A comparison of the gut microbiome between long‐term users and non‐users of proton pump inhibitors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Proton pump inhibitor (PPI) use is associated with an increased risk of Clostridium difficile infection (CDI), though the mechanism is unclear. PPI induced alterations to the gut microbiome may facilitate the emergence of CDI, though the effects of PPIs on gut microbiota are not well characterised. [Correction added on 10 March 2016, after first online publication: microflora has been changed to microbiota throughout the article.] AIM: To compare the faecal microbiomes of long-term PPI users to those with no history of PPI use. METHODS: We used a population-based database to identify individuals with ≥5 years of continuous PPI use along with non-PPI using controls. Stool samples were subjected to microbiological analysis, with hierarchical clustering at genus level, along with alpha and beta diversity measures comparing the two groups. Metadata was accounted for using quantile regression to eliminate potential confounding variables in taxonomic abundance comparisons. RESULTS: Sixty-one subjects (32 PPI, 29 controls) were analysed. While no significant differences in alpha diversity were found between the PPI users and controls, a moderate shift of the PPI users away from the non-PPI user cluster in the beta diversity was observed. After controlling for pertinent confounders, we discovered a decrease in Bacteroidetes and an increase in Firmicutes at the phylum level. We also performed species classifications and found Holdemania filiformis and Pseudoflavonifractor capillosus to be increased and decreased in the PPI cohort, respectively. CONCLUSIONS: Long-term PPIs use has an effect on the gut microbiome. The alteration in the ratio of Firmicutes to Bacteroidetes may pre-dispose to the development of CDI.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it