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Record W4324366844 · doi:10.1016/j.jhepr.2023.100727

MELD 3.0 adequately predicts mortality and renal replacement therapy requirements in patients with alcohol-associated hepatitis

2023· article· en· W4324366844 on OpenAlex
Luis Antonio Díaz, Eduardo Fuentes–López, Gustavo Ayares, Francisco Idalsoaga, Jorge Arnold, María Ayala-Valverde, Diego Pérez, Jaime Gómez, Rodrigo Escarate, Alejandro Villalón, Carolina Ramírez, María Hernández‐Tejero, Wei Zhang, Steve Qian, Douglas A. Simonetto, Joseph Ahn, Seth Buryska, Winston Dunn, Heer Mehta, Rohit Agrawal, Joaquín Cabezas, Inés García-Carrera, Berta Cuyàs, María Poca, Germán Soriano, Shiv Kumar Sarin, Rakhi Maiwall, Prasun K. Jalal, Saba Abdulsada, Fatima Higuera‐de la Tijera, Anand V. Kulkarni, Padaki Nagaraja Rao, Patricia Guerra Salazar, Ľubomír Skladaný, Natália Bystrianska, Ana Clemente, Clara Villaseca-Gómez, Tehseen Haider, Kristina R. Chacko, Gustavo Romero, Florencia Pollarsky, Juan Carlos Restrepo, Susana Castro-Sánchez, Luis Toro, Pamela Yaquich, Manuel Mendizábal, María Laura Garrido, Sebastián Marciano, Melisa Dirchwolf, Vı́ctor Vargas, César Jiménez, Alexandre Louvet, Guadalupe García–Tsao, Juan Pablo Roblero, Juan G. Abraldeṣ, Vijay H. Shah, Patrick S. Kamath, Marco Arrese, Ashwani K. Singal, Ramón Bataller, Juan Pablo Arab

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

VenueJHEP Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsLondon Health Sciences CentreUniversity of AlbertaWestern University
FundersFondo Nacional de Desarrollo Científico y TecnológicoNational Center for Advancing Translational SciencesNational Institute on Alcohol Abuse and AlcoholismNational Institute of Diabetes and Digestive and Kidney DiseasesAgencia Nacional de Investigación y Desarrollo
KeywordsRenal replacement therapyMedicineIntensive care medicineAlcoholInternal medicineBiology

Abstract

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•AH hepatitis is associated with multi-organ failure and high short-term mortality.•MELD 3.0 predicted 30- and 90-day mortality better compared with the MELD-Na score and mDF.•MELD 3.0 was not superior to MELD and ABIC scores in predicting mortality, but its classification accuracy was similar between countries.•MELD 3.0 was the best predictor of renal replacement therapy requirements compared with other models. Background & AimsModel for End-Stage Liver Disease (MELD) score better predicts mortality in alcohol-associated hepatitis (AH) but could underestimate severity in women and malnourished patients. Using a global cohort, we assessed the ability of the MELD 3.0 score to predict short-term mortality in AH.MethodsThis was a retrospective cohort study of patients admitted to hospital with AH from 2009 to 2019. The main outcome was all-cause 30-day mortality. We compared the AUC using DeLong's method and also performed a time-dependent AUC with competing risks analysis.ResultsA total of 2,124 patients were included from 28 centres from 10 countries on three continents (median age 47.2 ± 11.2 years, 29.9% women, 71.3% with underlying cirrhosis). The median MELD 3.0 score at admission was 25 (20–33), with an estimated survival of 73.7% at 30 days. The MELD 3.0 score had a better performance in predicting 30-day mortality (AUC:0.761, 95%CI:0.732–0.791) compared with MELD sodium (MELD-Na; AUC: 0.744, 95% CI: 0.713–0.775; p = 0.042) and Maddrey’s discriminant function (mDF) (AUC: 0.724, 95% CI: 0.691–0.757; p = 0.013). However, MELD 3.0 did not perform better than traditional MELD (AUC: 0.753, 95% CI: 0.723–0.783; p = 0.300) and Age-Bilirubin-International Normalised Ratio-Creatinine (ABIC) (AUC:0.757, 95% CI: 0.727–0.788; p = 0.765). These results were consistent in competing-risk analysis, where MELD 3.0 (AUC: 0.757, 95% CI: 0.724–0.790) predicted better 30-day mortality compared with MELD-Na (AUC: 0.739, 95% CI: 0.708–0.770; p = 0.028) and mDF (AUC:0.717, 95% CI: 0.687–0.748; p = 0.042). The MELD 3.0 score was significantly better in predicting renal replacement therapy requirements during admission compared with the other scores (AUC: 0.844, 95% CI: 0.805–0.883).ConclusionsMELD 3.0 demonstrated better performance compared with MELD-Na and mDF in predicting 30-day and 90-day mortality, and was the best predictor of renal replacement therapy requirements during admission for AH. However, further prospective studies are needed to validate its extensive use in AH.Impact and implicationsSevere AH has high short-term mortality. The establishment of treatments and liver transplantation depends on mortality prediction. We evaluated the performance of the new MELD 3.0 score to predict short-term mortality in AH in a large global cohort. MELD 3.0 performed better in predicting 30- and 90-day mortality compared with MELD-Na and mDF, but was similar to MELD and ABIC scores. MELD 3.0 was the best predictor of renal replacement therapy requirements. Thus, further prospective studies are needed to support the wide use of MELD 3.0 in AH. Model for End-Stage Liver Disease (MELD) score better predicts mortality in alcohol-associated hepatitis (AH) but could underestimate severity in women and malnourished patients. Using a global cohort, we assessed the ability of the MELD 3.0 score to predict short-term mortality in AH. This was a retrospective cohort study of patients admitted to hospital with AH from 2009 to 2019. The main outcome was all-cause 30-day mortality. We compared the AUC using DeLong's method and also performed a time-dependent AUC with competing risks analysis. A total of 2,124 patients were included from 28 centres from 10 countries on three continents (median age 47.2 ± 11.2 years, 29.9% women, 71.3% with underlying cirrhosis). The median MELD 3.0 score at admission was 25 (20–33), with an estimated survival of 73.7% at 30 days. The MELD 3.0 score had a better performance in predicting 30-day mortality (AUC:0.761, 95%CI:0.732–0.791) compared with MELD sodium (MELD-Na; AUC: 0.744, 95% CI: 0.713–0.775; p = 0.042) and Maddrey’s discriminant function (mDF) (AUC: 0.724, 95% CI: 0.691–0.757; p = 0.013). However, MELD 3.0 did not perform better than traditional MELD (AUC: 0.753, 95% CI: 0.723–0.783; p = 0.300) and Age-Bilirubin-International Normalised Ratio-Creatinine (ABIC) (AUC:0.757, 95% CI: 0.727–0.788; p = 0.765). These results were consistent in competing-risk analysis, where MELD 3.0 (AUC: 0.757, 95% CI: 0.724–0.790) predicted better 30-day mortality compared with MELD-Na (AUC: 0.739, 95% CI: 0.708–0.770; p = 0.028) and mDF (AUC:0.717, 95% CI: 0.687–0.748; p = 0.042). The MELD 3.0 score was significantly better in predicting renal replacement therapy requirements during admission compared with the other scores (AUC: 0.844, 95% CI: 0.805–0.883). MELD 3.0 demonstrated better performance compared with MELD-Na and mDF in predicting 30-day and 90-day mortality, and was the best predictor of renal replacement therapy requirements during admission for AH. However, further prospective studies are needed to validate its extensive use in AH.

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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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.127
GPT teacher head0.378
Teacher spread0.250 · 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