O9 Redefining poor prognostic criteria for acetaminophen-induced acute liver failure using regeneration and cell-death linked miRNA signatures
Bibliographic record
Abstract
Background Acute liver failure (ALF) remains a rare but life-threatening condition which requires early prognostication for transplantation (LTx). Existing models such as the King’s College Criteria (KCC) lack sensitivity. We have previously demonstrated the potential for regeneration linked miRNA to perform as biomarkers in acute and chronic liver disease. The aim of this study was to develop a miRNA-based prognostic model for acetaminophen (APAP) ALF. Methods Samples were provided by the US ALF Study Group. We assessed serum miRNA expression from 193 patients (94 survivors, 89 non-survivors) with APAP-ALF at two time points (early; day 1, late; day 3–5). Transplanted patients were excluded. A panel of 24 miRNA identified from our previous studies were analysed. Multiple logistic regression was used to create early and late miRNA outcome prediction models. Clinical data were incorporated to improve prognostication. Results Early up-regulation of miR-150 and down-regulation of -16–2 were associated with mortality. The early detection of miR-20a and absence of miR-149 were associated with mortality. Late up-regulation of miR-30a and down-regulation of -122, 16–2 and -21 were significantly associated with mortality. Late detection of miR-149, -17 and -191 were associated with mortality. Prognostic models were made for early and late miRNA expression. The early model contained miRNA associated with regeneration (miR-20a, -27a, -140, -150, -191) and achieved an area under the receiver operator curve (AUC) of 0.78 (95% CI 0.71–0.84, p<0.0001). This model was enhanced when combined with the Model for End-Stage Liver Disease score (MELD) and vasopressor requirement (AUC 0.83, 95% CI 0.78–0.89, p<0.0001). The late model contained miRNA associated with cell death (miR-16–2, -30a, -122, -149, -191) and achieved an AUC of 0.83. (95% CI 0.76–0.89, p<0.0001). This model was enhanced when combined with MELD and vasopressor requirements (AUC 0.91, 95% CI 0.86–0.96, p<0.0001). Conventional outcome prediction models performed as follows; KCC (early AUC 0.60, 95% CI 0.48–0.73, p=0.07, late AUC 0.69, 95% CI 0.56–0.82, p=0<0.01), MELD (early AUC 0.72, 95% CI 0.64–0.79, p<0.0001, late AUC 0.86, 95% CI 0.80–0.91, p<0.0001) and ALF Study Group Prognostic Index (early AUC 0.76, 95%CI 0.69–0.83, p<0.0001, late AUC 0.88, 95% CI 0.82–0.94, p<0.001). Conclusion We demonstrate that specific serum miRNA have prognostic value as biomarkers in ALF. Our early model utilised regeneration linked miRNA whereas our late model utilised cell-death linked miRNA; this may signify mechanistic differences at early and late time points which determine patient survival.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".