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Systematic Review and Meta-Analysis on the Sensitivity and Specificity of 13 C/ 14 C-Urea Breath Tests in the Diagnosis of Helicobacter pylori Infection.

Layal K Jambi
Published in: Diagnostics (Basel, Switzerland) (2022)
Helicobacter pylori ( H. pylori ) continues to be a major health problem worldwide, causing considerable morbidity and mortality due to peptic ulcer disease and gastric cancer. The aim of the present systematic review and meta-analysis was to determine the sensitivity and specificity of 13 C/ 14 C-urea breath tests in the diagnosis of H. pylori infection. A PRISMA systematic search appraisal and meta-analysis were conducted. A systematic literature search of PubMed, Web of Science, EMBASE, Scopus, and Google Scholar was conducted up to August 2022. Generic, methodological and statistical data were extracted from the eligible studies, which reported the sensitivity and specificity of 13 C/ 14 C-urea breath tests in the diagnosis of H. pylori infection. A random effect meta-analysis was conducted on crude sensitivity and specificity of 13 C/ 14 C-urea breath test rates. Heterogeneity was assessed by Cochran's Q and I2 tests. The literature search yielded a total of 5267 studies. Of them, 41 articles were included in the final analysis, with a sample size ranging from 50 to 21857. The sensitivity and specificity of 13 C/ 14 C-urea breath tests in the diagnosis of H. pylori infection ranged between 64-100% and 60.5-100%, respectively. The current meta-analysis showed that the sensitivity points of estimate were 92.5% and 87.6%, according to the fixed and random models, respectively. In addition, the specificity points of estimate were 89.9% and 84.8%, according to the fixed and random models, respectively. There was high heterogeneity among the studies (I 2 = 98.128 and 98.516 for the sensitivity and specificity, respectively, p -value < 0.001). The 13 C/ 14 C-urea breath tests are highly sensitive and specific for the diagnosis of H. pylori infection.
Keyphrases
  • systematic review
  • helicobacter pylori
  • helicobacter pylori infection
  • case control
  • structural basis
  • public health
  • meta analyses
  • healthcare
  • machine learning
  • risk assessment
  • electronic health record
  • big data