Transjugular intrahepatic portosystemic shunt for the treatment of refractory ascites: A population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Randomized trials have shown that transjugular intrahepatic portosystemic shunt (TIPS) improves control of ascites compared with serial large volume paracentesis (LVP) in patients with refractory ascites. However, the effect of TIPS on liver transplant-free (LTF) survival is controversial. Our objective was to compare TIPS versus serial LVP on LTF survival in the general population of patients with refractory ascites. METHODS: This is a retrospective, population-based cohort study using linked administrative health data from Ontario, Canada. Adult patients identified with refractory ascites from January 1, 2008 to December 31, 2016 were included and followed until December 31, 2017. A propensity score was used to match patients treated with serial LVP to those who received TIPS in a 2:1 ratio. LTF survival was evaluated using Kaplan–Meier analysis and Cox proportional hazards regression with TIPS treated as a time-varying exposure. RESULTS: Overall, 4,935 patients with refractory ascites were identified and 488 patients were matched (325 serial LVP, 163 TIPS). The mean age was 58 years, 70% were male, 50% had viral hepatitis, the median model for end-stage liver disease (MELD) score was 12, 13% received liver transplant and the 1-year LTF survival was 72%. After TIPS, 80 patients (49%) had no further requirement for LVP by 6 months and 61 patients (37%) never required a repeat paracentesis. In survival analysis, there was marginally worse LTF survival in patients receiving TIPS (TIPS HR 1.29, 95% CI 1.00–1.67; p = .052). CONCLUSION: In this population-based study of patients with refractory ascites, TIPS was associated with improved control of ascites but not improved LTF survival.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".