CKD) has emerged as a leading chronic condition contributing to global mortality and disability. Its early stages are often asymptomatic, leading to delayed detection. In China's western ethnic minority regions, characterized by geographical dispersion, insufficient primary healthcare resources, and relatively low public health literacy, the early identification and effective management of CKD face more complex challenges. Objective: Focusing on the Qiandongnan Miao and Dong Autonomous Prefecture in Guizhou Province as the study area, this research aimed to construct an integrated model for CKD early screening and tiered management adapted to regional characteristics. It sought to identify key barrier factors and assess the feasibility and application potential of the model in real-world primary care settings. Methods: Employing a multi-data source study design combining cross-sectional surveys with integrated real-world clinical data, the study was conducted in Qiandongnan Prefecture. Data collection involved public questionnaires ( Results: Overall public CKD awareness was low, and screening behavior participation was limited; however, a significant positive correlation existed between the two. Primary healthcare workers exhibited stratified competency in risk assessment, indicator application, and management pathway knowledge. ACR testing rates were constrained by both behavioral willingness and technical resource limitations. Most CKD patients were in G1-G2 stages, with primary glomerular diseases constituting the predominant pathological type. The integrated model demonstrated good operational feasibility in optimizing screening pathways and enhancing tiered management capacity. Conclusion: The integrated CKD early screening and tiered management model constructed in Qiandongnan Prefecture demonstrates the feasibility of linking behavioral, institutional, and clinical dimensions for early detection and management, as it integrates public awareness, primary care capacity, and clinical data into a unified framework. Its methodological contribution lies in the use of multi-source data and latent class analysis, while its practical contribution includes the identification of critical breakpoints and actionable recommendations for screening, ACR testing, and health education. Future directions should focus on longitudinal validation, application in other regions, and incorporation of advanced predictive models, and results should be interpreted in the context of regional characteristics and resource limitations.