Proton Pump Inhibitor Use Is Associated With an Increased Frequency of Hospitalization in Patients With Cystic Fibrosis
Bibliographic record
Abstract
BACKGROUND: Proton pump inhibitors (PPIs) are among the most commonly prescribed medications in clinical practice. PPI use has been associated with the development of community-acquired pneumonia. With a reported prevalence of gastroesophageal reflux disease (GERD) and PPI use that is higher than the general population, patients with cystic fibrosis (CF) are particularly vulnerable to PPI adverse effects. We sought to explore whether PPI use was associated with a higher number of hospitalizations for CF pulmonary exacerbation. METHODS: We conducted a longitudinal retrospective review in an academic outpatient setting. Patients > 18 years of age with a diagnosis of CF and at least 1 year of follow-up were eligible for inclusion. Baseline characteristics, PPI use, and details of hospitalization through 1 year of follow-up were collected. RESULTS: One hundred fourteen patients met inclusion criteria. Fifty-nine patients (51.7%) were hospitalized at least once in the follow-up year, mean number of hospitalizations was 2.17 (± 1.9). At least 6 months of PPI use was observed in 59 patients (51.7%). In univariate analysis, PPI use was associated with a significantly higher mean number of hospitalizations (0.9 vs. 1.4, P = 0.009). In a multi-variable regression model, PPI use remained significantly associated with a higher number of hospitalizations (P = 0.03), while controlling for risk factors traditionally associated with increased pulmonary exacerbations. CONCLUSION: PPI use is highly prevalent in CF patients. Exposure to PPI therapy is independently associated with a higher number of hospitalizations for pulmonary exacerbation in CF patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".