ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2021
Patient-reported outcomes and the identification of subgroups of atrial fibrillation patients: a retrospective cohort study of linked clinical registry and administrative data.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Quality of life before and after catheter ablation (pulmonary vein isolation) for atrial fibrillation: Results from the Netherlands Heart Registration.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2026Article
- Longitudinal Changes in Health-Related Quality of Life in Patients With Atrial Fibrillation.Journal of the American Heart Association · 2023Observational
- Managing With Atrial Fibrillation: An Exploratory Model-Based Cluster Analysis of Clinical and Personal Patient Characteristics.CJC open · 2023Article
- Age-dependency of EHRA improvement based on quality of life at diagnosis of atrial fibrillation.Journal of arrhythmia · 2022Article
- Growth mixture models: a case example of the longitudinal analysis of patient-reported outcomes data captured by a clinical registry.BMC medical research methodology · 2021Article
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Authors and funding
4 authors.
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Abstract
purposePrevious research about the health and quality of life of people with atrial fibrillation has typically identified a single health trajectory. Our study aimed to examine variability in health trajectories and patient characteristics associated with such variability.
methodsWe conducted a retrospective analysis of data collected between 2008 and 2016 for a cardiac registry in British Columbia (Canada) linked with administrative health data. The Atrial Fibrillation Effect on Quality of Life Questionnaire was used to measure health status at up to 10 clinic visits. Growth mixture models were used and a three-step multinomial logistic regression was conducted to identify predictors of subgroups with different trajectories.
resultsThe patients (N = 7439) were primarily men (61.1%) over 60 years of age (72.9%). Three subgroups of health status trajectories were identified: "poor but improving", "good and stable", and "excellent and stable" health. Compared with the other two groups, patients in the "poor but improving group" were more likely to (1) be less than 60 years of age; (2) be women; (3) have greater risk of stroke; (4) have had ablation therapy within 6 months to 1 year or more than 2 years after their initial consultation; and (5) have had anticoagulation therapy within 6 months.
conclusionUsing growth mixture models, we found that not all health trajectories are the same. These models can help to understand variability in trajectories with different patient characteristics that could inform tailored interventions and patient education strategies.
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