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患者报告结局和心房颤动患者亚组的识别:基于临床注册和行政数据的回顾性队列研究。

Patient-reported outcomes and the identification of subgroups of atrial fibrillation patients: a retrospective cohort study of linked clinical registry and administrative data.

机构信息

School of Nursing, University of British Columbia, Vancouver, Canada.

School of Nursing, Trinity Western University, 22500 University Drive, Langley, BC, V2Y 1Y1, Canada.

出版信息

Qual Life Res. 2021 Jun;30(6):1547-1559. doi: 10.1007/s11136-021-02777-6. Epub 2021 Feb 12.

DOI:10.1007/s11136-021-02777-6
PMID:33580448
Abstract

PURPOSE

Previous 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSION

Using 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.

摘要

目的

先前关于心房颤动患者健康和生活质量的研究通常确定了单一的健康轨迹。我们的研究旨在检查健康轨迹的可变性以及与这种可变性相关的患者特征。

方法

我们对 2008 年至 2016 年期间不列颠哥伦比亚省(加拿大)心脏登记处与行政健康数据相关联的数据进行了回顾性分析。使用房颤对生活质量问卷来衡量多达 10 次就诊时的健康状况。使用增长混合模型,并进行了三步多项逻辑回归,以确定具有不同轨迹的亚组的预测因子。

结果

患者(N=7439)主要为 60 岁以上的男性(61.1%)(72.9%)。确定了三种健康状况轨迹亚组:“较差但改善”、“良好且稳定”和“优秀且稳定”的健康状况。与其他两组相比,“较差但改善组”的患者更有可能:(1)年龄小于 60 岁;(2)为女性;(3)有更大的中风风险;(4)在初始咨询后 6 个月至 1 年或 2 年以上接受消融治疗;(5)在 6 个月内接受抗凝治疗。

结论

使用增长混合模型,我们发现并非所有健康轨迹都是相同的。这些模型可以帮助了解具有不同患者特征的轨迹的可变性,这可以为量身定制的干预措施和患者教育策略提供信息。

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Growth mixture models: a case example of the longitudinal analysis of patient-reported outcomes data captured by a clinical registry.增长混合模型:以临床注册中心采集的患者报告结局数据的纵向分析为例
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