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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Assessment of minimal hepatic encephalopathy (with emphasis on computerized psychometric tests)
Matthew R Kappus1, Jasmohan S Bajaj
1Division of Gastroenterology, Hepatology and Nutrition, McGuire VA Medical Center, Virginia Commonwealth University, 1201 Broad Rock Boulevard, Richmond, VA 23249, USA.
Abstract:
Minimal hepatic encephalopathy (MHE) is associated with a high risk of development of overt hepatic encephalopathy, impaired quality of life, and driving accidents. The detection of MHE requires specialized testing because it cannot, by definition, be diagnosed on standard clinical examination. Psychometric and neurophysiologic techniques are often used to test for MHE. Paper-pencil psychometric batteries and computerized tests have proved useful in diagnosing MHE and predicting its outcomes. Neurophysiologic tests also provide useful information. The diagnosis of MHE is an important issue for clinicians and patients alike. Testing strategies depend on the normative data available, patient comfort, and local expertise.
Insights
Minimal hepatic encephalopathy (MHE) detection requires specialized tests beyond standard exams. Early diagnosis using psychometric or neurophysiologic methods is crucial for patient outcomes and safety.
Area of Science:
- Hepatology
- Neurology
- Psychometry
Background:
- Minimal hepatic encephalopathy (MHE) poses significant risks, including progression to overt hepatic encephalopathy, reduced quality of life, and increased accident potential.
- MHE is subclinical and undetectable through standard clinical assessments, necessitating specialized diagnostic approaches.
Purpose of the Study:
- To highlight the importance of accurate MHE diagnosis.
- To discuss the utility of various testing modalities for MHE detection and outcome prediction.
Main Methods:
- Utilized psychometric tests, including paper-pencil batteries and computerized assessments.
- Incorporated neurophysiologic techniques for MHE evaluation.
Main Results:
- Psychometric and neurophysiologic tests are effective in diagnosing MHE.
- These specialized tests aid in predicting the clinical outcomes for patients with MHE.
Conclusions:
- Diagnosing MHE is clinically significant for both healthcare providers and patients.
- Testing strategies should consider available normative data, patient preferences, and local expertise for optimal MHE detection.
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