A186 LOWER HOSPITAL READMISSION RATES IN PATIENTS RECEIVING TIPS FOR ESOPHAGEAL VARICEAL BLEEDING: A NATIONWIDE LINKED ANALYSIS
Bibliographic record
Abstract
Readmission to hospital following a Transjugular Intrahepatic Portosystemic Shunt (TIPS) procedure after an episode of esophageal variceal bleeding (EVB) has not been assessed. We aimed to address this gap in knowledge. The Nationwide Readmission Database (NRD) was used to study the readmission rates for patients with decompensated cirrhosis who had a TIPS procedure performed for EVB. The NRD is a national database powered to track patients longitudinally for hospital readmissions. A propensity score matching model was created to match patients who received TIPS to those who did not. A total of 42,679,001 hospital admissions from the 2012–2014 NRD sample were analyzed. There were 33,934 patients with EVB who met inclusion criteria for the study, of which, 1,527 (4.5%) received TIPS after EVB. After propensity score matching, 1,527 patients without TIPS were matched to 1,527 patients who received TIPS. After a uniform follow-up of 3 months, patients with TIPS were less likely to be readmitted to hospital with a recurrent EVB (3.0%, 95% CI: 2.0%-3.9% vs. 9.3%, 95% CI: 7.6%-11.0%, p=0.01). Furthermore, at 3 months there was no difference in all cause hospital readmission between the two groups (38.8%, 95% CI: 38.1%-44.9% TIPS vs. 41.5%, 95% CI: 34.1%-43.3% no TIPS, p=0.17). In this large nationally represented analysis we showed that patients with EVB who underwent TIPS have a significantly lower risk of 3-month readmission for recurrent EVB. Further randomized controlled trials are warranted to confirm these findings. None
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".