Viral Hepatitis: Implication Of Viral Types from A To E

Pambuk, Chateen I. Ali; Muhammad, Fatma Mustafa; Ali, Mohammed Rhael

doi:10.34297/ajbsr.2019.04.000852

Cited by 2 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Treatment cost is considered an important factor in adherence to HCV treatment. 17 Free dispensing of medications in the Egyptian program leads to better adherence to therapy. The cost of laboratory investigations was one of the barriers to the completion of treatment.…”

Section: Discussionmentioning

confidence: 99%

Barriers to Completing Therapy for Hepatitis C with Direct-Acting Antivirals: A Real-Life Experience from a Single Treatment Center in Egypt

Ahmed

Shaarawy

Anwar

et al. 2021

J Prim Care Community Health

View full text Add to dashboard Cite

Introduction Interferon-based therapies against the hepatitis C virus had a poor adherence profile. On the other hand, new direct-acting antivirals (DAAs) are orally administered medications, show high efficacy against the hepatitis C virus in addition to a high safety profile. Therefore, adherence to this treatment is expected to improve. Assessment for treatment adherence is mandatory to assess the feasibility of achieving viral hepatitis elimination. Aim The study aims to assess the adherence rate and causes of non-adherence in Egyptian hepatitis C patients who received interferon-free treatment regimens. Methods Retrospective data analysis for 668 hepatitis C patient’s records from August 2014 to October 2019 was done. Assessment of treatment adherence was done by revising the records and phone calls. However, 172 patients were excluded due to the absence of contact data. Rest of patients (n = 496) was categorized into 2 groups: Adherent (n = 432) and non-adherent (n = 64). For whom comparative analysis was done. Results The adherent group (87%) achieved 100 % sustained virological response after 12 weeks (SVR 12). Non-adherence was reported in 12.9% of patients. Low awareness was the main cause of non-adherence (43.75%). BMI was the only significant risk factor for poor adherence ( P = . 04). Other Patient demographics, clinical, and laboratory data didn’t show any significant differences between both groups. Conclusion Interferon-free regimens are tolerable. Raising awareness is mandatory for proper treatment adherence and, subsequently, good clinical outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Barriers to Completing Therapy for Hepatitis C with Direct-Acting Antivirals: A Real-Life Experience from a Single Treatment Center in Egypt

Ahmed

Shaarawy

Anwar

et al. 2021

J Prim Care Community Health

View full text Add to dashboard Cite

show abstract

“…Viral hepatitis, a liver infection, often causes symptoms such as yellow eyes and skin fatigue. The liver performs various functions, such as protein creation, toxin elimination and bile production [ 5 ]. Because of this, hepatitis-induced inflammation can lead to liver dysfunction and health decline in infected individuals.…”

Section: Introductionmentioning

confidence: 99%

Novel graph-based machine-learning technique for viral infectious diseases: application to influenza and hepatitis diseases

Alqaissi,

Alotaibi,

Sher Ramzan

et al. 2023

Annals of Medicine

View full text Add to dashboard Cite

Background Most infectious diseases are caused by viruses, fungi, bacteria and parasites. Their ability to easily infect humans and trigger large-scale epidemics makes them a public health concern. Methods for early detection of these diseases have been developed; however, they are hindered by the absence of a unified, interoperable and reusable model. This study seeks to create a holistic and real-time model for swift, preliminary detection of infectious diseases using symptoms and additional clinical data. Materials and methods In this study, we present a medical knowledge graph (MKG) that leverages multiple data sources to analyse connections between different nodes. Medical ontologies were used to enhance the MKG. We applied various graph algorithms to extract key features. The performance of multiple machine-learning (ML) techniques for influenza and hepatitis detection was assessed, selecting multi-layer perceptron (MLP) and random forest (RF) models due to their superior outcomes. The hyperparameters of both graph-based ML models were automatically fine-tuned. Results Both the graph-based MLP and RF models showcased the least loss and error rates, along with the most specific, accurate recall, precision and F 1 scores. Their Matthews correlation coefficients were also optimal. When compared with existing ML techniques and findings from the literature, these graph-based ML models manifested superior detection accuracy. Conclusions The graph-based MLP and RF models effectively diagnosed influenza and hepatitis, respectively. This underlines the potential of graph data science in enhancing ML model performance and uncovering concealed relationships in the MKG.

show abstract

Viral Hepatitis: Implication Of Viral Types from A To E

Abstract: This work is licensed under Creative Commons Attribution 4.0 License AJBSR.MS.ID.000852.

Cited by 2 publications

References 14 publications

Barriers to Completing Therapy for Hepatitis C with Direct-Acting Antivirals: A Real-Life Experience from a Single Treatment Center in Egypt

Barriers to Completing Therapy for Hepatitis C with Direct-Acting Antivirals: A Real-Life Experience from a Single Treatment Center in Egypt

Novel graph-based machine-learning technique for viral infectious diseases: application to influenza and hepatitis diseases

Contact Info

Product

Resources

About