Document Type : Letter to the editor


P.O.Box 55302, Baghdad Post Office, Baghdad, Iraq


Dear Editor, 
We read carefully the article by Saeed et al. [1] entitled "Prevalence of Helicobacter pylori Infection in Cigarette and Nargileh Smoking Males in Erbil City, Iraq" which was published in volume 18, issue 2, 2022 of Al-Anbar Medical Journal. On using serology (IgG antibody test) Saeed et al. [1] found that Helicobacter pylori (H. pylori) prevalence in smokers and nonsmokers were 64.9% and 45.5%, respectively (P = 0.03). The young age group (25-34 years old) had the highest prevalence (54.1%; P = 0.05), and 89.2% of H. pylori-infected individuals had gastric complaints (P = 0.01). Nargileh smokers made up half of the H. pylori-positive participants. We, hereby, explore the limitations of the published article and provide insight into the value of serology to diagnose H. pylori infection.


Main Subjects

[1]      C. H. Saeed, S. H. Shareef, and P. D. Majeed, “Prevalence of Helicobacter pylori Infection in Cigarette and Nargileh Smoking Males in Erbil City, Iraq,” Al-Anbar Med. J., vol. 18, no. 2, pp. 72–76, 2022.
[2]      A. G. Gravina et al., “Extra-gastric manifestations of Helicobacter pylori infection,” J. Clin. Med., vol. 9, no. 12, p. 3887, 2020.
[3]      A. Elbehiry et al., “Helicobacter pylori Infection: Current Status and Future Prospects on Diagnostic, Therapeutic and Control Challenges,” Antibiotics, vol. 12, no. 2, p. 191, 2023.
[4]      G. Godbole, F. Mégraud, and E. Bessède, “Diagnosis of Helicobacter pylori infection,” Helicobacter, vol. 25, p. e12735, 2020.
[5]      D. S. Bordin, I. N. Voynovan, D. N. Andreev, and I. V Maev, “Current Helicobacter pylori diagnostics,” Diagnostics, vol. 11, no. 8, p. 1458, 2021.
[6]      M. Zhang et al., “An explainable artificial intelligence system for diagnosing Helicobacter Pylori infection under endoscopy: a case–control study,” Therap. Adv. Gastroenterol., vol. 16, p. 17562848231155024, 2023.
[7]      J. Y. Seo, H. Hong, W.-S. Ryu, D. Kim, J. Chun, and M. Kwak, “Development and validation of a convolutional neural network model for diagnosing Helicobacter pylori infections with endoscopic images–A multicenter study.,” Gastrointest. Endosc., 2023.
[8]      Y.-D. Li et al., “Assessment of Helicobacter pylori infection by deep learning based on endoscopic videos in real time,” Dig. Liver Dis., 2023.
[9]      R. A. Hussein, M. T. S. Al-Ouqaili, and Y. H. Majeed, “Detection of Helicobacter Pylori infection by invasive and non-invasive techniques in patients with gastrointestinal diseases from Iraq: A validation study,” PLoS One, vol. 16, no. 8, p. e0256393, 2021.