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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:p>Cognitive impairment, depression and (mental) fatigue represent the most frequent neuropsychiatric symptoms of the post-COVID syndrome. Neuroinflammation, oxidative stress and mitochondrial dysfunction have been identified as common pathophysiological mechanisms underlying these symptoms. Attempts to treat post-COVID-associated cognitive impairment and fatigue with different drugs available for other diseases have not yet been successful. One probable explanation could be that these drugs work by one specific mechanism of action only and not in a broad multi-target way. Therefore, they will not address the broad pathophysiological spectrum possibly responsible for cognitive impairment, depression and fatigue in post-COVID syndrome. Notably, nearly all drugs currently under investigation for fatigue in post-COVID syndrome are rather addressing one single target instead of the several pathomechanisms underlying this condition. Contrary to this approach, herbal drugs often consist of many different ingredients with different pharmacological properties and pharmacological targets. Therefore, these drugs might be a promising approach for the treatment of the broad symptomatic presentation and the pathophysiological mechanisms of cognitive impairment and fatigue following a SARS-CoV-2 infection. Of these herbal drugs, extracts of <jats:italic>Ginkgo biloba</jats:italic> and <jats:italic>Rhodiola rosea</jats:italic> probably are the best investigated candidates. Their broad pharmacological spectrum in vitro and in vivo includes anti-oxidative, anti-inflammatory, antidepressant as well as properties reducing cognitive impairment and fatigue. In several studies, both drugs showed positive effects on physical and mental fatigue and impaired cognition. Moreover, depressive symptoms were also reduced in some studies. However, even if these results are promising, the data are still preliminary and require additional proof by further studies.</jats:p>
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1000
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Hinweis
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DeepGreen-ID: c9ae98580bfc4b9082ec0129c6546730 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search) ;
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