Year: 2024
Type: conference-paper
Study design: Observational Study
Abstract: Objective Basilar artery occlusions, one of the most severe of large vessel occlusions, are associated with high mortality and morbidity even with appropriate intervention.Viz.AI, a novel technology facilitating rapid live consultation and imaging review with neurointerventional clinicians, holds promise in advising on optimal treatment or transport decisions. This study aims to assess whether implementing Viz.AI at a Comprehensive Stroke Center improved patient outcomes. Patients and Methods We identified 34 patients diagnosed with basilar artery occlusion who underwent thrombectomy at our Comprehensive Stroke Center from January 2018 to January of 2022. Electronic health records were reviewed to determine Viz.AI utilization in thrombectomy activation, as well as admit and discharge National Institutes of Health Stroke Scale (NIHSS) scores. We evaluated both admit and discharge NIHSS scores and changes in scores from admission to discharge. Results For sixteen patients (47%) Viz.AI was utilized; these were compared to 18 (53%) in which Viz.AI was not used. Among the 18 patients where Viz.AI was not utilized, median admit NIHSS score was 21.5(IQR 9.3–30) and median discharge NIHSS was 17.5(IQR 4–22). The 16 patients who utilized Viz.AI had a median admit NIHSS score of 19(IQR 12–29) and a median discharge score of 1(IQR 1–4). In comparing groups, while no significant difference was found between admission NIHSS scores (p=0.96), a significant difference was found between discharge scores (p=0.006). Improvement in NIHSS score was significant highly in the Viz.AI group compared to the no-Viz.AI group. The no-Viz.AI group had a median change of 6.5(IQR 0–13) while the Viz.AI group had a median of 13(IQR 9–24); this represented a significant improvement in the Viz.AI group (p=0.04). Conclusion Following the implementation of Viz.AI at a Comprehensive Stroke Center, patients who entered with comparable deficits as measured by NIHSS scores had a significant improvement in discharge scores and change in score from admission. While multifactorial, this observation highlights the potential of Viz.AI in enhancing neurological outcomes in cases of basilar occlusions. Further investigation into surrounding factors is warranted to elucidate its full impact. Disclosures D. Williams-Stankewicz: None. E. Paulin: None. J. Frank: None. J. Lee: None. M. Campbell: None. L. Wise: None. D. Lukins: None. M. Al-Kawaz: None. D. Dornbos: None. S. Pahwa: None. J. Fraser: None.
Institution: University of Kentucky
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4400893191