P67 Assessment of prognostic scores in patients undergoing transjugular intrahepatic portosystemic shunts for ascites
Bibliographic record
Abstract
Background and Aims Transjugular intrahepatic portosystemic shunts (TIPSS) are increasingly used for the management of portal hypertensive complications. Outcomes for patients undergoing TIPSS for the management of ascites over a 12-year period were reviewed to assess for predictors of mortality. Method Data was collected for patients undergoing TIPSS procedures at a tertiary transplant centre between April 2010 and September 2022. Statistical analyses used included t-tests and Mann-Whitney tests for comparison of continuous variables between groups and the Cox proportional hazards model to identify predictive factors for mortality. Patients were censored at the point of death, last known follow up or the date of transplantation. Results There were 279 TIPSS procedures and 62.7% of the patients were male with a mean age of 56.6 years. Alcohol was the most common aetiology (63.4%), followed by metabolic dysfunction- associated steatotic liver disease (14.3%) and hepatitis C infection (8.6%). The median baseline MELD was 11 (IQR 9–14). Following TIPSS, a total of 14% of patients were transplanted, 5 within 90 days and 24 within one year. Of the remaining patients, survival at 90 days and 12-months was 91.5% (237/259) and 74.5% (175/235) respectively. Of the documented causes of death, 68.1% were due to liver related causes and 13.9% due to sepsis. Baseline variables predictive at univariate analysis for 90-day survival included hypertension, diabetes, previous cardiac and smoking histories but only hypertension (aHR 3.780, 95% C.I. 1.628–8.776) remained significant at multivariable analysis. Multivariable analysis showed all prognostic scores assessed (MELD aHR 1.097, 95% C.I 1.037–1.159, MELDNa 1.059, 95% C.I. 1.011–1.109, GEMA aHR 1.074, 95% C.I. 1.010–1.143 and GEMANa aHR 1.060, 95% C.I 1.002–1.121) to be predictive for survival at 12-months alongside diabetes (aHR 1.740, 95% C.I 1.034–2.925), ‘non-alcohol or metabolic’ aetiologies (aHR 2.281, 95% C.I 1.146–4.538) and previous cardiac disease (aHR 2.497, 95% C.I 1.164–5.357). For overall mortality, although all prognostic scores were significant at univariate analysis only MELD (aHR 1.073, 95% C.I, 1.025–1.122), MELDNa (aHR 1.043, 95% C.I. 1.007–1.079) and GEMA (aHR 1.050, 95% C.I. 1.004–1.099) remained independently predictive at multivariable analysis. Clinical factors included age (aHR 1.022, 95% C.I.1.004–1.041), diabetes (aHR 1.448, 95% C.I.1.005–2.086) and platelet count (aHR 0.998, 95% C.I 0.995–1.000). Conclusion In this cohort of patients undergoing TIPSS for ascites, prognostic scores were not predictive of survival at three months, potentially relating to the small number of events, however were predictive of 12 month and overall mortality.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".