The loss of chance doctrine can be a strong tool for plaintiffs to recover damages when a physician’s failure to follow a certain course of treatment resulted in the patient losing the opportunity of a better outcome. It is important to consult with qualified legal counsel in the local jurisdiction to ascertain whether it applies, and with what potential nuances.
Stroke is a common problem, affecting nearly 800,000 people annually in the United States and serving as a leading cause of significant long-term disability. This article begins with a brief discussion of stroke epidemiology and then provides an overview of the various stroke mechanisms, setting a framework for which to consider etiology-specific stroke management.
Vulnerable stroke patients often are transitioned home, which can create challenges and the continued need for case management or follow-up care. Researchers studied these transitions in a pragmatic trial to see if health systems would implement transitional care for certain stroke patients.
Since 2015, when multiple international trials were reported showing clear benefit for mechanical thrombectomy in patients with large vessel occlusions, this treatment has been the standard of care. However, the speed of treatment remains paramount for good outcomes, and different models have been developed around the world in different geographic settings.
Ticagrelor is an antiplatelet agent that works by reversibly binding to P2Y12 adenosine diphosphate receptors on platelets, similar to the mechanism of action of clopidogrel. However, it is a direct-acting drug, and not a pro-drug, and does not need to be enzymatically converted to be active, like clopidogrel.
Since the pivotal trials demonstrating the benefit of endarterectomy vs. medical therapy many years ago, there has been significant improvement in the risk factors for atherosclerosis, including better treatment of blood pressure and diabetes, as well as improved antiplatelet medication regimens and high-potency statins.
Strokes, especially posterior circulation events, are associated with significant diagnostic error in the ED. Machine learning models can be designed to capture subtle signs and assist providers in catching cases that might otherwise go undetected.