Assessment of stigma among patients infected with hepatitis C virus in Suez City, Egypt

Soltan, Enayat M.; Salama, Hind; Abo-Elmagd, M.

doi:10.1007/s10389-017-0872-6

Cited by 9 publications

(8 citation statements)

References 26 publications

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“…In the present study, gender was not independently associated with stigma. In previous studies in the United States and Australia, women experienced significantly more stigma than men in the community [34,35]. Consistent with the current study, previous studies in Egypt and Pakistan have not found such an association among people with perceived hepatitis C-related stigma [33,36].…”

Section: Discussionsupporting

confidence: 89%

“…In the present study, social rejection and social isolation obtained the highest scores as dimensions of perceived stigma, indicating the worst condtions. In line with previous studies, perceived stigma in HCV patients can result in excessive anxiety of being infected experienced by people in touch with the patients, and this can greatly contribute to higher social isolation and decreased closeness and intimacy in relationships [33,34].…”

Section: Discussionsupporting

confidence: 85%

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Stigma, Anxiety, Depression, and Quality of Life Among Patients With Hepatitis C in Iran

Movahedi

Moshirpanahi²,

Mokhayeri³

et al. 2022

CJHR

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Background: Hepatitis C is one of the most challenging viral infections worldwide. Patients with hepatitis C may experience some disease-related stigma. Objectives: The aim of this study was to evaluate perceived stigma and its role in predicting anxiety, depression, and quality of life among patients with hepatitis C. Materials & Methods: This cross-sectional analytic study was conducted in behavioral counseling centers of three cities, i.e., Khorramabad, Boroujerd and Noorabad, located in the western part of Iran, from May to August 2019. Stratified multistage sampling was used to select 144 patients diagnosed with hepatitis C. The WHOQOL-BREF Scale, Stigma Impact Scale (SIS), Beck Depression Inventory, Second Edition (BDI-II), and Beck Anxiety Inventory, Second Edition (BAI) were used to collect the data. Univariate and multivariate linear regression models were used to estimate the association of covariates on stigma and quality of life. The Stata 16 software was used to analyze the data at the significance level of 0.05. Results: The mean perceived stigma was 66.805 ± 1.291 with social rejection and social isolation achieving the highest scores (23.409 ± 0.551, 20.208 ± 0.437). In the multivariate regression model, depression (B=0.7, 95%; CI: 0.5, 0.89) and anxiety (B=0.21, 95%; CI: 0.02, 0.41) had direct significant associations with stigma independent of age, sex, marital status, and occupation. Depression (B=-0.27, 95%; CI:-0.47, -0.07), anxiety (B=-0.33, 95%; CI: -0.5, -0.16), and stigma (B=-0.41, 95%; CI: -0.56, -0.26) were inversely associated with patients’ quality of life. Conclusion: This study found a high perceived stigma score among HCV patients. Depression and anxiety were significantly associated with stigma. The quality of life of HCV patients were inversely associated with depression, anxiety, and stigma scores.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 85%

Stigma, Anxiety, Depression, and Quality of Life Among Patients With Hepatitis C in Iran

Movahedi

Moshirpanahi²,

Mokhayeri³

et al. 2022

CJHR

View full text Add to dashboard Cite

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“…This group could have been suffering from HCV stigma which might have affected their social and marital lives and required to achieve cure from HCV infection. HCV related stigma has been indicated to clearly affect young married persons in a recent study from Egypt 11 …”

Section: Discussionmentioning

confidence: 99%

Pregnancy outcome of anti‐HCV direct‐acting antivirals: Real‐life data from an Egyptian cohort

AbdAllah

Alboraie

Abdel-Razek

et al. 2021

Liver International

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We aimed to assess the pregnancy outcome in women with chronic HCV who had negative pregnancy test prior to the anti‐HCV course and had unintended pregnancy while on HCV treatment. Hundred patients with a mean age of 30 ± 6.7 y were included and advised to withhold antivirals and continue follow‐up in viral hepatitis and obstetrics centres till delivery. All patients received a 12‐weeks regimen of anti‐HCV [sofosbuvir plus daclatasvir (SOF/DCV): n = 95, SOF/DCV plus ribavirin: n = 3, and paritaprevir/ritonavir/ombitasvir plus ribavirin: n = 2]. Only nine patients completed the full antiviral course against medical advice, and 91 stopped between on‐treatment weeks 4 and 8. Eighty‐eight patients delivered full‐term babies, eight had preterm babies and two had abortions. Of the nine patients who completed the full course of DAAs, seven (77.8%) delivered normal babies, attended their post‐treatment week 12 visit, and all (100%) achieved sustained virological response. No major antiviral‐related adverse events were reported.

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“…Primary care professionals also play an important role in community education, and it has been shown to be effective to cope with the stigma between patients. Numerous challenges such as social labeling, lack of awareness of untreated HCV infection and fear of diagnosis and treatment represent an increased risk [ 23 ]. These barriers can be overcome through intensive educational and awareness activities.…”

Section: Discussionmentioning

confidence: 99%

“…The availability of direct-acting antiviral (DAA) therapy greatly changed the perspective of HCV curability and elimination [ 23 , 24 , 25 , 26 ]. Easily understandable, once-daily and with a high viral response rate, this therapy has transformed the WHO’s goal into an optimistic landscape and has become the state-of-art treatment.…”

Section: Discussionmentioning

confidence: 99%

Resource Management through Artificial Intelligence in Screening Programs—Key for the Successful Elimination of Hepatitis C

et al. 2022

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Background: The elimination of the Hepatitis C virus (HCV) will only be possible if rapid and efficient actions are taken. Artificial neural networks (ANNs) are computing systems based on the topology of the biological brain, containing connected artificial neurons that can be tasked with solving medical problems. Aim: We expanded the previously presented HCV micro-elimination project started in September 2020 that aimed to identify HCV infection through coordinated screening in asymptomatic populations and developed two ANN models able to identify at-risk subjects selected through a targeted questionnaire. Material and method: Our study included 14,042 screened participants from a southwestern region of Oltenia, Romania. Each participant completed a 12-item questionnaire along with anti-HCV antibody rapid testing. Hepatitis-C-positive subjects were linked to care and ultimately could receive antiviral treatment if they had detectable viremia. We built two ANNs, trained and tested on the dataset derived from the questionnaires and then used to identify patients in a similar, already existing dataset. Results: We found 114 HCV-positive patients (81 females), resulting in an overall prevalence of 0.81%. We identified sharing personal hygiene items, receiving blood transfusions, having dental work or surgery and re-using hypodermic needles as significant risk factors. When used on an existing dataset of 15,140 persons (119 HCV cases), the first ANN models correctly identified 97 (81.51%) HCV-positive subjects through 13,401 tests, while the second ANN model identified 81 (68.06%) patients through only 5192 tests. Conclusions: The use of ANNs in selecting screening candidates may improve resource allocation and prioritize cases more prone to severe disease.

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Assessment of stigma among patients infected with hepatitis C virus in Suez City, Egypt

Cited by 9 publications

References 26 publications

Stigma, Anxiety, Depression, and Quality of Life Among Patients With Hepatitis C in Iran

Stigma, Anxiety, Depression, and Quality of Life Among Patients With Hepatitis C in Iran

Pregnancy outcome of anti‐HCV direct‐acting antivirals: Real‐life data from an Egyptian cohort

Resource Management through Artificial Intelligence in Screening Programs—Key for the Successful Elimination of Hepatitis C

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