Association of proton pump inhibitors with the risk of hepatic encephalopathy during hospitalization for liver cirrhosis
Bibliographic record
Abstract
Background Hepatic encephalopathy is associated with altered gut microbiota. Proton pump inhibitors increase the risk of small bowel bacterial overgrowth. Objectives This was a case‐control study aimed at exploring the relationship of proton pump inhibitor use with the risk of hepatic encephalopathy during hospitalization in liver cirrhosis. Methods Case and control groups were defined as cirrhotic patients who developed hepatic encephalopathy during hospitalization and those without hepatic encephalopathy at admission or during hospitalization, respectively. Age, gender, and Child‐Pugh score were matched between the groups. Odds ratios with 95% confidence intervals were calculated to express the association of proton pump inhibitors with the risk of hepatic encephalopathy. Four subgroup analyses were performed after excluding patients with acute upper gastrointestinal bleeding, infections, and in‐hospital death, and after matching model for end‐stage liver disease score. Results In the overall analysis, 128 patients were included in each group of cases and controls. The proportion of proton pump inhibitor use was significantly higher in the case group than the control group (79.7% vs 43%, p < 0.001). Proton pump inhibitor use (odds ratio = 3.481, 95% confidence interval: 1.651–7.340, p = 0.001) was independently associated with the development of hepatic encephalopathy in the multivariate analysis. In the four subgroup analyses, proton pump inhibitor use remained independently associated with the risk of hepatic encephalopathy. Conclusion Proton pump inhibitor use might increase the risk of hepatic encephalopathy during hospitalization.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".