Thrombectomy of Ventricular Assist Device-Originated Embolic Stroke: A Clinical Decision Model. Journal Article

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Authors: Colletta, KL; Bar, B; Liebo, MJ; Borys, E; Schneck, MJ; Gomez, CR
Article Title: Thrombectomy of Ventricular Assist Device-Originated Embolic Stroke: A Clinical Decision Model.
Abstract: BACKGROUND AND PURPOSE: The use of ventricular assist devices (VADs) for the treatment of heart failure has become increasingly common. These patients have a considerable risk of cerebral embolism. We describe such a patient and his successful treatment by thrombectomy, compare his attributes with those previously published, and describe the construct of a clinical decision model, whose results bear practical implications for patient management. METHODS: The details of our patient and his treatment are presented, followed by a literature review of all previously reported similar cases. Using this information, as well as that available from published series, we constructed a probabilistic decision tree, completed all calculations (ie, "folding back"), and, in order to assess the strength of the results, subjected them to multiple independent sensitivity analyses of each of the variables. RESULTS: The therapeutic success of our case, the 14th reported to date, when combined with previous reports, shows: (1) recanalization times of 184 minutes, (2) "successful" recanalization (ie, TICI = 2b or 3) achieved in 71% of procedures, (3) ultimate functional outcome (ie, mRS = 0-2) achieved in 57% patients, and (4) ultimate successful heart transplantations in 66% of cases. The clinical decision model showed the predicted utility of thrombectomy to be superior to conservative management (3.33 QALY vs. 2.56 QALY, respectively). The sensitivity analyses support the validity of these results. CONCLUSIONS: In conclusion, thrombectomy appears to be a safe and effective method (and often the only viable one) for urgent treatment of patients with VAD-originated cerebral embolism.
Journal Title: Journal of neuroimaging : official journal of the American Society of Neuroimaging
ISSN: 1552-6569; 1051-2284
Publisher: Unknown  
Date Published: 2019