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Kidney Disease: Improving Global Outcomes Summit Recommendations on Implementation of Diabetes Management in CKD: From Primary to Data-Driven Collaborative Care

  • Philip Kam Tao Li
  • , Michael Cheung
  • , Kai Ming Chow
  • , Maria Kwan Wa Leung
  • , Lee Ling Lim
  • , Juliana N.M. Lui
  • , Andrea O.Y. Luk
  • , Jo Anne Manski-Nankervis
  • , Samuel Seidu
  • , Nikhil Tandon
  • , Adrian Liew
  • , Peter Lin
  • , Fei Chau Pang
  • , Na Tian
  • , Kohjiro Ueki
  • , Martin C.S. Wong
  • , Sophia Zoungas
  • , Kit Man Loo
  • , Kin Lai Chung
  • , Victor Hin Fai Hung
  • Huyen Thi Thanh Vu, Maggie Lee, Junne Ming Sung, Cheuk Chun Szeto, Man Wo Tsang, Sunny Wong, Jack Kit Chung Ng, Harriet Chung, Sydney C.W. Tang, Kenny Kung, Sing Leung Lui, David V.K. Chao, Coral Cyzewski, Tanya Green, Juliana C.N. Chan

研究成果: Article同行評審

摘要

Type 2 diabetes and chronic kidney disease (CKD) are preventable and treatable. Their silent and progressive clinical course calls for structured assessment with timely feedback to patients and care providers for activating decision-making. Apart from CKD, patients with diabetes can have complications affecting multiple organs, notably the cardiovascular system, eyes, and feet. International practice guidelines recommend annual assessment of the eyes, feet, blood, and urine to detect silent complications and measure cardiovascular-kidney-metabolic (CKM) risk factors to ensure early intervention, including treatment to multiple targets and use of organ-protective drugs. In this report, we highlight the barriers and gaps in the implementation of practice guidelines in managing diabetes in CKD with proposed solutions to overcome such barriers. By improving the practice environment and workflow, nurses can be trained to perform protocol-guided evaluation under medical supervision. The systematic data collection enables physicians to make timely decisions, including drug prescriptions and referrals to other specialists to promote collaborative care, whereas nurses can use the personalized data to empower patient self-management and improve health literacy. This ongoing data collection will form a register to align payers, providers, and patients in delivering data-driven and value-based care with the creation of real-world evidence to verify treatment effectiveness and identify care gaps while providing on-the-job training. When accompanied by a biobank, the ongoing collection and analysis of this multidimensional data will refine diagnosis, classification, prognosis, and treatment in pursuit of precision medicine.

原文English
頁(從 - 到)2551-2565
頁數15
期刊Kidney International Reports
10
發行號8
DOIs
出版狀態Published - 2025 8月

UN SDG

此研究成果有助於以下永續發展目標

  1. SDG 3 - 良好的健康和福祉
    SDG 3 良好的健康和福祉

All Science Journal Classification (ASJC) codes

  • 腎臟病學

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