Clinical trajectory and disease progression in patients with cardio-renal-metabolic syndrome: the CaReMap observational study
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Federico Turoldo1, Giulia Barbati2, Cinzia Radesich3
1Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy.
Background:
Cardio-renal-metabolic (CRM) syndrome describes the pathophysiological interconnection among diabetes mellitus (DM), atherosclerotic cardiovascular disease (ASCVD) and heart failure (HF), and chronic kidney disease (CKD). Limited studies simultaneously examine progression trajectories across all three conditions at the population level. We aimed to quantify the coexistence of CRM components, with a specific focus on patients with HF, and analyse survival and disease progression in a real-world setting.
Methods:
CaReMap, an observational cohort study, analysed data from an Italian Regional Epidemiological Repository. The selection period spanned from 2017 to 2022. Incident patients had a first diagnosis of DM, HF, or CKD after January 1, 2017. Prevalent patients were classified based on their baseline morbidity status on January 1, 2017. Descriptive statistics, Kaplan-Meier survival estimates, and cumulative incidence curves for cause-specific events were reported. The CRM stage was further defined according to disease coexistence and severity.
Results:
CaReMap included 71,694 adults with established CRM-related conditions (31.8% incident; 68.2% prevalent). Among incident patients, HF was associated with the highest probability of developing an additional diagnosis (60.4% at 6 years), while CKD showed the highest probability of death before a new diagnosis (43.3% at 6 years). In prevalent patients, the DM&HF group showed the highest cumulative incidence of further diagnoses (47.1% at 6 years). Across both incident and prevalent cohorts, HF and CKD patients experienced the steepest decline in overall survival.
Conclusion:
In this population-based Italian cohort, DM, HF, and CKD define distinct diagnostic trajectories with substantial competing risk of death. These findings provide real-world estimates of transition patterns and absolute risks that may inform risk stratification and integrated care pathways.
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