Background: We previously showed that the endoscopic Kyoto classification for gastritis could predict infection in individuals with a high negative titer of serum anti- antibodies. This study evaluated infection and the Kyoto classification score in patients with a low negative titer (<3 U/ml), high negative titer (3-9.9 U/ml), low positive titer (10-49.9 U/ml), and high positive titer (≥50 U/ml).
Methods: Serum antibody levels, Kyoto classification score and histology were investigated in 870 individuals with no history of -eradication therapy. Urea breath tests (UBTs) were additionally conducted for patients with a low negative titer and a Kyoto score ≥1 or an antibody titer ≥10 U/ml and a Kyoto score of 0 or 1. UBTs and/or histological studies were conducted for participants with a high negative titer.
Results: False diagnoses based on anti- antibody titers were observed in 0.3% of the low-negative-titer group, 11.7% of the high-negative-titer group, 18.9% of the low-positive-titer group and 2.2% of the high-positive-titer group. Surprisingly, false diagnoses based on antibody titers were noted in 63.2% of patients with a low positive titer and a Kyoto score of 0 and in 62.5% of patients with a high negative titer and a Kyoto score ≥2, respectively.
Conclusions: Endoscopic findings could predict false diagnoses determined using serum antibody titers.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466756 | PMC |
| http://dx.doi.org/10.1177/2050640619825947 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Assessment of Helicobacter pylori infection in Lebanon: Endoscopic and histopathological findings.
J Infect Public Health
January 2025
Department of Medical Laboratory Sciences, Faculty of Health Sciences, Beirut Arab University, Beirut 11-5020, Lebanon. Electronic address:
Helicobacter pylori (H. pylori), a pervasive pathobiont, colonizes the gastric mucosa and plays a crucial role in the pathogenesis of several gastroduodenal pathologies ranging from chronic gastritis to more severe disorders including peptic ulcer disease, gastric mucosa-associated lymphoid tissue lymphoma, and gastric adenocarcinoma. In symptomatic patients, endoscopy and histological examination of the gastric mucosa are the preferred tests for diagnosing H.
View Article and Find Full Text PDFRe-evaluating prognostic factors for cervical cancer with lymph node metastasis: a Japanese multicenter cohort study based on FIGO 2018.
Int J Clin Oncol
January 2025
Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-Cho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan.
Background: In 2018, the International Federation of Gynecology and Obstetrics (FIGO) revised its cervical cancer staging system to enhance clinical relevance, notably by categorizing lymph node metastases (LNM) as an independent stage IIIC. This multicenter study evaluates the prognostic implications of the FIGO 2018 classification within a Japanese cohort.
Methods: This study included 1468 patients with cervical cancer.
Sequential Versus Continuous Feeding and Its Effect on the Gut Microbiota in Critically Ill Patients: A Randomized Controlled Trial.
Clin Nutr ESPEN
January 2025
Department of Critical Care Medicine, The affiliated hospital of Qingdao University, 1677 Wutaishan Road, Qingdao, Shandong, 266000, China. Electronic address:
Background: Gut microbiota disturbance may worsen critical illnesses and is responsible for the progression of multiple organ dysfunction syndrome. In our previous study, there was a trend towards a higher α-diversity of the gut microbiota in sequential feeding (SF) than in continuous feeding (CF) for critically ill patients. We designed this non-blinded, randomized controlled study to confirm these results.
View Article and Find Full Text PDFData-Efficient Bone Segmentation Using Feature Pyramid- Based SegFormer.
Sensors (Basel)
December 2024
Master's Program in Information and Computer Science, Doshisha University, Kyoto 610-0394, Japan.
The semantic segmentation of bone structures demands pixel-level classification accuracy to create reliable bone models for diagnosis. While Convolutional Neural Networks (CNNs) are commonly used for segmentation, they often struggle with complex shapes due to their focus on texture features and limited ability to incorporate positional information. As orthopedic surgery increasingly requires precise automatic diagnosis, we explored SegFormer, an enhanced Vision Transformer model that better handles spatial awareness in segmentation tasks.
View Article and Find Full Text PDFApplication of machine learning for detecting high fall risk in middle aged workers using video-based analysis of the first three steps.
J Occup Health
January 2025
Panasonic Corporation, Department Electric Works Company/Engineering Division, Osaka, Japan.
Background: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fall risk prediction model using machine learning (ML) and video-based first three steps in middle-aged workers.
Methods: Train data (n=190, age 54.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!