A211 INCREASED RATES OF PPI DEPRESCRIPTION OVER TIME IN PATIENTS WITH UPPER GI BLEEDS
Bibliographic record
Abstract
Abstract Background Proton Pump Inhibitors (PPIs) are commonly used for various indications, including prophylaxis of upper GI bleeding. We aimed to assess if there has been more PPI deprescription in recent years in patients treated for Upper GI Bleeds (UGIB). Aims Our study aimed to assess the frequency of PPI deprescription in patients treated with endoscopic therapy for UGIBs. We hypothesized that there was a higher rate of PPI deprescription in recent years. Methods This retrospective cohort study analyzed patients who received endoscopic treatment for UGIB between the years 2015-2022. All patients who were treated with endoscopic therapy for an UGIB from two academic GI practices were included. PPI deprescription was defined as a 50% dose reduction, frequency reduction or complete medication discontinuation in the past 3 months or longer in established PPI users. To assess trends, the cohort was divided into group 1 (2015-2018) and group 2 (2019-2022). Data were analysed using SPSS and chi-squared testing was used to compare categorical variables. Results Data were collected from 301 UGIB treated endoscopically. The mean age was 66.4 ± 13.5 years with 64% males and 36% females. Patients from group 1 had a deprescription rate of 2% (2/101 cases). Patients from group 2 (2019-2022) had a deprescription rate of 16% (32/200 cases) (pampersand:003C0.001). Conclusions There was a higher rate of PPI deprescription in patients treated for UGIB in the second time period. Reasons for the increased rate of PPI deprescription require further investigation. Chi-Squared of PPI Deprescription for entire cohort Fisher Exact test: P value ampersand:003C0.001 Funding Agencies None
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".