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Alcoholic Hepatitis: Prognostic Models and Treatment
Gastroenterology Clinics of North America, 2011Alcoholic hepatitis is a distinct subset of alcoholic liver disease. Inflammation and oxidative stress are the two main pathogenetic mechanisms involved in its pathogenesis. Patients with mild disease usually improve with conservative management. However, about 30-50% of those with severe disease succumb to their illness within about 1 month. Therefore,
Ashwani K, Singal, Vijay H, Shah
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Prognostic Models in Acute Liver Failure
Clinics in Liver Disease, 2018There is a strong imperative to develop valid and accurate prognostic modeling for acute liver failure (ALF). Despite the numerous clinical models that have been proposed thus far and the use of some such models, that is, King's College Criteria and Model for End-Stage Liver Disease, in clinical practice to aid decision-making, there is a significant ...
Avantika, Mishra, Vinod, Rustgi
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Prognostic models in the clinical arena
Aging Clinical and Experimental Research, 2012Making a prognosis is to predict the course of a disease and estimate the probability (or risk) of the appearance of a given outcome in relationship to clinical or non-clinical characteristics. Prognostic assessment is usually modelled by multivariable mathematic equations (prognostic models). In this article we describe what a prognostic model is, how
Bolignano Davide +7 more
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2000
Multiple regression analyses have found widespread use in melanoma research. Such methods are natural candidates for prognostic factor studies, where it is desired to examine the joint influence of various clinical, pathologic, and demographic variables on indicators of disease. For example, in a recent article, Schuchter et al.
Ranjini Natarajan, Martin A. Weinstock
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Multiple regression analyses have found widespread use in melanoma research. Such methods are natural candidates for prognostic factor studies, where it is desired to examine the joint influence of various clinical, pathologic, and demographic variables on indicators of disease. For example, in a recent article, Schuchter et al.
Ranjini Natarajan, Martin A. Weinstock
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Prognostic models in the myeloproliferative neoplasms
Blood Reviews, 2020The management of myelofibrosis (MF) is predominantly supportive, with the use of JAK2 inhibitors or allogeneic stem cell transplantation reserved for patients predicted to have poor overall survival. Identification of these patients is aided by a number of prognostic scoring systems, foremost among them the Dynamic International Prognostic Scoring ...
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Prognostic models in primary biliary cholangitis
Journal of Autoimmunity, 2018Risk prediction modelling is important to better understand the determinants of the course and outcome of PBC and to inform the risk across the disease continuum in PBC enabling risk-stratified follow-up care and personalised therapy. Current prognostic models in PBC are based on treatment response to ursodeoxycholic acid because of the well ...
Cristoferi L. +5 more
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Improving Prognostic Modeling in Myelodysplastic Syndromes
Current Hematologic Malignancy Reports, 2016Myelodysplastic syndromes (MDSs) are a heterogeneous group of disorders characterized by the accumulation of complex genetic alterations that drive disease pathogenesis and outcome. Several prognostic models have been developed over the last two decades to risk stratify patients with MDS.
Aziz, Nazha, Mikkael A, Sekeres
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Prognostic models in melanoma.
Seminars in oncology, 1997Predicting which patients with primary melanoma are at risk of developing metastastic disease is important for making rational therapeutic decisions. Tumor thickness alone is the most commonly used predictor of survival, but other clinical and pathologic variables also play an important role.
A C, Halpern, L M, Schuchter
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Prognostic Model Evaluation Metrics
2023 IEEE Aerospace Conference, 2023Shashvat Prakash +2 more
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