Nonalcoholic Fatty Liver Disease: Evidence-Based Management and Early Recognition of Nonalcoholic Steatohepatitis

Clinical practice gaps and challenges in non-alcoholic steatohepatitis care: An international physician needs assessment

BACKGROUND AND AIMS

Even as several pharmacological treatments for non-alcoholic steatohepatitis (NASH) are in development, the incidence of NASH is increasing on an international scale. We aim to assess clinical practice gaps and challenges of hepatologists and endocrinologists when managing patients with NASH in four countries (Germany/Italy/United Kingdom/United States) to inform educational interventions.

METHODS

A sequential mixed-method design was used: qualitative semi-structured interviews followed by quantitative online surveys. Participants were hepatologists and endocrinologists practising in one of the targeted countries. Interview data underwent thematic analysis and survey data were analysed with chi-square and Kruskal-Wallis tests.

RESULTS

Most interviewees (n = 24) and surveyed participants (89% of n = 224) agreed that primary care must be involved in screening for NASH, yet many faced challenges involving and collaborating with them. Endocrinologists reported low knowledge of which blood markers to use when suspecting NASH (56%), when to order an MRI (65%) or ultrasound/FibroScan® (46%), and reported sub-optimal skills interpreting alanine aminotransferase (ALT, 37%) and aspartate aminotransferase (AST, 38%) blood marker test results, causing difficulty during diagnosis. Participants believed that more evidence is needed for upcoming therapeutic agents; yet, they reported sub-optimal knowledge of eligibility criteria for clinical trials. Knowledge and skill gaps when managing comorbidities, as well as skill gaps facilitating patient lifestyle changes were reported.

CONCLUSIONS

Educational interventions are needed to address the knowledge and skill gaps identified and to develop strategies to optimize patient care, which include implementing relevant care pathways, encouraging referrals and testing, and multidisciplinary collaboration, as suggested by the recent Global Consensus statement on NAFLD.

Automatic Classification of Fatty Liver Disease Based on Supervised Learning and Genetic Algorithm

Fatty liver disease is considered a critical illness that should be diagnosed and detected at an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this disease, radiologists commonly use ultrasound images. However, because of their low quality, radiologists found it challenging to recognize this disease using ultrasonic images. To avoid this problem, a Computer-Aided Diagnosis technique is developed in the current study, using Machine Learning Algorithms and a voting-based classifier to categorize liver tissues as being fatty or normal, based on extracting ultrasound image features and a voting-based classifier. Four main contributions are provided by our developed method: firstly, the classification of liver images is achieved as normal or fatty without a segmentation phase. Secondly, compared to our proposed work, the dataset in previous works was insufficient. A combination of 26 features is the third contribution. Based on the proposed methods, the extracted features are Gray-Level Co-Occurrence Matrix (GLCM) and First-Order Statistics (FOS). The fourth contribution is the voting classifier used to determine the liver tissue type. Several trials have been performed by examining the voting-based classifier and J48 algorithm on a dataset. The obtained TP, TN, FP, and FN were 94.28%, 97.14%, 5.71%, and 2.85%, respectively. The achieved precision, sensitivity, specificity, and F1-score were 94.28%, 97.05%, 94.44%, and 95.64%, respectively. The achieved classification accuracy using a voting-based classifier was 95.71% and in the case of using the J48 algorithm was 93.12%. The proposed work achieved a high performance compared with the research works.

Cross-sectional pilot study to assess primary healthcare workers' knowledge of nonalcoholic fatty liver disease in a marginalized community in Mexico

The registered incidence of nonalcoholic fatty liver disease (NAFLD) in primary healthcare centers is lower than expected, suggesting a lack of awareness by primary care healthcare professionals. The implementation of educational tools for healthcare workers has been found to increase timely referral and treatment of patients. We aimed to determine healthcare workers' knowledge of NAFLD to identify their educational needs in one marginalized region. We performed a cross-sectional survey of 261 healthcare professionals in Tlapa de Comonfort, Guerrero, Mexico from October 2019 to December 2019. We created a questionnaire that assessed domains most relevant to NAFLD knowledge. Two hundred and forty-six questionnaires were completed. Of the respondents, 38.3% were nurses and 63.4% were women. Most nurses identified NAFLD as a prevalent (89%) and preventable (93%) disease. Hypertension (33%) and obesity (84%) were recognized as risk factors. The associations between NAFLD and cancer, cirrhosis and cardiovascular disease were identified by 53%, 67% and 72% of respondents, respectively. The largest gaps were found in diagnostic workup, therapeutic approach and the current treatments. We identify modifiable knowledge gaps in NAFLD. Educational strategies for primary care workers could enhance the identification of patients with NAFLD and prevent complications.