Your browser doesn't support javascript.
loading
Prediction of delayed reperfusion in patients with incomplete reperfusion following thrombectomy.
Mujanovic, Adnan; Brigger, Robin; Kurmann, Christoph C; Ng, Felix; Branca, Mattia; Dobrocky, Tomas; Meinel, Thomas R; Windecker, Daniel; Almiri, William; Grunder, Lorenz; Beyeler, Morin; Seiffge, David J; Pilgram-Pastor, Sara; Arnold, Marcel; Piechowiak, Eike I; Campbell, Bruce; Gralla, Jan; Fischer, Urs; Kaesmacher, Johannes.
Afiliación
  • Mujanovic A; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Brigger R; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Kurmann CC; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Ng F; Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Branca M; Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
  • Dobrocky T; CTU Bern, University of Bern, Bern, Switzerland.
  • Meinel TR; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Windecker D; Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Almiri W; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Grunder L; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Beyeler M; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Seiffge DJ; Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Pilgram-Pastor S; Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Arnold M; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Piechowiak EI; Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Campbell B; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Gralla J; Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
  • Fischer U; Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bern, University of Bern, Bern, Switzerland.
  • Kaesmacher J; Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland.
Eur Stroke J ; 8(2): 456-466, 2023 06.
Article en En | MEDLINE | ID: mdl-37231686
ABSTRACT

BACKGROUND:

The clinical course of patients with incomplete reperfusion after thrombectomy, defined as an expanded Thrombolysis in Cerebral Infarction (eTICI) score of 2a-2c, is heterogeneous. Patients showing delayed reperfusion (DR) have good clinical outcomes, almost comparable to patients with ad-hoc TICI3 reperfusion. We aimed to develop and internally validate a model that predicts DR occurrence in order to inform physicians about the likelihood of a benign natural disease progression. PATIENTS AND

METHODS:

Single-center registry analysis including all consecutive, study-eligible patients admitted between 02/2015 and 12/2021. Preliminary variable selection for the prediction of DR was performed using bootstrapped stepwise backward logistic regression. Interval validation was performed with bootstrapping and the final model was developed using a random forests classification algorithm. Model performance metrics are reported with discrimination, calibration, and clinical decision curves. Primary outcome was concordance statistics as a measure of goodness of fit for the occurrence of DR.

RESULTS:

A total of 477 patients (48.8% female, mean age 74 years) were included, of whom 279 (58.5%) showed DR on 24 follow-up. The model's discriminative ability for predicting DR was adequate (C-statistics 0.79 [95% CI 0.72-0.85]). Variables with strongest association with DR were atrial fibrillation (aOR 2.06 [95% CI 1.23-3.49]), Intervention-To-Follow-Up time (aOR 1.06 [95% CI 1.03-1.10]), eTICI score (aOR 3.49 [95% CI 2.64-4.73]), and collateral status (aOR 1.33 [95% CI 1.06-1.68]). At a risk threshold of R = 30%, use of the prediction model could potentially reduce the number of additional attempts in one out of four patients who will have spontaneous DR, without missing any patients who do not show spontaneous DR on follow-up.

CONCLUSIONS:

The model presented here shows fair predictive accuracy for estimating chances of DR after incomplete thrombectomy. This may inform treating physicians on the chances of a favorable natural disease progression if no further reperfusion attempts are made.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Accidente Cerebrovascular Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male Idioma: En Revista: Eur Stroke J Año: 2023 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Accidente Cerebrovascular Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male Idioma: En Revista: Eur Stroke J Año: 2023 Tipo del documento: Article País de afiliación: Suiza