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Malaysian Journal of Medical Sciences
School of Medical Sciences, Universiti Sains Malaysia
ISSN: 1394-195X
Vol. 25, No. 4, 2018, pp. 92-99
Bioline Code: mj18050
Full paper language: English
Document type: Research Article
Document available free of charge

Malaysian Journal of Medical Sciences, Vol. 25, No. 4, 2018, pp. 92-99

 en Warthin-Starry Staining for the Detection of Helicobacter pylori check for this species in other resources in Gastric Biopsies
Farouk, Wirda Indah; Hassan, Nur Hidayah; Ismail, Teh Rasyidah; Daud, Intan Sufinaz & Mohammed, Fazarina

Abstract

    Background: Warthin-Starry (WS) staining is an ancillary stain used in the detection of Helicobacter sp., spirochaete and other microorganisms in tissue sections. The present study aimed to determine the validity of WS stain in the confirmation of H. pylori diagnosis in gastric biopsies in comparison with anti-H. pylori immunohistochemistry (IHC) staining.
    Methods: This study involved 104 cases of gastric biopsies that were previously subjected to WS staining. All cases involved retrieval of formalin-fixed paraffin-embedded (FFPE) gastric biopsies that were re-cut, subjected to anti-H. pylori IHC staining and reviewed blindly by a pathologist. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of WS as compared to IHC were calculated.
    Results: In this study, WS stain was less sensitive in detecting H. pylori. The sensitivity, specificity, PPV and NPV for WS stain were 50.0%, 92.4%, 79.2% and 76.3%, respectively.
    Conclusions: The sensitivity of WS stain in the histopathology laboratory was lower than that described previously. Several external factors that might influence the results were identified. However, sufficient information on patients’ history of treatment and medication would be required for the diagnosis or confirmation of the presence of H. pylori in gastric biopsies by WS staining.

Keywords
H. pylori; Warthin-Starry; sensitivity; specificity; positive predictive value; negative predictive value

 
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