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Association between Rhesus Blood Groups and Malaria Infection: A Systematic Review and Meta-Analysis.

Yanisa RattanapanThitinat DuangchanKinley WangdiAongart MahittikornManas Kotepui
Published in: Tropical medicine and infectious disease (2023)
In the literature, there was inconsistency in the risk of malaria between individuals with Rhesus blood group positive (Rh+) and negative (Rh-). The systematic review aimed to investigate the risk of malaria among participants with different Rh blood types. All observational studies that reported the occurrence of Plasmodium infection and investigation of the Rh blood group were searched in five databases (Scopus, EMBASE, MEDLINE, PubMed, and Ovid). Strengthening the Reporting of Observational Studies in Epidemiology was used to assess the reporting quality in the included studies. A random-effects model was used to calculate the pooled log OR and 95% confidence intervals (CIs). Database searches yielded a total of 879 articles, of which 36 were eligible for inclusion in the systematic review. The majority of the included studies (44.4%) revealed that Rh+ individuals had a lower proportion of malaria than Rh- individuals; however, the remaining studies revealed a higher or no difference in the proportion of malaria between Rh+ and Rh- individuals. Overall, with moderate heterogeneity, the pooled results showed no difference in malaria risk between patients with Rh+ and Rh- ( p = 0.85, pooled log OR: 0.02, 95% CI: -0.20-0.25, I 2 : 65.1%, 32 studies). The current study found no link between the Rh blood group and malaria, even though there was a moderate amount of heterogeneity. Further studies using prospective designs and a definitive method for Plasmodium identification are needed to investigate the risk of Plasmodium infection in Rh+ individuals and increase the reliability and quality of these studies.
Keyphrases
  • plasmodium falciparum
  • systematic review
  • case control
  • single cell
  • meta analyses
  • randomized controlled trial
  • emergency department
  • clinical trial
  • radiation therapy
  • risk assessment
  • quality improvement
  • big data