Περίληψη:
Why can we still not translate preclinical research to clinical treatments for acute strokes? Despite > 1000 successful preclinical studies, drugs, and concepts for acute stroke, only two have reached clinical translation. This is the translational block. Yet, we continue to routinely model strokes using almost the same concepts we have used for over 30 years. Methodological improvements and criteria from the last decade have shed some light but have not solved the problem. In this conceptual analysis, we review the current status and reappraise it by thinking “out-of-the-box” and over the edges. As such, we query why other scientific fields have also faced the same translational failures, to find common denominators. In parallel, we query how migraine, multiple sclerosis, and hypothermia in hypoxic encephalopathy have achieved significant translation successes. Should we view ischemic stroke as a “chronic, relapsing, vascular” disease, then secondary prevention strategies are also a successful translation. Finally, based on the lessons learned, we propose how stroke should be modeled, and how preclinical and clinical scientists, editors, grant reviewers, and industry should reconsider their routine way of conducting research. Translational success for stroke treatments may eventually require a bold change with solutions that are outside of the box. © Copyright © 2021 Lourbopoulos, Mourouzis, Xinaris, Zerva, Filippakis, Pavlopoulos and Pantos.
Συγγραφείς:
Lourbopoulos, A.
Mourouzis, I.
Xinaris, C.
Zerva, N.
Filippakis, K.
Pavlopoulos, A.
Pantos, C.
Λέξεις-κλειδιά:
angiotensin receptor antagonist; dipeptidyl carboxypeptidase inhibitor, Article; attrition bias; brain ischemia; cerebrovascular accident; clinical practice; conceptual framework; disease model; disease severity; experimental model; failure of translation; heart infarction; heart muscle ischemia; human; hypothermia; hypoxic ischemic encephalopathy; interdisciplinary research; medical research; migraine; multiple sclerosis; nonhuman; performance bias; polypharmacy; resuscitation; selection bias; translational block; translational research; translational success
