Full adherence to cirrhosis quality indicators is associated with lower mortality in acute variceal bleeding: Nationwide audit
Bibliographic record
Abstract
BACKGROUND AND AIMS: Acute variceal bleeding (AVB) is a major complication in patients with cirrhosis. Using a nationwide AVB audit, we performed a nested cohort study to determine whether full adherence to the AVB quality indicator (QI) improves clinical outcomes in patients with cirrhosis and AVB. APPROACH AND RESULTS: We assessed real-world adherence to AVB QI among patients with cirrhosis admitted for AVB in all public hospitals in Singapore between January 2015 and December 2020. Full adherence was considered when all 5 QIs were fulfilled: prophylactic antibiotics, vasoactive agents, timely endoscopy, endoscopic hemostasis during index endoscopy, and nonselective beta-blockers after AVB. We compare 6-week mortality between the full adherence and suboptimal adherence groups using a propensity-matched cohort.A total of 989 patients with AVB were included. Full adherence to all AVB QI was suboptimal (56.5%). Analysis of the propensity-matched cohort with comparable baseline characteristics showed that full adherence was associated with a lower risk of early infection (20.0% vs. 26.9%), early rebleeding (5.2% vs. 10.2%), and mortality at 6 weeks (8.2% vs. 19.7%) and 1 year (21.3% vs. 35.4%) ( p <0.05 for all). While full adherence was associated with a lower 6-week mortality regardless of the MELD score, nonadherence was associated with a higher 6-week mortality despite a lower predicted risk of 6-week mortality. Despite high adherence to the recommended process measures, patients with CTP-C remain at a higher risk of rebleeding, 6-week and 1-year mortality. CONCLUSIONS: Full adherence to the AVB QI should be the target for quality improvement in patients with cirrhosis.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".