The Mortality Index for Alcohol-Associated Hepatitis: A Novel Prognostic Score

Kezer, Camille A.; Buryska, Seth; Ahn, Joseph; Harmsen, William S.; Dunn, Winston; Singal, Ashwani K.; Arab, Juan Pablo; Díaz, Luis Antonio; Arnold, Jorge; Kamath, Patrick S.; Shah, Vijay H.; Simonetto, Douglas A.

doi:10.1016/j.mayocp.2021.10.026

Cited by 9 publications

(4 citation statements)

References 44 publications

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“…Although a new model called the Mortality Index for Alcohol-Associated Hepatitis (MIAAH) was developed to predict short-term mortality, its performance was lower than that of traditional MELD in the validation cohort. 46 Thus, further studies should compare the performance of MIAAH and MELD 3.0 in this population.…”

Section: Discussionmentioning

confidence: 99%

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

Díaz¹,

Fuentes‐López²,

Ayares³

et al. 2023

JHEP Reports

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Section: Discussionmentioning

confidence: 99%

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

Díaz¹,

Fuentes‐López²,

Ayares³

et al. 2023

JHEP Reports

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“…As artificial intelligence (AI) has been more commonly incorporated in health care, there have been attempts of optimizing AAH prognostication through AI. Of note, a multicenter retrospective cohort by Kezer et al [ 43 ] validated a new 30-d mortality scoring system based on age, BUN, albumin, bilirubin and INR. The score was derived through AI: The Mortality Index for Alcohol-Associated Hepatitis.…”

Section: Prognostic Scoring Systemsmentioning

confidence: 99%

“…The score was derived through AI: The Mortality Index for Alcohol-Associated Hepatitis. Performance showed comparable accuracy to clinical scores, however superiority was only demonstrated compared to MDF but not to MELD[ 43 ].…”

Section: Prognostic Scoring Systemsmentioning

confidence: 99%

Prognostic and diagnostic scoring models in acute alcohol-associated hepatitis: A review comparing the performance of different scoring systems

Mitri,

Almeqdadi,

Karagozian

2023

World J Hepatol

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Primary sclerosing cholangitis (PSC) is a chronic and progressive immune-mediated cholangiopathy causing biliary tree inflammation and scarring, leading to liver cirrhosis and end-stage liver disease. Diagnosis of PSC is challenging due to its nonspecific symptoms and overlap with other liver diseases. Despite the rising incidence of PSC, there is no proven medical therapy that can alter the natural history of the disease. While liver transplantation (LT) is the most effective approach for managing advanced liver disease caused by PSC, post-transplantation recurrence of PSC remains a challenge. Therefore, ongoing research aims to develop better therapies for PSC, and continued efforts are necessary to improve outcomes for patients with PSC. This article provides an overview of PSC’s pathogenesis, clinical presentation, and management options, including LT trends and future aspects. It also highlights the need for improved therapeutic options and ethical considerations in providing equitable access to LT for patients with PSC. Additionally, the impact of liver transplant on the quality of life and psychological outcomes of patients with PSC is discussed. Ongoing research into PSC’s pathogenesis and post-transplant recurrence is crucial for improved understanding of the disease and more effective treatment options.

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“…An example is the MELD score, which was generated by logistic regressionin recent studies, the predictive capabilities of the MELD score have been refined using additional non-biased variables. [67][68][69] Similar predictive analytics have recently been used to help clinicians distinguish differential diagnoses such as cholangitis from AH. 70 Although these advances are exciting and will continue to improve over the coming years as we generate even larger data sets and better analytic capabilities, most of these have not been definitively able to improve upon traditional clinician diagnosis.…”

Section: Digital Biomarkersmentioning

confidence: 99%