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Record W4389166622 · doi:10.1016/j.jhepr.2023.100977

Evolution of spontaneous portosystemic shunts over time and following aetiological intervention in patients with cirrhosis

2023· article· en· W4389166622 on OpenAlexaff
Judit Vidal‐González, Javier Martínez, Akhilesh Mulay, Marta López, Anna Baiges, Ahmed Elmahdy, Katharina Lampichler, Geert Maleux, Johannes Chang, Marta Poncela Blanco, Gavin Low, Gabriele Ghigliazza, Alexander Zipprich, Carmen Picón, Rushabh S. Shah, Elba Llop, Anna Darnell, Martin Maurer, Lawrence Bonne, Enrique de Ramón, Sergi Quiroga, Juan G. Abraldeṣ, Aleksander Krag, Jonel Trebicka, Cristina Ripoll, Vincenzo La Mura, Puneeta Tandon, Rita García‐Martínez, Michael Praktiknjo, Wim Laleman, Thomas Reiberger, Annalisa Berzigotti, Virginia Hernández–Gea, José Luís Calleja, Emmanuel Tsochatzis, Agustı́n Albillos, Macarena Simón‐Talero, Joan Genescà

Bibliographic record

VenueJHEP Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of Alberta
FundersEuropean Social FundEuropean Regional Development FundInstituto de Salud Carlos IIIEuropean Commission
KeywordsCirrhosisMedicineEtiologyIntervention (counseling)CardiologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Background & aimsSpontaneous portosystemic shunts (SPSS) develop frequently in liver cirrhosis. Changes over time and the effect of aetiological interventions on SPSS are unknown, so we aimed to explore the effect of these variables in SPSS evolution.MethodsCirrhotic patients from the Baveno VI-SPSS cohort were selected provided there was a follow-up abdominal computed tomography (CT) or magnetic resonance imaging (MRI). Clinical and laboratory data were collected at baseline and follow-up. Imaging tests were reviewed, evaluating changes along time in the presence and size of SPSS (large (L)-SPSS was ≥8 mm). Regarding alcohol or hepatitis C virus (HCV) related cirrhosis, two populations were defined: cured patients (abstinent or successful HCV therapy), and non-cured patients.ResultsA total of 617 patients were included. At baseline SPSS distribution was 22% L-SPSS, 30% small (S)-SPSS, and 48% without (W)-SPSS. During follow-up (median follow-up of 63 months), SPSS distribution worsened: L-SPSS 26%, S-SPSS 32%, and W-SPSS 42% (p <0.001). Patients with deteriorated liver function during follow-up showed a simultaneous aggravation in SPSS distribution. Non-cured patients (n=191) experienced a significant worsening in liver function, more episodes of liver decompensation and lower transplant-free survival compared to cured patients (n=191). However, no differences were observed regarding SPSS distribution at inclusion and at follow-up, with both groups showing a trend to worsening. Total shunt diameter increased more in non-cured (52%) than in cured patients (28%). However, total shunt area (TSA) significantly increased only in non-cured patients (74 to 122 mm2, p <0.001).ConclusionsThe presence of SPSS in cirrhosis increases over time and parallels liver function deterioration. Aetiological intervention in these patients reduces liver-related complications, but SPSS persist although progression is decreased.Impact and implicationsThere is no information regarding the evolution of SPSS during the course of cirrhosis, and especially after disease regression with aetiological interventions, such as HCV treatment with DAA or alcohol abstinence. These results are relevant for clinicians dealing with patients with cirrhosis and portal hypertension because have important implications on the management of cirrhosis with SPSS after disease regression. From a practical point of view, physicians should be aware that in advanced cirrhosis with portal hypertension, after aetiological intervention, SPSS mostly persist despite liver function improvement, and complications related to SPSS may still develop.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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 teacher head, 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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Citations7
Published2023
Admission routes1
Has abstractyes

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