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Record W4406634178 · doi:10.1093/alcalc/agae092

Prospective study on time-to-tertiary care in alcohol-associated hepatitis: space–time coordinates as prognostic tool and therapeutic target

2025· article· en· W4406634178 on OpenAlexaff
Ľubomír Skladaný, Daniela Žilinčanová, Natália Kubánek, Světlana Adamcová Selčanová, Daniel Ján Havaj, Lukáš Lafférs, Michal Žilinčan, Alvi H. Islam, Juan Pablo Arab, T. Köller

Bibliographic record

VenueAlcohol and Alcoholism · 2025
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsSt Joseph's Health CareSt Joseph's Health CentreLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineHazard ratioAlcoholic hepatitisInternal medicineLiver diseaseLiver transplantationAdverse effectModel for End-Stage Liver DiseaseAlcoholic liver diseaseDecompensationCirrhosisProspective cohort studyProportional hazards modelConfidence intervalTransplantation

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Alcohol-associated hepatitis (AH) frequently triggers acute decompensation (AD) in cirrhosis, with severe AH linked to high short-term mortality, especially in acute-on-chronic liver failure. Current corticosteroid treatments have limited efficacy, highlighting the need for new therapies. We hypothesized that severe AH outcomes are influenced by early specialized care; thus, we examined the impact of time-to-tertiary care (TTTc). METHODS: Adults with cirrhosis or advanced chronic liver disease were enrolled (RH7, NCT04767945). AH was diagnosed using National Institute on Alcohol Abuse and Alcoholism criteria. Primary admission site, TTTc, and adverse outcomes (death or liver transplantation) were analyzed. Patients admitted directly to tertiary care were assigned a TTTc of zero. RESULTS: Of 221 AD-AH patients, 107 were transferred from secondary care to tertiary care (TTTc >0) and 114 were admitted directly (TTTc = 0). TTTc >0 patients were younger (48.3 vs. 52 years, P = .008) and had more severe disease, as shown by model for end-stage liver disease scores (25.5 vs. 20.8, P < .001) and Maddrey's discriminant function (59.3 vs. 40.6, P < .001). Propensity-score matching yielded 49 case pairs. The Cox model showed that transfer from secondary care was not associated with increased risk, but delayed transfer (days, hazard ratio = 1.03, 95% confidence interval 1.01-1.05) independently predicted adverse outcomes. CONCLUSIONS: Delayed initiation of specialized care adversely impacts outcomes in AD-AH. If validated, timely care bundles could improve AH survival, similar to sepsis or vascular syndromes. HIGHLIGHTS: AD-AH is a common syndrome associated with high short-term mortality. There is an unmet need for new prognosis-modifying therapies for AH. Currently, in real-life hepatology, refining the existing bundle of care is the only practical option to improve the prognosis of AD-AH. Past experience with acute coronary syndromes, stroke, and sepsis, emphasizing symptoms-to-intervention duration, combined with the recent COVID-19 lockdown finding of increased mortality due to skewed access to specialized liver care indicates that focusing on timely specialized care might be key to improved outcome in certain liver conditions. In this line, we set out to track the number of days elapsing between admission to SC and referral to TC, coining this interval as "time-to-tertiary care" (TTTc). We examined TTTc as a potential compound surrogate that might influence the prognosis in AD-AH. After correcting for important baseline differences, we conclude that the delay of transfer to the tertiary care hospital was independently associated with a worse prognosis with each additional day in TTTc increasing adverse outcomes by nearly 3%.

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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.020
GPT teacher head0.329
Teacher spread0.310 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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