Publications by authors named "C D Rollo"
Background: There are limited therapeutic options in cases of failed reperfusion (modified thrombolysis in cerebral infarction [mTICI] score < 2b) after stent-retriever and/or aspiration based endovascular treatment (EVT) for acute ischemic stroke. Despite the absence of data supporting its use, rescue therapy (balloon angioplasty and/or stent implantation) is often utilized in such cases. Studies are limited to large vessel occlusions, while the outcomes and complications after rescue therapy in medium/distal vessel occlusions (MDVOs) have not been reported.
View Article and Find Full Text PDFBackground: Data about the safety and the efficacy of flow diversion for distal anterior cerebral artery (DACA) aneurysms are limited. We present the largest multicenter analysis evaluating the outcomes of flow diversion in unruptured DACA aneurysm treatment.
Methods: Databases from 39 centers were retrospectively reviewed for unruptured DACA aneurysms treated with flow-diverting stents.
Article Synopsis
- Beta-blockers play a key role in therapy after a heart attack (myocardial infarction), but their effectiveness for patients without reduced left ventricular function (LVEF) is under scrutiny.
- A study assessed how well patients with ST-segment elevation myocardial infarction (STEMI) adhered to beta-blocker medication after discharge, looking at the effects of adherence on health outcomes based on LVEF at discharge using data from 4,688 patients.
- Results showed that good adherence (≥80%) was linked to lower overall and heart-related deaths, particularly in patients with severely reduced LVEF (≤40%), but no significant benefit was observed in those with better LVEF.
Article Synopsis
- * Data from 459 patients with vessel perforation showed a 90-day mortality rate of 51.9%, with only 16.3% achieving a favorable recovery (mRS 0-2).
- * The findings indicate that large vessel perforation leads to worse outcomes, while thrombolysis doesn’t worsen prognoses; quick management of bleeding is crucial for survival.
Purpose: Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The development of effective classification and prognostication systems is crucial to improve the decision-making process and drive innovative treatment strategies. We have created and implemented MOSAIC, an artificial intelligence (AI)-based framework designed for multimodal analysis, classification, and personalized prognostic assessment in rare cancers.
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