Evaluation of chronic hepatitis B patients who voluntarily discontinued oral antiviral therapy: is there an answer to the controversial topic?

OBJECTIVE: The uncertain treatment duration for nucleos(t)ide analogues (NA) used in the treatment of chronic hepatitis B (CHB) is an important problem for both patients and physicians. The aim of this study was to evaluate the determinants of virologic relapse (VR) and the optimum time of treatment discontinuation in the follow-up of CHB patients who voluntarily discontinued treatment after virological suppression was achieved under NA use. METHODS: Data from 138 patients from 11 centers were included in this registry-based study. Factors associated with VR were investigated using multivariate Cox regression analysis. RESULTS: Ninety-nine (71.7%) of the patients were HBeAg (Hepatitis B e antigen) negative. During the 24-month follow-up period after treatment discontinuation, VR occurred in 58.7% (n = 81) of all patients and 57.6% (n = 57) of HBeAg-negative patients. The duration of NA treatment was significantly shorter (cutoff 60 months) in HBeAg-negative patients who later developed VR. In addition, the duration of virologic remission achieved under NA treatment was significantly shorter (cutoff 52 months) in those who later developed VR. In the Cox multivariate regression model of HBeAg-negative patients, having less than 60 months of NA treatment (HR = 2.568; CI:1.280-5.148; P  = 0.008) and the levels of alanine aminotransferase being equal to or higher than twice the upper level of normal at the beginning of treatment (HR = 3.753; CI:1.551-9.081; P  = 0.003) were found to be statistically significant and independently associated with VR. CONCLUSION: The findings of this study may provide clinical guidance in terms of determining the most appropriate discontinuation time for NA.

First year real life experience with tenofovir alafenamide fumarate: The pythagorean cohort.

Background and Aim: In chronic hepatitis B infection, antiviral therapy significantly reduces the incidence of complications. This study aimed to present real-life 12-month effectiveness and safety data for TAF. Materials and Methods: This Pythagoras Retrospective Cohort Study included patients from 14 centers in Turkiye. The study presents 12-month results of 480 patients treated with TAF as initial therapy or after switching from another antiviral drug. Results: The study shows treatment of about 78.1% patients with at least one antiviral agent (90.6% tenofovir disoproxil [TDF]). The rate of undetectable HBV DNA increased in both treatment-experienced and naive patients. In TDF-experienced patients, the rate of alanine transaminase (ALT) normalization increased slightly (1.6%) within 12 months, but the change was not statistically significant (p=0.766). Younger age, low albumin, and high body mass index and cholesterol were identified as risk factors for abnormal ALT after 12 months, but no linear relationship was detected. In TDF-experienced patients, renal and bone function indicators showed significant improvement three months after the transition to TAF and remained stable for 12 months. Conclusion: Real-life data demonstrated effective virological and biochemical responses with TAF therapy. After switching to TAF treatment, gains in kidney and bone functions were achieved in the early period.

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF. Various machine learning and deep learning (DL) techniques have been developed for the automated detection of AF. In this review, we focused on the automated AF detection models developed using DL techniques. Twenty-four relevant articles published in international journals were reviewed. DL models based on deep neural network, convolutional neural network (CNN), recurrent neural network, long short-term memory, and hybrid structures were discussed. Our analysis showed that the majority of the studies used CNN models, which yielded the highest detection performance using ECG and heart rate variability signals. Details of the ECG databases used in the studies, performance metrics of the various models deployed, associated advantages and limitations, as well as proposed future work were summarized and discussed. This review paper serves as a useful resource for the researchers interested in developing innovative computer-assisted ECG-based DL approaches for AF detection.

Evaluation of kidney function tests in HIV-positive patients receiving combined antiretroviral therapy.

INTRODUCTION: Human immunodeficiency virus is a chronic infection that attacks the immune system of the human body, particularly CD4 T lymphocytes. Combined antiretroviral therapies are highly effective in virological suppression of human immunodeficiency virus infection. It has been shown that some retroviral therapies have a higher nephrotoxicity potential. As a result of renal injury, serum creatinine increases and the estimated glomerular filtration rate is reduced. The aim of our study was to assess changes in kidney function during a 24-month period in HIV-positive patients who were begun on combined antiretroviral therapy. MATERIAL AND METHODS: A total of 127 HIV-positive patients were enrolled. The patients were divided into five groups; patients who received no therapy were designated as group 1; those who received Dolutegravir/Abacavir/Lamivudine combination as group 2; those who received Elvitegravir/Cobicistat/Emtricitabine/Tenofovir Alafenamide Fumarate combination as group 3; those who received Emtricitabine/Tenofovir Disoproxil Fumarate/Dolutegravir combination as group 4; and those who received Emtricitabine/Tenofovir Disoproxil Fumarate/Raltegravir combination as group 5. We compared the effects of these drugs on estimated glomerular filtration rate during a 24-month follow-up period. RESULTS: At the 24th month of therapy, a significant difference was observed between the estimated glomerular filtration rate (eGFR) levels of the study groups (P < .001). eGFR level was significantly higher in group 4 compared with groups 1, 2 and 3 (P = .009, P < .001, P < .001, respectively), whereas it was significantly lower in group 5 than groups 1, 2 and 3 (P = .005, P < .001, P < .001, respectively). No significant eGFR difference was found between group 4 and group 5 (P > .05). Serum creatinine level was significantly higher in groups 4 and 5 compared with the other groups (P < .001). CONCLUSION: The use of TDF-containing regimens causes renal dysfunction. Therefore, we recommend close monitoring of renal function, especially in patients treated with TDF.

Occult hepatitis B infection in Turkish HIV-infected patients: A multicentre, retrospective, cross-sectional study, Schindler study.

OBJECTIVE: Occult hepatitis B infection (OHBI) appears to have a higher prevalence in populations at high risk for hepatitis B virus (HBV) infection with concomitant liver disease. The aim was to assess the prevalence of OHBI in a sample of human immunodeficiency virus -1 positive and HBV surface antigen-negative (HIV-1+/HBsAg-) Turkish patients. METHODS: Ten centres in Turkey were included in the study. Patients were selected on the basis of a power calculation with a known population size of HIV-positive patients and a reported prevalence of OHBI. Gender, age, occupation, place of residence, treatment and clinical status, and laboratory results, including immunodeficiency panel, antibody tests, hemogram, biochemistry, and coagulation studies were evaluated retrospectively. RESULTS: The number of HIV-infected patients followed in these centres was 3172 and the sample population numbered 278. All 278 were HBsAg negative. The mean age of the sample was 37.2 ± 13.1 years and 235 (84.5%) were male. All but one patient (99.6%) had been treated with antiretroviral therapy. Of the 278 patients, 169 (60.6%) were positive for Anti-HBs and 125 (44.8%) were positive for Anti-HBc IgG. HIV RNA was detected in 203/278 (73%) of the patients. Four HBV DNA (1.4%) were diagnosed with OHBI. There was no significant difference in hemogram, hemoglobin or bilirubin concentrations in those with OHBI compared with the other patients. CONCLUSION: In a representative sample of HIV+ patients from 10 Turkish centres, the prevalence of OHBI was found to be 1.4%. In HIV positive patients, it is important to identify those with OHBI for optimal clinical management and prognosis.

Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review.

Deep learning models have become a popular mode to classify electrocardiogram (ECG) data. Investigators have used a variety of deep learning techniques for this application. Herein, a detailed examination of deep learning methods for ECG arrhythmia detection is provided. Approaches used by investigators are examined, and their contributions to the field are detailed. For this purpose, journal papers have been surveyed according to the methods used. In addition, various deep learning models and experimental studies are described and discussed. A five-class ECG dataset containing 100,022 beats was then utilized for further analysis of deep learning techniques. The constructed models were examined with this dataset, and results are presented. This study therefore provides information concerning deep learning approaches used for arrhythmia classification, and suggestions for further research in this area.