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Published on: July 20, 2022
Evaluation of the ABC pathway in patients with atrial fibrillation: A machine learning cluster analysis
Jingyang Wang1, Haiyang Bian2, Jiangshan Tan1
1Emergency and Critical Care Center, Fuwai Hospital, National Center for Cardiovascular Diseases of China, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Insights
The Atrial Fibrillation Better Care (ABC) pathway effectively reduces adverse outcomes in Chinese atrial fibrillation (AF) patients. Tailoring management to distinct patient clusters optimizes care and improves outcomes.
Area of Science:
- Cardiology
- Public Health
- Genetics
Background:
- The Atrial Fibrillation Better Care (ABC) pathway is guideline-recommended for managing atrial fibrillation (AF).
- Its effectiveness across diverse Chinese patient populations requires systematic evaluation.
- Understanding variations in ABC pathway efficacy is crucial for optimizing AF patient care.
Purpose of the Study:
- To evaluate the effectiveness of the ABC pathway across diverse patient groups in China.
- To identify patient clusters based on clinical characteristics.
- To assess the impact of ABC pathway adherence on adverse outcomes within these clusters.
Main Methods:
- Utilized data from an observational cohort of 2,016 AF patients.
- Employed cluster analysis on 45 baseline variables to identify patient phenotypes.
- Evaluated management patterns, adverse outcomes, and the effectiveness of ABC criteria adherence.
Main Results:
- Identified three distinct AF patient clusters: elderly with comorbidities, young females with valve comorbidities, and low-comorbidity paroxysmal AF patients.
- Significant differences in major adverse cardiovascular and neurological events (MACNE), mortality, and stroke were observed among clusters.
- Full adherence to the ABC pathway significantly reduced MACNE risk across all identified clusters.
Conclusions:
- The study highlights the need for tailored risk stratification and integrated management strategies for different AF patient groups.
- Considering clinical, genetic, and socioeconomic factors is essential for optimizing AF patient care.
- Specific optimization strategies can enhance the effectiveness of the ABC pathway in diverse Chinese AF populations.
Background:
Atrial fibrillation Better Care (ABC) pathway is recommended by guidelines on atrial fibrillation (AF) and exerts a protective role against adverse outcomes of AF patients. But the possible differences in its effectiveness across the diverse range of patients in China have not been systematically evaluated. We aim to comprehensively evaluate multiple clinical characteristics of patients, and probe clusters of ABC criteria efficacy in patients with AF.
Methods:
We used data from an observational cohort that included 2,016 patients with AF. We utilized 45 baseline variables for cluster analysis. We evaluated the management patterns and adverse outcomes of identified phenotypes. We assessed the effectiveness of adherence to the ABC criteria at reducing adverse outcomes of phenotypes.
Results:
Cluster analysis identified AF patients into three distinct groups. The clusters include Cluster 1: old patients with the highest prevalence rates of atherosclerotic and/or other comorbidities (n = 964), Cluster 2: valve-comorbidities AF in young females (n = 407), and Cluster 3: low comorbidity patients with paroxysmal AF (n = 644). The clusters showed significant differences in MACNE, all-cause death, stroke, and cardiovascular death. All clusters showed that full adherence to the ABC pathway was associated with a significant reduction in the risk of MACNE (all P < 0.05). For three clusters, adherence to the different 'A'/'B'/'C' criterion alone showed differential clinic impact.
Conclusion:
Our study suggested specific optimization strategies of risk stratification and integrated management for different groups of AF patients considering multiple clinical, genetic and socioeconomic factors.
