Outcomes in Atrial Fibrillation Patients with Different Clinical Phenotypes: Insights from the French Population

<b>Background</b>: Atrial fibrillation (AF) patients represent a clinically complex, heterogeneous population comprising multiple homogeneous cohorts. <b>Purpose:</b> We aimed to identify the common clinical phenotypes of AF patients and compare clinical outcomes between these subgroups. <b>Methods:</b> A 1% representative sample of all AF patients hospitalized between 2010 and 2019 was identified from the French national database. Agglomerative hierarchical cluster analysis was performed using Ward's method and squared Euclidian distance to derive the clusters of patients. Cox regression analyses were used to evaluate outcomes including all-cause death, cardiovascular death, non-cardiovascular death, ischemic stroke, hospitalization for heart failure (HF) and composite of ventricular tachycardia, ventricular fibrillation and cardiac arrest (VT/VF/CA) over a mean follow-up period of 2.0 ± 2.3 years. <b>Results:</b> Four clusters were generated from the 12,688 patients included. Cluster 1 (<i>n</i> = 2375) was younger, low cardiovascular disease (CVD)-risk group with a high cancer prevalence. Clusters 2 (<i>n</i> = 6441) and 3 (<i>n</i> = 1639) depicted moderate-risk groups for CVD. Cluster 3 also had the highest degree of frailty and lung disease while Cluster 4 (<i>n</i> = 2233) represented a high-risk cohort for CVD. After adjusting for confounders, with cluster 1 as the reference, cluster 3 had the highest risk of all-cause death, HR 1.24 (1.09-1.41), ARD (10.3%), cardiovascular death, HR 1.56 (1.19-2.06), ARD (3.3%), non-cardiovascular death, HR 1.20 (1.04-1.38), ARD (6.9%), hospitalization for HF, HR 2.07 (1.71-2.50), ARD (9.1%) and VT/VF/CA, HR 1.74 (1.20-2.53), (ARD 1.3%). <b>Conclusions:</b> Four distinct clusters of AF patients were identified, discriminated by the differential presence of comorbidities. Our findings suggest that hospitalized AF patients with moderate CVD risk may have a poorer prognosis compared to hospitalized AF patients with high CVD risk in the presence of lung pathology and frailty. This subgroup of patients may require more stringent management of existing comorbidities such as chronic obstructive pulmonary disease and sleep apnea, alongside their AF.

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Journal
Journal of Clinical Medicine
Published
2025-02-07
DOI
https://doi.org/10.3390/jcm14041044
Citations
2
Primary Topic
Atrial Fibrillation Management and Outcomes
Type
article
Field-Weighted Citation Impact
2.78
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article

Outcomes in Atrial Fibrillation Patients with Different Clinical Phenotypes: Insights from the French Population

Thibault Lenormand, Gregory Y.H. Lip, Ameenathul M. Fawzy, Laurent Fauchier et al.
2 citations
Journal of Clinical Medicine
Atrial Fibrillation Management and Outcomes
2.78
article

Outcomes in Atrial Fibrillation Patients with Different Clinical Phenotypes: Insights from the French Population

Thibault Lenormand, Gregory Y.H. Lip, Ameenathul M. Fawzy, Laurent Fauchier, Arnaud Bisson, Lisa Lochon
article en
2 citations

Abstract

<b>Background</b>: Atrial fibrillation (AF) patients represent a clinically complex, heterogeneous population comprising multiple homogeneous cohorts. <b>Purpose:</b> We aimed to identify the common clinical phenotypes of AF patients and compare clinical outcomes between these subgroups. <b>Methods:</b> A 1% representative sample of all AF patients hospitalized between 2010 and 2019 was identified from the French national database. Agglomerative hierarchical cluster analysis was performed using Ward's method and squared Euclidian distance to derive the clusters of patients. Cox regression analyses were used to evaluate outcomes including all-cause death, cardiovascular death, non-cardiovascular death, ischemic stroke, hospitalization for heart failure (HF) and composite of ventricular tachycardia, ventricular fibrillation and cardiac arrest (VT/VF/CA) over a mean follow-up period of 2.0 ± 2.3 years. <b>Results:</b> Four clusters were generated from the 12,688 patients included. Cluster 1 (<i>n</i> = 2375) was younger, low cardiovascular disease (CVD)-risk group with a high cancer prevalence. Clusters 2 (<i>n</i> = 6441) and 3 (<i>n</i> = 1639) depicted moderate-risk groups for CVD. Cluster 3 also had the highest degree of frailty and lung disease while Cluster 4 (<i>n</i> = 2233) represented a high-risk cohort for CVD. After adjusting for confounders, with cluster 1 as the reference, cluster 3 had the highest risk of all-cause death, HR 1.24 (1.09-1.41), ARD (10.3%), cardiovascular death, HR 1.56 (1.19-2.06), ARD (3.3%), non-cardiovascular death, HR 1.20 (1.04-1.38), ARD (6.9%), hospitalization for HF, HR 2.07 (1.71-2.50), ARD (9.1%) and VT/VF/CA, HR 1.74 (1.20-2.53), (ARD 1.3%). <b>Conclusions:</b> Four distinct clusters of AF patients were identified, discriminated by the differential presence of comorbidities. Our findings suggest that hospitalized AF patients with moderate CVD risk may have a poorer prognosis compared to hospitalized AF patients with high CVD risk in the presence of lung pathology and frailty. This subgroup of patients may require more stringent management of existing comorbidities such as chronic obstructive pulmonary disease and sleep apnea, alongside their AF.

Journal of Clinical MedicineVol. 14(4)
Université de Tours (FR), Université d'Orléans (FR), University of Liverpool (GB), Liverpool Heart and Chest Hospital (GB), Liverpool John Moores University (GB)
Good health and well-being
Openalex Percentile: Top 12%
Atrial Fibrillation Management and Outcomes
2.78
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