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Enregistrement 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 sur 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

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Notice bibliographique

RevueJHEP Reports · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAlcohol Consumption and Health Effects
Établissements canadiensLondon Health Sciences CentreUniversity of AlbertaWestern University
Organismes subventionnairesFondo 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
Mots-clésRenal replacement therapyMedicineIntensive care medicineAlcoholInternal medicineBiology

Résumé

récupéré en direct d'OpenAlex

•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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,666

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,127
Tête enseignante GPT0,378
Écart entre enseignants0,250 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle