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Record W3153863274 · doi:10.1136/gutjnl-2020-basl.9

O9 Redefining poor prognostic criteria for acetaminophen-induced acute liver failure using regeneration and cell-death linked miRNA signatures

2020· article· en· W3153863274 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAbstracts · 2020
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversité de MontréalUniversity of Alberta
Fundersnot available
KeywordsmicroRNAMedicineLiver transplantationLogistic regressionReceiver operating characteristicInternal medicineLiver failureRetrospective cohort studyOncologyTransplantationBiologyGene

Abstract

fetched live from OpenAlex

<h3>Background</h3> 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. <h3>Methods</h3> 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. <h3>Results</h3> 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<b>–</b>0.84, p&lt;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&lt;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&lt;0.0001). This model was enhanced when combined with MELD and vasopressor requirements (AUC 0.91, 95% CI 0.86–0.96, p&lt;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&lt;0.01), MELD (early AUC 0.72, 95% CI 0.64–0.79, p&lt;0.0001, late AUC 0.86, 95% CI 0.80–0.91, p&lt;0.0001) and ALF Study Group Prognostic Index (early AUC 0.76, 95%CI 0.69–0.83, p&lt;0.0001, late AUC 0.88, 95% CI 0.82–0.94, p&lt;0.001). <h3>Conclusion</h3> 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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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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.207
GPT teacher head0.403
Teacher spread0.196 · 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