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BACKGROUND: Enhanced liver fibrosis (ELF) score is an accurate, noninvasive test for assessing the severity of liver fibrosis in chronic liver disease, including alcohol-related liver disease. However, whether the ELF score changes during alcohol withdrawal is unknown. This pilot study assessed changes in the ELF score during withdrawal in patients with a history of excessive alcohol intake. METHODS: In this prospective study, ELF was performed on day 0 (D0, at the beginning of hospitalization), at day 7 (D7, on discharge from hospital), and at follow-up visits on days 30 (D30) and 90 (D90). Transient elastography (TE) was also assessed on days 4 (D4) and D30. RESULTS: The study included 35 patients (71% male) with a mean alcohol intake of 139 g/day. On D30 and D90, 8 and 13 patients had resumed alcohol consumption (mean intake of 90 and 80 g/day, respectively). In patients who remained abstinent, the mean ELF score was 8.93 on D0, 9.14 on D30 (p = 0.32), and 9.27 on D90 (p = 0.14). In patients who resumed alcohol, mean ELF score was 9.7 on D0, 10.05 on D30 (p = 0.09), and 9.71 on D90 (p = 0.12). ELF score was comparable over the first months after withdrawal, although there was a slight increase in the first week (mean ELF score increased from 9.24 on D0 to 9.74 on D7, p < 0.001). Mean TE value was 7.9 kPa on D4 and 8.1 kPa on D30 (p = 0.84) in patients who resumed alcohol consumption, and 8.3 and 7.5 kPa (p = 0.03) on D4 and D30, respectively, in abstinent patients. CONCLUSION: The ELF score is stable during the first months after withdrawal and thus appears to be a useful tool to assess liver fibrosis or cirrhosis in this setting. Nevertheless, because in the first week there is a transient increase in ELF score, caution in interpretation is warranted.
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Radiomics is a discipline that involves studying medical images through their digital data. Using "artificial intelligence" algorithms, radiomics utilizes quantitative and high-throughput analysis of an image's textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor's heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical.
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BACKGROUND AND AIMS: A highly sensitive and specific point-of-care method for diagnosing spontaneous bacterial peritonitis (SBP) is currently lacking. The objective of the present study is to evaluate the diagnostic value of a rapid, easy-to-use, mid-infrared fiber evanescent wave spectroscopy (MIR-FEWS) method for ruling out SBP. PATIENTS AND METHODS: Cirrhotic patients (n = 256) at five centers in France were included for suspected SBP or for the scheduled evacuation of ascites fluid. The mid-infrared spectrum of 7 µL of an ascites fluid sample was recorded using a MIR-FEWS system. To define a model for the diagnosis of SBP, the patients were divided into a calibration group (n = 170) and a validation group (n = 86). RESULTS: Most of the patients were male (71%). The mean age was 60.25 years. Alcohol-related liver disease was the most common cause of cirrhosis. SBP was observed in 18% of the patients. For the diagnosis of SBP in the calibration and validation groups, respectively, the model gave areas under the receiver operating characteristic curves of 0.87 and 0.89, sensitivities of 90% and 87%, specificities of 78% and 80%, positive predictive values of 48% and 50%, negative predictive values of 97% and 96%, positive likelihood ratio of 4.09 and 4.35, negative likelihood ratio of 0.13 and 0.16, Youden index of 0.68 and 0.67, and correct classification rates of 80% and 81%. CONCLUSION: The results of this proof-of-concept study show that MIR-FEWS is a highly sensitive diagnostic method for ruling out SBP. The method warrants further investigation.
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Type 2 diabetes mellitus (T2DM) is a frequent comorbidity in patients with cirrhosis that is projected to rise in prevalence due to the worldwide burden of obesity, insulin-resistance and non-alcoholic fatty liver disease. The management of T2DM in patients with cirrhosis is complex given the requirement for accurate adaptation according to the level of liver function impairment, with lack of summary of the little evidence available in the literature. Here, we summarise the data available with respect to the epidemiology and the impact of T2DM in patients with cirrhosis, as well as those on the management of T2DM in these patients. We provide guidance for the diagnosis of T2DM and the monitoring of glycaemic control in patients with cirrhosis, and for the management of nutrition and pharmacological treatments in relation to the level of liver dysfunction.
