Pathways of Coagulopathy and Inflammatory Response in SARS-CoV-2 Infection among Type 2 Diabetic Patients.
Orsolya-Zsuzsa Akácsos-SzászSándor PálKinga-Ilona NyulasEnikő Nemes-NagyAna-Maria FárrLóránd DénesMónika SzilveszterErika-Gyöngyi BánMariana Cornelia TilincaZsuzsánna Simon SzabóPublished in: International journal of molecular sciences (2023)
Chronic inflammation and endothelium dysfunction are present in diabetic patients. COVID-19 has a high mortality rate in association with diabetes, partially due to the development of thromboembolic events in the context of coronavirus infection. The purpose of this review is to present the most important underlying pathomechanisms in the development of COVID-19-related coagulopathy in diabetic patients. The methodology consisted of data collection and synthesis from the recent scientific literature by accessing different databases (Cochrane, PubMed, Embase). The main results are the comprehensive and detailed presentation of the very complex interrelations between different factors and pathways involved in the development of arteriopathy and thrombosis in COVID-19-infected diabetic patients. Several genetic and metabolic factors influence the course of COVID-19 within the background of diabetes mellitus. Extensive knowledge of the underlying pathomechanisms of SARS-CoV-2-related vasculopathy and coagulopathy in diabetic subjects contributes to a better understanding of the manifestations in this highly vulnerable group of patients; thus, they can benefit from a modern, more efficient approach regarding diagnostic and therapeutic management.
Keyphrases
- sars cov
- coronavirus disease
- respiratory syndrome coronavirus
- inflammatory response
- type diabetes
- end stage renal disease
- oxidative stress
- newly diagnosed
- cardiovascular disease
- ejection fraction
- healthcare
- chronic kidney disease
- risk factors
- big data
- nitric oxide
- glycemic control
- metabolic syndrome
- atrial fibrillation
- lps induced
- gene expression
- patient reported outcomes
- peritoneal dialysis
- machine learning
- toll like receptor
- drug induced
- insulin resistance
- copy number
- weight loss