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Record W4403391579 · doi:10.1136/gutjnl-2024-basl.74

P65 Assessing predictors of mortality following transjugular intrahepatic portosystemic shunts for variceal bleeding

2024· article· en· W4403391579 on OpenAlexaff
Jemima Finkel, Silke François, Amine Benmassaoud, Louise China, David Patch, Emmanuel Tsochatzis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransjugular intrahepatic portosystemic shuntMedicinePortal hypertensionInternal medicineCirrhosis

Abstract

fetched live from OpenAlex

Background and Aims Transjugular intra-hepatic portosystemic shunts (TIPSS) are used as salvage therapy in variceal bleeding and are also increasingly being utilised pre-emptively. Our aim was to evaluate the outcomes of salvage TIPSS performed for variceal bleeding at a tertiary liver transplant centre and identify predictors of mortality. Method Data was collected for patients undergoing TIPSS procedures between April 2010 and September 2022. Statistical analyses 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, their last known follow-up or the date of transplantation. Results 193 patients had an average age of 52.7 years and were 68.4% male. Aetiology was predominantly alcohol (64.8%), followed by metabolic dysfunction-associated steatotic liver disease (10.9%) and hepatitis C infection (7.8%). 9 patients progressed to transplant and in those who did not, survival was 74.6% at 90 days and 64.8% at 12 months. Documented causes of death revealed 79.4% as liver-related. The median MELD was 13 (IQR 10–17). Baseline MELD, MELDNa, GEMA and GEMANa were all associated with 90-day, 12 month and overall survival. In predicting 90-day mortality, AUROC analysis of the MELD score was 0.819 (0.753–0.884), MELD Na 0.813 (0.747–0.880), GEMA 0.809 (0.743–0.875) and GEMA Na 0.801 (0.732–0.870). Both 90-day and overall survival analysis showed significance at univariate analysis for bilirubin, creatinine, INR, albumin, WBC, MELD, MELDNa, GEMA, GEMANa, Bureau’s criteria, previous hepatic encephalopathy and the RFH eGFR. All prognostic scores (tested in separate multivariate models) except for Bureau’s were independently predictive of mortality at multivariable analysis at both 90 days (MELD aHR 1.138, 95% C.I. 1.090–1.188, MELDNa aHR 1.123, 95% C.I.1.076–1.172, GEMA aHR 1.136, 95% C.I. 1.078–1.185, GEMANa aHR 1.130, 95% C.I.1.078–1.185) and overall (MELD aHR 1.083, 95% C.I 1.045–1.122, MELDNa aHR 1.074, 95% C.I.1.037–1.111, GEMA aHR 1.077, 95% C.I. 1.040–1.115, GEMANa aHR 1.079, 95% C.I 1.040–1.119). Previous encephalopathy, smoking and age at TIPSS insertion remained independently significant in all models as did WBC (aHR 1.040, 95% C.I.1.008–1.072), RFH e-GFR (aHR 0.990, 95% C.I. 0.983–0.998) and MetALD (HR 1.912, 95% C.I 1.144–3.197) when modelled with the Bureau criteria for overall survival. Conclusion Prognostic scores assessed on this large cohort of TIPSS procedures performed for variceal bleeding were good predictors of mortality. As increasing numbers of pre-emptive procedures are being implemented, these will need to be re-assessed in this subset of patients.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.025
GPT teacher head0.325
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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