Accuracy of Office‐Based Immunoassays for the Diagnosis of <i>Helicobacter pylori</i> Infection in Children
Bibliographic record
Abstract
BACKGROUND: Rapid non-invasive diagnostic tests that can reliably document the presence or absence of Helicobacter pylori infection are urgently required. The aim of this study was to determine the accuracy of two immunoassays (Flex-Sure and MedMira), developed for use outside the laboratory setting by practitioners, in the setting of a low prevalence of H. pylori infection. METHODS: Serum samples collected in four previous studies (n = 349) were employed to detect the presence of H. pylori-specific immunoglobulin G, compared to previous results obtained using endoscopic biopsies, serology, flow cytometry, and urease breath testing. Serum samples included 52 obtained from adults (parents and grandparents of symptomatic children), 123 sera collected from children and adolescents undergoing diagnostic upper endoscopy for upper gastrointestinal tract symptoms, and 174 samples drawn from children in the primary care setting with or without recurrent abdominal pain. RESULTS: Overall, 16% of subjects were infected by the gastric pathogen. Both the specificity (%) and negative predictive value (%) of the two tests were high (FlexSure: 91 and 92; Medmira: 97 and 94, respectively). In adults, both tests also demonstrated high sensitivity (83% and 86%) and positive predictive values (79% and 83%, respectively). However, in children where the prevalence of infection was 12% (37 of 297 subjects), the sensitivity (59% and 71%) and positive predictive values (55% and 88%, respectively) of the immunoassays were lower. CONCLUSIONS: These findings indicate that, in the setting of a low prevalence of H. pylori infection, the MedMira office-based test provides satisfactory results and utility. However, the low positive-predictive value of the FlexSure kit may limit applicability of this test in children.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".