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Therapeutic Effects of Mesenchymal Stem Cell-Derived Extracellular Vesicles in sepsis: a Systematic Review and Meta-Analysis of Preclinical Studies

  • Amir Hossein Aghayan,
  • Yasin Mirazimi,
  • Kosar Fateh,
  • Abbasali Keshtkar,
  • Mohammad Rafiee,
  • Amir Atashi

摘要

Abstract Background

Sepsis is a life-threatening disorder with no definitive cure. Preclinical studies suggest that extracellular vesicles derived from mesenchymal stromal cells (EV-MSCs) can mitigate inflammatory conditions, potentially leading to increased survival and reduced organ dysfunction during sepsis. Our aim to conduct this systematic review and meta-analysis is assessing the EV-MSCs therapeutic efficacy in sepsis.

Methods

PubMed, Embase, Scopus, WOS and ProQuest databases and also Google Scholar search engine were searched for published articles. We used hazard ratio (HR) and standardized mean difference (SMD) as effect sizes to evaluate the therapeutic effect of EV-MSCs on survival rate and determine their effect on reducing organ dysfunction, respectively. Finally, we employed GRADE tool for preclinical animal studies to evaluate certainty of the evidence.

Results

30 studies met the inclusion criteria for our article. Our meta-analysis results demonstrate that animals treated with MSC-EVs have better survival rate than untreated animals (HR = 0.33; 95% CI: 0.27–0.41). Our meta-analysis suggests that EV-MSCs can reduce organ dysfunctions in sepsis, such as the lung, kidney, and liver. Additionally, EV-MSCs decrease pro-inflammatory mediators like TNF-α, IL-1β, and IL-6.

Conclusion

Our results indicate that EV-MSCs can be as promising therapy for sepsis management in animal models and leading to increased survival rate and reduced organ dysfunction. Furthermore, our study introduces a novel tool for risk of bias assessment and provides recommendations based on various analysis. Future studies with aiming to guide clinical translation can utilize the results of this article to establish stronger evidence for EV-MSC effectiveness.

Graphical Abstract