The Prevalence of and the Clinical and Demographic Characteristics Associated With High-Intensity Proton Pump Inhibitor Use
Bibliographic record
Abstract
INTRODUCTION: High-intensity proton pump inhibitor (PPI) use is often recommended by physicians, though there is little proven benefit over standard PPI dosing in many clinical situations. We therefore sought to calculate the prevalence and predictors of high-intensity PPI use. METHODS: We used a Canadian provincial administrative database to capture all PPI prescriptions between 1996 and 2004. A person was defined as a high-intensity user if he used PPIs at more than 1.5 times the standard PPI dose for greater than 45 of 90 days before the index date. The prevalence of high-intensity use was calculated at four index dates annually. Stepwise logistic regression was performed to determine clinical and demographic factors associated with high-intensity PPI use. RESULTS: The prevalence of high-intensity PPI use increased from 9.7% in 1997 to 14.2% in 2004. Polypharmacy, concomitant use of antispasmodic/promotility agents, and recent endoscopy were most strongly predictive of high-intensity PPI use. Severity of gastroesophageal reflux disease (GERD) (as assessed by the number of GERD-related physician visits) was relatively weakly predictive of high-intensity PPI use. CONCLUSIONS: High-intensity PPI use is becoming more prevalent over time, and its use is strongly associated with factors suggestive of a high degree of comorbidity and treatment failure. Further research into factors that drive high-intensity PPI prescription and use are required.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".