Predicting symptomatic intracranial haemorrhage after mechanical thrombectomy: the TAG score.

Published

Journal Article

BACKGROUND: There is limited data on predictors of symptomatic intracranial haemorrhage (sICH) in patients who underwent mechanical thrombectomy. In this study, we aim to determine those predictors with external validation. METHODS: We evaluated mechanical thrombectomy in a derivation cohort of patients at a comprehensive stroke centre over a 30-month period. Clinical and radiographic data on these patients were obtained from the prospective quality improvement database. sICH was defined using the European Cooperative Acute Stroke Study III. We compared clinical and radiographic characteristics between patients with and without sICH using χ2 and t tests to identify independent predictors of sICH with p<0.1. Significant variables were then combined in a multivariate logistic regression model to derive an sICH prediction score. This score was then validated using data from the Blood Pressure After Endovascular Treatment multicentre prospective registry. RESULTS: We identified 578 patients with acute ischaemic stroke who received thrombectomy, 19 had sICH (3.3%). Predictive factors of sICH were: thrombolysis in cerebral ischaemia (TICI) score, Alberta stroke program early CT score (ASPECTS), and glucose level, and from these predictors, we derived the weighted TICI-ASPECTS-glucose (TAG) score, which was associated with sICH in the derivation (OR per unit increase 1.98, 95% CI 1.48 to 2.66, p<0.001, area under curve ((AUC)=0.79) and validation (OR per unit increase 1.48, 95% CI 1.22 to 1.79, p<0.001, AUC=0.69) cohorts. CONCLUSION: High TAG scores are associated with sICH in patients receiving mechanical thrombectomy. Larger studies are needed to validate this scoring system and test strategies to reduce sICH risk and make thrombectomy safer in patients with elevated TAG scores.

Full Text

Duke Authors

Cited Authors

  • Montalvo, M; Mistry, E; Chang, AD; Yakhkind, A; Dakay, K; Azher, I; Kaushal, A; Mistry, A; Chitale, R; Cutting, S; Burton, T; Mac Grory, B; Reznik, M; Mahta, A; Thompson, BB; Ishida, K; Frontera, J; Riina, HA; Gordon, D; Parella, D; Scher, E; Farkas, J; McTaggart, R; Khatri, P; Furie, KL; Jayaraman, M; Yaghi, S

Published Date

  • December 2019

Published In

Volume / Issue

  • 90 / 12

Start / End Page

  • 1370 - 1374

PubMed ID

  • 31427365

Pubmed Central ID

  • 31427365

Electronic International Standard Serial Number (EISSN)

  • 1468-330X

Digital Object Identifier (DOI)

  • 10.1136/jnnp-2019-321184

Language

  • eng

Conference Location

  • England