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The Prevalence of Hypothyroidism among Patients With β-Thalassemia: A Systematic Review and Meta-Analysis of Cross-Sectional Studies.

Sezaneh HaghpanahMahnaz Hosseini-BensenjanMehrab SayadiMehran KarimiVincenzo de SanctisMani RamziMohammad Reza Mousavi
Published in: Hemoglobin (2021)
As a cause of chronic blood transfusions, iron overload is an important issue in β-thalassemia (β-thal) patients that leads to multiple organ dysfunctions. This is an updated meta-analysis conducted to summarize the existing evidence of the prevalence of hypothyroidism (HT) among patients with transfusion-dependent (TDT) and non transfusion-dependent β-thal (NTDT) and for the first time we meta-analyzed the relationship between ferritin level and HT. This systematic review and meta-analysis were done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. We searched databases including Web of Science (ISI), Scopus, PubMed, Embase, and Scholar. The quality of the included studies was assessed based on the Newcastle-Ottawa scale (NOS) checklist. Meta-analysis was done using Stata statistical software. The pooled prevalence of total HT, subclinical HT, and overt HT among β-thal patients was 13.25 [95% confidence interval (95% CI): 10.29-16.21; 11.84, 95% CI: 8.43-15.25 and 12.46, 95% CI: 1.05-23.87], respectively. The prevalence of total HT was 16.22% (95% CI: 12.36-20.08) in TDT and 7.22% (95% CI: 3.66-10.78) in NTDT patients. Serum ferritin (SF) levels were significantly lower in euthyroid compared to hypothyroid patients [standard mean difference (SMD) -2.15 (95% CI: -3.08, -1.21, p value <0.001]. The prevalence of HT was higher in TDT compared to NTDT patients. Moreover, our results showed a significant association of high serum ferritin (SF) levels with hypothyroidism in β-thal patients. Both of these findings highlight the importance of prevention measures and timely diagnosis and management of iron overload in β-thal patients.
Keyphrases
  • systematic review
  • ejection fraction
  • end stage renal disease
  • newly diagnosed
  • prognostic factors
  • public health
  • meta analyses
  • cross sectional
  • emergency department
  • risk factors
  • artificial intelligence