Stroke: Vascular and Interventional Neurology (Mar 2023)

Abstract Number ‐ 95: Common Data Elements Analysis of Mechanical Thrombectomy Clinical Trials for Acute Ischemic Large Core Stroke

  • Mohamed Sobhi Jabal,
  • Mohamed Ibrahim,
  • Jade Thurnham,
  • Kevin Kallmes,
  • Hassan Kobeissi,
  • Sherief Ghozy,
  • Nicole Hardy,
  • Ranita Tarchand,
  • Cem Bilgin,
  • Jeremy Heit,
  • Waleed Brinjikji,
  • David Kallmes

DOI
https://doi.org/10.1161/SVIN.03.suppl_1.095
Journal volume & issue
Vol. 3, no. S1

Abstract

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Introduction Various clinical trials addressing large core acute ischemic stroke (AIS) are ongoing from multiple international groups. Future development of clinical guidelines depends on meta‐analyses of these trials calling for a degree of homogeneity of elements across the different studies. The aim of this common data element study was to provide an overview of the key features of pertinent large core infarct trials. Methods PubMed and ClinicalTrials.gov databases were screened for published and ongoing clinical trials assessing mechanical thrombectomy in patients with AIS with large core infarct. Nested Knowledge AutoLit living review platform was utilized to categorize primary and secondary outcomes as well as inclusion and exclusion criteria for patient selection in the clinical trials. Results The most reported data element was ASPECTS score, but with varied definitions of what compromises large core. Non‐utility‐weighted modified Rankin Score (mRS) was reported in 6/7 studies as the primary outcome, while the utility‐weighted mRS was the outcome of interest in the TESLA trial, all of them at the 3‐months mark, with only LASTE looking for mRS shift at the 6‐months mark. Secondary outcomes had more variations. Mortality is reported separately only in 4/7 trials, all at the 3‐month mark. Additionally, the TENSION trial reports the frequency of serious adverse events, including mortality, at the 1‐week and 12‐month mark. Conclusions In the published and the ongoing large core trials, there is a large degree of variability in the collected data elements. Differences in definition and timepoints renders reaching a unified standard difficult, which hinders high quality meta‐analyses and cohesive evidence‐driven synthesis.