MétaCan
Menu
Back to cohort
Record W4390945005 · doi:10.14744/hf.2023.2023.0010

Changing trends in the etiology of liver transplantation in Turkiye: A multicenter study

2023· article· en· W4390945005 on OpenAlexfundno aff
Mesut Akarsu

Bibliographic record

VenueHepatology forum/Hepatology forum (Online) · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsnot available
FundersDokuz Eylül ÜniversitesiAlberta Innovates - Health Solutions
KeywordsMedicineEtiologyLiver transplantationViral hepatitisInternal medicineAlcoholic liver diseaseCirrhosisFatty liverLiver diseaseGastroenterologyChronic liver diseaseAlcoholic hepatitisTransplantationDisease

Abstract

fetched live from OpenAlex

Background and Aim: This study aimed to identify the indications for liver transplantation (LT) based on underlying etiology and to characterize the patients who underwent LT. Materials and Methods: We conducted a multicenter cross-sectional observational study across 11 tertiary centers in Turkiye from 2010 to 2020. The study included 5,080 adult patients. Results: The mean age of patients was 50.3±15.2 years, with a predominance of female patients (70%). Chronic viral hepatitis (46%) was the leading etiological factor, with Hepatitis B virus infection at 35%, followed by cryptogenic cirrhosis (24%), Hepatitis C virus infection (8%), and alcohol-related liver disease (ALD) (6%). Post-2015, there was a significant increase in both the number of liver transplants and the proportion of living donor liver transplants (p<0.001). A comparative analysis of patient characteristics before and after 2015 showed a significant decline in viral hepatitis-related LT (p<0.001), whereas fatty liver disease-related LT significantly increased (p<0.001). Conclusion: Chronic viral hepatitis continues to be the primary indication for LT in Turkiye. However, the proportions of non-alcoholic fatty liver disease (NAFLD) and ALD-related LT have seen an upward trend over the years.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.331
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 teacher head, not a consensus.

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHepatology forum/Hepatology forum (Online)Same topicOrgan Transplantation Techniques and OutcomesFrench-language works237,207