Diagnosis and Treatment of Low-Grade Hepatic Encephalopathy

Hepatic encephalopathy post-TIPS: Current status and prospects in predictive assessment

Transjugular intrahepatic portosystemic shunt (TIPS) is an essential procedure for the treatment of portal hypertension but can result in hepatic encephalopathy (HE), a serious complication that worsens patient outcomes. Investigating predictors of HE after TIPS is essential to improve prognosis. This review analyzes risk factors and compares predictive models, weighing traditional scores such as Child-Pugh, Model for End-Stage Liver Disease (MELD), and albumin-bilirubin (ALBI) against emerging artificial intelligence (AI) techniques. While traditional scores provide initial insights into HE risk, they have limitations in dealing with clinical complexity. Advances in machine learning (ML), particularly when integrated with imaging and clinical data, offer refined assessments. These innovations suggest the potential for AI to significantly improve the prediction of post-TIPS HE. The study provides clinicians with a comprehensive overview of current prediction methods, while advocating for the integration of AI to increase the accuracy of post-TIPS HE assessments. By harnessing the power of AI, clinicians can better manage the risks associated with TIPS and tailor interventions to individual patient needs. Future research should therefore prioritize the development of advanced AI frameworks that can assimilate diverse data streams to support clinical decision-making. The goal is not only to more accurately predict HE, but also to improve overall patient care and quality of life.

The Value of Electroencephalogram (EEG) Findings in the Evaluation and Treatment Management of Pediatric Acute Liver Failure

Background Pediatric acute liver failure (PALF) is still life-threatening and requires urgent care. The presence of encephalopathy is a clinical diagnosis, but it is more difficult to diagnose in children than in adults, and an electroencephalogram (EEG) can be invaluable. The role of EEG in managing the treatment of patients with PALF, other than the identification of encephalopathy, is unknown. This study aimed to investigate patients' EEGs, which may guide in choosing the most appropriate treatment in encephalopathy children. A further aim was to investigate a new score method, based on the laboratory results, which might indicate the presence of encephalopathy in cases with PALF. Methods Medical data of 33 PALF patients followed in our clinic were reviewed retrospectively. This study included 33 patients, whose EEG recording was taken on the first day of supportive treatment due to liver failure in the pediatric intensive care unit (PICU). The EEG findings were categorized into three classes: normal, epileptic and non-epileptic paroxysmal, and background encephalopathic patterns including widespread slowing and voltage suppression. Result This retrospective study included 13 male and 20 female patients with a mean age at presentation of 4.82±4.81 months whose EEG was performed on the first day of supportive therapy for liver failure in the PICU. The EEG findings were categorized into three groups: normal, epileptic and non-epileptic paroxysms, and encephalopathic patterns including diffuse background slowing and voltage suppression. Comparing EEG findings and treatments, we found that the normal EEG group responded well to liver-supporting therapy and the rate of plasmapheresis treatment was significantly higher in the diffuse slowing group. Patients with diffuse slowing of the EEG were 9.6 times more likely to receive plasmapheresis. We found that above a cut-off of ≥7.5 for the TAI (total bilirubin, albumin, and international normalized ratio (INR)) score used in our study, the risk of developing encephalopathy increased 14.4-fold. Conclusions In PALF, EEG findings can provide findings that will help clinicians in determining treatment selection and prognosis, as well as detecting epileptic focus and encephalopathy. The TAI score can be used to assess the risk of encephalopathy in cases of PALF, when it is challenging to identify encephalopathy or when an EEG is not possible.

Diagnosis of minimal hepatic encephalopathy in a tertiary care center from eastern Romania: validation of the psychometric hepatic encephalopathy score (PHES)

The psychometric hepatic encephalopathy score (PHES) is frequently used as a "gold standard" for the diagnosis of minimal hepatic encephalopathy (MHE). In Romania, there are currently no widely available tests for the detection of MHE. In this study we aimed to standardize the PHES in a healthy Romanian population and to estimate the prevalence of MHE in a group of Romanian patients with liver cirrhosis. A total of 260 healthy volunteers and 106 patients with liver cirrhosis were included in the study. The five neuropsychological tests comprising the PHES were administered to all enroled subjects. Blood samples for routine tests and serum ammonia were collected. In the healthy volunteer group age and education years were found to be predictors of all tests and gender only in two tests: digit symbol test and serial dotting test. The PHES of the healthy volunteer group was 0,43 ± 1,37 and the cut-off between normal and pathological values was set at -3 points. In the liver cirrhosis group the mean PHES was -2,44 ± 3,41, significantly lower than in the control group (p = 0,001). The estimated prevalence of MHE was 34,7 % (37 patients). In patients with cirrhosis there was a significant correlation between PHES and the severity of the liver disease according to Child-Pugh classification (r = 0,529, p = 0,001) and MELD score (r = -0,525, p = 0,001). According to our results, accurate Romanian PHES norms for the diagnosis of MHE have been developed. MHE was diagnosed in a significant proportion of Romanian patients with liver cirrhosis.