DWI-Based Algorithm to Predict Disability in Patients Treated with Thrombectomy for Acute Stroke

AJNR Am J Neuroradiol. 2020 Feb;41(2):274-279. doi: 10.3174/ajnr.A6379. Epub 2020 Jan 30.

Abstract

Background and purpose: The reasons for poor clinical outcome after thrombectomy for acute stroke, concerning around half of all patients, are misunderstood. We developed a hierarchic algorithm based on DWI to better identify patients at high risk of disability.

Materials and methods: Our single-center, retrospective study included consecutive patients with acute ischemic stroke who underwent thrombectomy for large anterior artery occlusion and underwent pretreatment DWI. The primary outcome was the mRS at 3 months after stroke onset. Multivariable regression was used to identify independent clinical and imaging predictors of poor prognosis (mRS > 2) at 3 months, and a hierarchic algorithm predictive of disability was developed.

Results: A total of 149 patients were analyzed. In decreasing importance, DWI lesion volume of >80 mL, baseline NIHSS score of >14, age older than 75 years, and time from stroke onset to groin puncture of >4 hours were independent predictors of poor prognosis. The predictive hierarchic algorithm developed from the multivariate analysis predicted the risk of disability at 3 months for up to 100% of patients with a high predictive value. The area under the receiver operating characteristic curve was 0.87.

Conclusions: The DWI-based hierarchic algorithm we developed is highly predictive of disability at 3 months after thrombectomy and is easy to use in routine practice.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Algorithms*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • ROC Curve
  • Retrospective Studies
  • Risk Factors
  • Stroke / complications
  • Stroke / surgery*
  • Thrombectomy / methods*
  • Treatment Outcome*