Community pharmacy–based <i>H. pylori</i> screening for patients with uninvestigated dyspepsia
Bibliographic record
Abstract
Background: Helicobacter pylori is identified by the World Health Organization as a major risk factor of gastritis, peptic ulcer disease and gastric carcinomas. As point-of-care screening technology becomes more widely available, pharmacists are ideally suited to use this tool to screen patients with H. pylori infection. Purpose: The objective of this study was to evaluate the feasibility of implementing point-of-care screening technology for H. pylori into community pharmacy practice and to assess the number of patients who are positively identified as a result of testing. Methods: Three pharmacies in Toronto, Ontario, offered H. pylori screening as part of their clinical programs. Pharmacists enrolled patients with symptoms of dyspepsia and/or receiving acid suppressant therapy for >6 weeks. Decision to screen was based on the Canadian Helicobacter Study Group Consensus (CHSG). Patients were screened using the Rapid Response H. pylori test. Results: Seventy-one patients were recruited, with a mean age of 46.3 years. Patients were ethnically diverse, with a significant proportion (59.2%) identified as being born outside of North America, including Asia (26.8%), Africa (9.9%), the Middle East (7%), Europe (9.9%) and South and Central America (5.6%). Overall, the detection rate of H. pylori infection was 21%. North Americans had the lowest incidence of an undiagnosed H. pylori infection (6.9%). Europeans (28.6%), Middle Easterners (20%) and Asians (21.1%) had a moderate incidence, followed by the highest prevalence in those of African descent (71.4%). Conclusion: These results highlight the readiness of community pharmacists to adopt H. pylori screening into practice and to leverage this novel technology to positively identify and treat undiagnosed H. pylori infection. Can Pharm J (Ott) 2020;153:xx-xx.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".