Comparison of invasive histological and molecular methods in the diagnosis of Helicobacter pylori from gastric biopsies of Sudanese patients: a cross-sectional study.
Maram ElnoshHisham AltaybYousif HamedelnilWafa ElshareefAliaa AbugrainEsraa OsmanAalaa Mahgoub AlbashaAbdelhamid AbdelhamidEhssan MogladAhmed Bakheet Abd AllaAhmed I HashimPublished in: F1000Research (2022)
Background: The continuous rise in the number of patients suffering from Helicobacter pylori is probably due to the changes in modern life. Nowadays, patients suffering from gastrointestinal problems are diagnosed through invasive and non-invasive techniques. The choice of a diagnostic test is influenced by factors such as the tests' sensitivity and specificity, the clinical conditions, and the cost-effectiveness of the testing strategy. This study aimed to compare molecular detection methods of H. pylori by polymerase chain reaction (PCR) targeting the 16S rRNA, ureA and glmM genes with an invasive histopathological technique. Methods: 290 gastric biopsies were collected using gastrointestinal endoscopy from patients with gastritis symptoms in different hospitals in Khartoum state. Two gastric biopsies were collected from each patient for PCR and histopathology. Results : A total of 103 (35.5%) samples were positive by histopathological examination, 88 (30.3%) by 16S rRNA , 39 (13.4%) by glmM gene, and 56 (19.3%) by ureA gene. The highest sensitivity was observed in 16S rRNA (46.6%), followed by glmM (24.3%) and ureA (23.3%). While the best specificity was observed in glmM gene (92.5%), followed by ureA (82.3%) and 16S rRNA (78.6%). Conclusion : PCR test targeting the 16S rRNA gene exhibited the best results for molecular detection of H. pylori compared to other genes.
Keyphrases
- helicobacter pylori
- end stage renal disease
- genome wide
- ejection fraction
- newly diagnosed
- prognostic factors
- healthcare
- mental health
- peritoneal dialysis
- genome wide identification
- gene expression
- dna methylation
- patient reported outcomes
- ultrasound guided
- risk factors
- transcription factor
- single molecule
- sleep quality
- structural basis