3PM-guided innovation in treatments of severe alcohol-associated hepatitis utilizing fecal microbiota transplantation
Bibliographic record
Abstract
Abstract Rationale Severe alcohol-associated hepatitis (SAH) is the most critical, acute, inflammatory phenotype within the alcohol-associated liver disease (ALD) spectrum, characterized by high 30- and 90-day mortality. Since several decades, corticosteroids (CS) are the only approved pharmacotherapy offering highly limited survival benefits. Contextually, there is an evident demand for 3PM innovation in the area meeting patients’ needs and improving individual outcomes. Fecal microbiota transplantation (FMT) has emerged as one of the new potential therapeutic options. In this study, we aimed to address the crucial 3PM domains in order to assess (i) the impact of FMT on mortality in SAH patients beyond CS, (ii) to identify factors associated with the outcome to be improved (iii) the prediction of futility, (iv) prevention of suboptimal individual outcomes linked to increased mortality, and (v) personalized allocation of therapy. Methods We conducted a prospective study (NCT04758806) in adult patients with SAH who were non-responders (NR) to or non-eligible (NE) for CS between January 2018 and August 2022. The intervention consisted of five 100 ml of FMT, prepared from 30 g stool from an unrelated healthy donor and frozen at − 80 °C, administered daily to the upper gastrointestinal (GI) tract. We evaluated the impact of FMT on 30- and 90-day mortality which we compared to the control group selected by the propensity score matching and treated by the standard of care; the control group was derived from the RH7 registry of patients hospitalized at the liver unit (NCT04767945). We have also scrutinized the FMT outcome against established and potential prognostic factors for SAH — such as the model for end-stage liver disease (MELD), Maddrey Discriminant Function (MDF), acute-on-chronic liver failure (ACLF), Liver Frailty Index (LFI), hepatic venous-portal pressure gradient (HVPG) and Alcoholic Hepatitis Histologic Score (AHHS) — to see if the 3PM method assigns them a new dimension in predicting response to therapy, prevention of suboptimal individual outcomes, and personalized patient management. Results We enrolled 44 patients with SAH (NR or NE) on an intention-to-treat basis; we analyzed 33 patients per protocol for associated factors (after an additional 11 being excluded for receiving less than 5 doses of FMT), and 31 patients by propensity score matching for corresponding individual outcomes, respectively. The mean age was 49.6 years, 11 patients (33.3%) were females. The median MELD score was 29, and ACLF of any degree had 27 patients (81.8%). FMT improved 30-day mortality (p = 0.0204) and non-significantly improved 90-day mortality (p = 0.4386). Univariate analysis identified MELD ≥ 30, MDF ≥ 90, and ACLF grade > 1 as significant predictors of 30-day mortality, (p = 0.031; p = 0.014; p = 0.034). Survival was not associated with baseline LFI, HVPG, or AHHS. Conclusions and recommendations in the framework of 3PM In the most difficult-to-treat sub-cohort of patients with SAH (i.e., NR/NE), FMT improved 30-day mortality. Factors associated with benefit included MELD ≤ 30, MDF ≤ 90, and ACLF < 2. These results support the potential of gut microbiome as a therapeutic target in the context of 3PM research and vice versa — to use 3PM methodology as the expedient unifying template for microbiome research. The results allow for immediate impact on the innovative concepts of (i) personalized phenotyping and stratification of the disease for the clinical research and practice, (ii) multilevel predictive diagnosis related to personalized/precise treatment allocation including evidence-based (ii) prevention of futile and sub-optimally effective therapy, as well as (iii) targeted prevention of poor individual outcomes in patients with SAH. Moreover, our results add to the existing evidence with the potential to generate new research along the SAH’s pathogenetic pathways such as diverse individual susceptibility to alcohol toxicity, host-specific mitochondrial function and systemic inflammation, and the role of gut dysbiosis thereof.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 source (direct Gemma or distilled Codex), 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".