A Comparison Between Histology and Rapid Urease Test in the Diagnosis of Helicobacter Pylori in Gastric Biopsies: A Systematic Review
Bibliographic record
Abstract
Helicobacter pylori (H. pylori) is a gram-negative aerobic pathogen that primarily colonizes the gastric mucosa. Peptic ulcer disease, atrophic gastritis, gastric cancer, and mucosal-associated lymphoid tissue lymphoma have all been linked to chronic H. pylori infection. Hence, it is critical to diagnose and treat it as early as possible. There are both invasive and noninvasive tests available to detect it. In this review, the diagnostic abilities of two invasive tests - histology and the rapid urease test (RUT) - are compared in a variety of clinical situations. This systematic review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 checklist. We performed a literature search using the PubMed and Google Scholar databases in accordance with the eligibility criteria and ultimately selected eight articles for final analysis. The Newcastle-Ottawa scale adapted for cross-sectional studies, the Scale for the Assessment of Narrative Review Articles (SANRA), and the PRISMA 2020 checklist were used to assess the quality of selected articles for cross-sectional studies, traditional literature reviews, and systematic reviews, respectively. According to the findings of the review, both histology and the RUT have high sensitivity and specificity in diagnosing H. pylori though this varies depending on the clinical situation, making one test superior to the other. Neither of these tests can be considered the gold standard method on its own. Hence, using at least two diagnostic tests at the same time is critical for ensuring high sensitivity and specificity while accurately diagnosing the pathogen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.015 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".