Back

Diagnostic value of combined detection of pepsinogen, gastrin-17, and 13C-urea breath test in children with chronic gastritis: A multivariate analysis

Gao, Y.; Liu, C.; Oayang, K.; Li, S.; Huang, W.

2025-08-21 gastroenterology
10.1101/2025.08.18.25333943 medRxiv
Show abstract

BackgroundThis study evaluated the diagnostic efficacy of combining pepsinogen (PG I/II), gastrin-17 (G-17), and 13C-urea breath test (13C-UBT) for chronic gastritis in children using logistic regression and receiver operating characteristic (ROC) analysis. MethodsBetween June 2018 and August 2023, 65 children from Junan Branch Hospital of Shunde Hospital of Guangzhou University of Chinese Medicine, diagnosed with chronic gastritis (chronic gastritis group), and 50 healthy children (control group) participated in this study. The enzyme-linked immunosorbent assay (ELISA) determined serum levels of PG I, PG II, and G-17. Furthermore, 13C-UBT was performed for Helicobacter pylori (Hp) infection detection. Both groups underwent serological tests and gastroscopy. ResultsCombined detection showed significantly higher positive rates than individual PG I/II or G-17 tests (P < 0.05), though comparable to 13C-UBT alone. Chronic gastritis patients exhibited elevated PG I, PG II, and G-17 levels versus controls (P < 0.05). Multivariate analysis identified PG I (OR = 2.982, P = 0.011), G-17 (OR = 3.527, P = 0.0013), and 13C-UBT positivity (OR = 4.193, P = 0.002) as significant predictors. ROC analysis revealed AUCs of 0.673 (PG I), 0.792 (G-17), 0.814 (13C-UBT), and 0.887 (combined), with sensitivity [&ge;]89% and specificity >76%. ConclusionSerum PG I, G-17 detection, and 13C-UBT provided considerable predictive accuracy for chronic gastritis in children, and combination testing further improved diagnostic accuracy in this population.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.