Novel Interactive Data Visualization: Exploration of the ESCAPE Trial (Endovascular Treatment for Small Core and Anterior Circulation Proximal Occlusion With Emphasis on Minimizing CT to Recanalization Times) Data

Stroke. 2018 Jan;49(1):193-196. doi: 10.1161/STROKEAHA.117.018814. Epub 2017 Dec 4.

Abstract

Background and purpose: The ESCAPE (Endovascular Treatment for Small Core and Anterior Circulation Proximal Occlusion With Emphasis on Minimizing CT to Recanalization Times) randomized clinical trial collected a large diverse data set. However, it is difficult to fully understand the effects of the study on certain patient groups and disease progression. We developed and evaluated an interactive visualization of the ESCAPE trial data.

Methods: We iteratively designed an interactive visualization using Python's Bokeh software library. The design was evaluated through a user study, which quantitatively evaluated its efficiency and accuracy against traditional modified Rankin Scalegraphic. Qualitative feedback was also evaluated.

Results: The novel interactive visualization of the ESCAPE data are publicly available at http://escapevisualization.herokuapp.com/. There was no difference in the efficiency and accuracy when comparing the use of the novel with the traditional visualization. However, users preferred the novel visualization because it allowed for greater exploration. Some insights obtained through exploration of the ESCAPE data are presented.

Conclusions: Novel interactive visualizations can be applied to acute stroke trial data to allow for greater exploration of the results.

Clinical trial registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01778335.

Keywords: disease progression; feedback; humans; software; stroke.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Electronic Data Processing*
  • Female
  • Humans
  • Male
  • Programming Languages*
  • Stroke* / pathology
  • Stroke* / physiopathology
  • Stroke* / therapy
  • User-Computer Interface*

Associated data

  • ClinicalTrials.gov/NCT01778335