Mehraeen E, Abbaspour F, Banach M, SeyedAlinaghi S, Zarebidoki A, Tamehri Zadeh SS. The prognostic significance of insulin resistance in COVID-19: a review.
J Diabetes Metab Disord 2024;
23:305-322. [PMID:
38932824 PMCID:
PMC11196450 DOI:
10.1007/s40200-024-01385-8]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 12/31/2023] [Indexed: 06/28/2024]
Abstract
Objectives
Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19.
Method
The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19.
Results
We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients.
Conclusion
Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.
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