Correlation between the patients with Hepatitis C Virus and their Health-Related Quality of Life

Introduction

Hepatitis C virus (HCV) infection is a global health problem and a major cause of morbidity and mortality (Faddan, et al., 2019), Egypt has the highest prevalence of Hepatitis C in the world. Overall, estimates of the HCV rate in the general population have ranged between 10 and 20 percent. Geographically, the Hepatitis C prevalence is higher in Lower Egypt (Nile Delta) than in Upper Egypt and lower in urban compared to rural areas. The economic burden is multiplied by the impact of HCV on health-related quality of life (HRQoL), appreciable at any stage of severity
(Omran et al., 2018).

 In Egypt, a cross-sectional survey of 21 governorates was done by El-Ghitany and Farghaly, (2019) to determine geospatial epidemiology of hepatitis C infection in Egypt found that the participant's age ranged from 14-90 years, the darkest spot of HCV infection in Menoufeya (37.8%) followed by Beni Suef (29.2%) and Minia (28.6%), and anti-HCV prevalence was higher among males.

Quality of Life (QOL) is a popular term that conveys an overall sense of well-being, including aspects of happiness and satisfaction with life as a whole. It is broad and subjective rather than specific and objective. The Complications of advanced liver disease such as encephalopathy, variceal hemorrhage, and ascites have been reported to negatively affect HRQoL. Extra-hepatic manifestations related to HCV as fatigue, irritability, depression, muscle pain, joint pain, and cognitive impairment may also influence the patient’s psychological well-being and self-perceived health
(Jain, et al., 2019).

Chronic infection with HCV has a profound effect on health-related quality of life (HRQoL) – with fatigue, depression, and neurocognitive deficits among the most common complaints. Neuropsychiatric symptoms have prompted research to determine whether the HCV acts within the central nervous system. The replicating virus has been found in central nervous tissues, and changes in neurotransmitter levels in the frontal white matter of patients with chronic hepatitis C are correlated with impaired attention and concentration (Youssef, et al., 2017).

Although treatment-related adverse effects may dissuade people from starting therapy and reduce compliance with associated reductions in sustained viral response, for the majority of patients' viral clearance produces improvements in both HRQoL and long-term prognosis. Novel agents, with improved adverse effect profiles, may allow more patients to achieve a sustained viral response (Zainulabid, 2019).

The nurse must participate in educating individuals with HCV infection to improve HRQL through lifestyle changes initiated through behavioral modification. For example, education on the monitoring of symptoms such as fatigue, body pain, depression, and lack of ability to function effectively. Previous research has shown that individuals chronically infected with HCV respond to interventions focused on increasing knowledge and this, improves functional status and HRQL of individuals with chronic HCV (Youssef et al., 2017).

Significance of the Study:

According to a recent survey done in Egypt, 2015 found the prevalence rate among the population aged from 1-59 years (sample size 1,466) in Minia governorate was 9.0% of them have positive HCV antibody and 6.1% have positive HCV RNA test. HCV has a major impact on the quality of life and can cause patients significant distress. So, this study will be carried out to investigate the effect of HCV infection on HRQOL among patients. Multiple studies worldwide have shown that chronic hepatitis C is associated with considerable impairment of HRQoL (Ministry of Health and Population et al., 2015).

Aim of the study:

Assess the correlation between the patients with Hepatitis C Virus and their Health-Related Quality of Life. 

Research question:

Is there a correlation between the patients with Hepatitis C Virus and their Health-Related Quality of Life impairment?

Research Design:

A Descriptive research design was utilized

Subjects

A convenient sample of two hundred adult patients with HCV newly received Sofosbuvir and Daclatasvir.

Inclusion criteria:

• Adult patient from18- 60 years
• Conscious and oriented
• The patient has early stage of chronic hepatitis C
• Newly received Sofosbuvir and Daclatasvir medication.

Exclusion criteria:

• Musculoskeletal problems.
• Pregnant women.
• Other hepatitis viruses 
• Immunocompromised diseases.
• Obesity (overweight 25 kg) and underweight patients.
• Patients with speech and mental disorders.

.

Setting:

The study was conducted in liver virology outpatients' clinic at Minia University Hospital and Fever Hospital related to ministry of health.

Study duration:

The total data collections were collected over period of 12 months starting from December 2018 to December 2019.

Data Collection Tools:

The current study data were collected by Two tools were designed, prepared, tested, and used for collecting data in this study after extensive reading in the literature review by the investigator (Rand Corporation, 2013).

Tool Ӏ: Bio-socio-demographic characteristics were included in two parts (Appendix B)

1^st part: sociodemographic data : sex, age, marital status, education level, occupation, and residence

2^nd part: Medical information include: past and present medical history, including medical diagnosis, smoking, medication

Tool ӀӀ: A Short-Form health survey (SF-36) questionnaire arabic version adopted byWare and Sherbourne, (1992) & McHorney et al. (1994) to measure the quality of life for patients with hepatitis C virus which include eight health domains: physical functioning (ten items from Q 3 to Q 12), physical role problems (four items from Q 13 to Q 16) and due to emotional problems (three items from Q 17 to Q 19), energy or fatigue (four items:  Q 23, 27, 29, 31), emotional wellbeing (five items Q 24- 26, Q 28, Q 30), social functioning (two items, Q 20, Q 32), Bodily Pain (two items, Q 21 & Q 22),  and general health perceptions (five items: Q 1 and from Q33 to Q 36), which Q 2 refer to current patient health compared to one year ago.

Scoring system

Each subscale is scored from (0 to 100) when patient assessment indicates score 0 this means the worst score for quality of life but when have  100 mean they have the best score for quality of life. While the total scores were less than 50% considered as poor quality of life. If the total scores ranged from 50 % – 75% considered as good quality of life, and when the total scores were 75% or more considered as excellent quality of life.

Tool Validity and Reliability:

A panel of five experts in the field of medical surgicalnursing staff to examine validity of the content. No alterations of the content were be done allowing to the panel judgment on the clearness of sentences, suitability of the content, and categorization of items. Reliability was done by using the alpha Cronbach’s test was .81 and it examined by many studies was 0.80 by McHorney et al. (1994)  

Pilot Study:

Was conducted for 10 % (20 patients) of the total sample to test the study process and to evaluate the efficiency of tools.

Procedure:

The researcher met the patients during a time of outpatient clinics, introducing herself, and explained the purpose and nature of the study. oral consent was obtained to participate in this study. The researcher started a collection of data in 12 months by using Bio-socio-demographic characteristics for 15- 20 minutes for each patient. The researcher distributed the data collection sheets to respondents individually in the reception in the liver virology outpatient patient clinics at Minia university hospital and fever hospital. Collection of the study data was done on daily basis (2 to 3 days /week) during the morning shift. The researcher checked the completeness of each filled form after the participant filled it. Health-related quality of life was measured for every patient before and after 3 months from finishing the treatment.

Statistical data

Statistical analysis was done by using Statistical Package for the Social Science (SPSS IBM 25.0). Quality control was done at the stages of coding and data entry. Data were presented by using descriptive statistics in the form of frequencies and percentages for qualitative variables and mean & standard deviation (SD) for quantitative variables. Chi-square ( ) was used to test the association between two qualitative variables. T-test was used to measure mean differences of quality of life measured by short-form questionnaire (SF-36) between before and after treatment Graphs were done for data visualization using Microsoft Excel.  The P-value of ≤ 0.05 indicates a significant result while the P-value of > 0.05 indicates a non-significant result.

Results:

Table (1): Percentage distribution of Bio-socio-demographic characteristics of the studied Sample (n = 200)

Table (1): presents that 29.0% of the studied patient their age ranged between 31- 40 years with mean 33.4 ± 8.1 years, 62.0% of them was man. The highest percentage of the study sample were married and lived in rural areas constituted (80.0% & 84.0% respectively). Related to occupation status found that two-third (68.0%) of the study sample were jobless.

.

Figure (1): Percentage distribution of studied Sample regarding the duration of disease (n = 200)

Figure (1): illustrates that near to three quarters (72.0%) of the studied sample have duration of their disease from one year ago, while 25.0% of them from one month, and a minority of them from one week.

Figure (2): Percentage distribution of studied Sample regarding smoking habit (n = 200)

Figure (2): demonstrates that near to three quarters (72.0%) of the studied patient was not smokers and more than one-quarter (28.0%) of them was smoker.

Table (2): Mean scores of quality of life domain of the studied sample before and after 3 months from the administration of treatment

Independent t test           **Highly statistical significant difference at ≤  0.01

Table (2): reveals that the total mean score of quality of life domain after 3 months of treatment with Sofosbuvir and Daclatasvir medication was higher than before treatment constitute (75.6 ± 19.2 & 47.6 ± 24.9) respectively with highly statistically significant (0.001).

Table (3 Relation between total Quality of life of the studied sample and their bio-socio-demographic characteristics before administration of Sofosbuvir and Daclatasvir (n= 200).

Chi-test for qualitative variables NS = not statistically significant differences ** Highly statistically significant differences

Table (3): shows that, 69.0% of studied patient who aged between 31- 40 years and 53.8% of the studied patient who aged between 41- 50 years had a poor total quality of life before administration of treatment with Sofosbuvir and Daclatasvir medication, and 73.1% of them who had bachelor degree and 63.1% of them who had basic education had poor quality of life before treatment with statistically significant differences ( 0.005 and 0.005) respectively.

Table (4): Relation between total Quality of life of the studied sample and their bio-socio-demographic characteristics 3 months after the administration of Sofosbuvir and Daclatasvir   (n= 200).

Chi-test for qualitative variables NS = not statistically significant differences

Table (4): reveals that there were no statistically significant total Quality of life of the studied sample and their socio-demographic characteristics 3 months after the administration of treatment. 

Figure (3): Comparison between total Quality of life of the studied sample and their duration of disease before and after 3 months administration of Sofosbuvir and Daclasvir  (n= 200).

Figure (3): illustrates that 59.7% of the studied patient with hepatitis from one year had poor quality of life before administration of treatment with Sofosbuvir and Daclatasvir medication decreased to 12.0% of them after 3 months of treatment

Figure (4): Comparison between total Quality of life of the studied sample and their smoking habits before and after 3 months administration of Sofosbuvir and Daclasvir  (n= 200).

Figure (4): illustrates that 71.4% of the smoker patient had poor quality of life before administration of treatment with Sofosbuvir and Daclatasvir medication decreased to 3.0% of them after 3 months of treatment

Table (5): Correlation between bio-socio-demographic characteristics and their total quality of life measured by short-form of health before and after 3 months of Sofosbuvir and Daclatasvir   administration

Pearson and spearman correlation test**Correlation is significant at the 0.01 level

Table (5): reveals that there was a fair negative association between duration of disease of the studied sample with their total quality of life measured by short-form of health before administration of treatment with Sofosbuvir and Daclatasvir  (r= -.329& P – value < .001).