Department of Psychiatry and Behavioral Sciences, Johns Hopkins Bayview and Johns Hopkins University, Baltimore, Maryland, USA.
Int J Methods Psychiatr Res. 2022 Dec;31(4):e1932. doi: 10.1002/mpr.1932. Epub 2022 Jul 27.
As epidemiological studies become longer and larger, the field needs novel graphical methods to visualize complex longitudinal data. The aim of this study was to present the Slinkyplot, a longitudinal crosstabulation, to illustrate patterns of antidepressant use in a large prospective cohort of older adults with mild cognitive impairment.
Data from the National Alzheimer's Coordinating Center are used to track switches between different states and types of antidepressant use. A Slinkyplot is populated with rows representing the state of medication use at each timepoint and columns representing the state at each subsequent visit.
The constructed Slinkyplots display the common practice of switching on and off different antidepressants over time, with citalopram, sertraline, and bupropion most commonly used followed by switching to another SSRI or SNRI as second-line treatment.
Slinkyplots are an innovative graphical means of visualizing complex patterns of transitions between different states over time for large longitudinal studies.
随着流行病学研究变得越来越长和越来越大，该领域需要新的图形方法来可视化复杂的纵向数据。本研究旨在介绍 Slinkyplot，一种纵向交叉表，以说明在一个大型前瞻性轻度认知障碍老年人队列中抗抑郁药使用的模式。
使用来自国家阿尔茨海默病协调中心的数据来跟踪不同状态和类型的抗抑郁药使用之间的转换。Slinkyplot 用行表示每个时间点的药物使用状态，用列表示每个后续就诊时的状态。
构建的 Slinkyplots 显示了随着时间的推移不同抗抑郁药的开和关的常见做法，西酞普兰、舍曲林和安非他酮最常用，其次是转换为另一种 SSRI 或 SNRI 作为二线治疗。
Slinkyplots 是一种创新的图形方法，用于可视化大型纵向研究中不同状态之间随时间变化的复杂转换模式。
