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Cardiovascular-Kidney-Metabolic Syndrome: Models of Care
Isaac Chung1, Dorottya I Fricska2, Suvro Banerjee3
1Renal and Transplantation Unit, St George's University Hospitals NHS Foundation Trust, SW17 0QT London, UK.
Cardiovascular-kidney-metabolic (CKM) syndrome requires integrated care. New multispecialty models improve outcomes for patients with CKM conditions by coordinating care across cardiology, nephrology, and endocrinology.
Area of Science:
- Internal Medicine
- Nephrology
- Cardiology
- Endocrinology
Background:
- Cardiovascular-kidney-metabolic (CKM) syndrome involves interconnected cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders.
- These conditions share risk factors and mechanisms, leading to organ dysfunction, increased morbidity, and mortality.
- Current disease-specific care models are inadequate for managing CKM syndrome's complexity.
Purpose of the Study:
- To review evidence on multispecialty clinics and interventions for improving care in CKM syndrome.
- To highlight the need for coordinated, patient-centered, and multidisciplinary approaches to CKM care.
- To explore how digital health, precision medicine, and analytics can support integrated CKM care models.
Main Methods:
- Synthesis of available evidence on multispecialty clinics and interventions.
- Review originated from an International Society of Nephrology Transplant Sister Center Meeting.
- Focus on improving care for patients with multiple CKM comorbidities.
Main Results:
- Traditional, fragmented care models lead to delayed treatment and poorer outcomes.
- Integrated CKM care models require cross-specialty collaboration, data sharing, and shared decision-making.
- Digital health and precision medicine offer potential for improved risk stratification and personalized interventions.
Conclusions:
- New care models are essential to address the integrated nature of CKM syndrome.
- Multidisciplinary, patient-centered approaches are crucial for optimizing treatment.
- Future CKM care should leverage technology for enhanced monitoring and personalized interventions.
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