Managing With Atrial Fibrillation: An Exploratory Model-Based Cluster Analysis of Clinical and Personal Patient Characteristics

Examining characteristics of patients with atrial fibrillation (AF) has the potential to help in identifying groups of patients who might benefit from different management approaches. Secondary analysis of online survey data was combined with clinic referral data abstraction from 196 patients with AF attending an AF specialty clinic. Cluster analyses were performed to identify distinct, homogeneous clusters of AF patients defined by 11 relevant variables: CHA2DS2-VASc score, age, AF symptoms, overall health, mental health, AF knowledge, perceived stress, household and recreation activity, overall AF quality of life, and AF symptom treatment satisfaction. Follow-up analyses examined differences between the cluster groups in additional clinical variables. Evidence emerged for both 2- and 4-cluster solutions. The 2-cluster solution involved a contrast between patients who were doing well on all variables (n = 129; 66%) vs those doing less well (n = 67; 34%). The 4-cluster solution provided a closer-up view of the data, showing that the group doing less well was split into 3 meaningfully different subgroups of patients who were managing in different ways. The final 4 clusters produced were as follows: (i) doing well; (ii) stressed and discontented; (iii) struggling and dissatisfied; and (iv) satisfied and complacent. Patients with AF can be accurately classified into distinct, natural groupings that vary in clinically important ways. Among the patients who were not managing well with AF, we found 3 distinct subgroups of patients who may benefit from tailored approaches to AF management and support. The tailoring of treatment approaches to specific personal and/or behavioural patterns, alongside clinical patterns, holds potential to improve patient outcomes (eg, treatment satisfaction). L’examen des caractéristiques des patients atteints de fibrillation auriculaire (FA) pourrait permettre de mieux cerner les groupes qui pourraient bénéficier de différentes approches de prise en charge. Nous avons combiné une analyse secondaire de données issues d’un sondage en ligne et les données issues de l’orientation clinique de 196 patients atteints de FA d’une clinique spécialisée en FA. Des analyses par grappes ont été réalisées pour cerner des groupes homogènes et distincts de patients atteints de FA, définis grâce à 11 variables pertinentes : score CHA2DS2-VASc, âge, symptômes de FA, état de santé général, état de santé mentale, niveau de connaissances sur la FA, nivea