Prospective study on time-to-tertiary care in alcohol-associated hepatitis: space–time coordinates as prognostic tool and therapeutic target
Bibliographic record
Abstract
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%.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
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 teacher head, 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".