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A cross-sectional assessment of health-related quality of life in Chinese patients with chronic hepatitis c virus infection with EQ-5D

Overview of attention for article published in Health and Quality of Life Outcomes, June 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

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1 Redditor

Citations

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32 Dimensions

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81 Mendeley
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Title
A cross-sectional assessment of health-related quality of life in Chinese patients with chronic hepatitis c virus infection with EQ-5D
Published in
Health and Quality of Life Outcomes, June 2018
DOI 10.1186/s12955-018-0941-8
Pubmed ID
Authors

Rui Huang, Huiying Rao, Jia Shang, Hong Chen, Jun Li, Qing Xie, Zhiliang Gao, Lei Wang, Jia Wei, Jianning Jiang, Jian Sun, Jiaji Jiang, Lai Wei

Abstract

Hepatitis C virus (HCV) infection is one of the most common liver infections, with a decrement in HRQoL of HCV patients. This study aims to assess Health-related quality of life (HRQoL) in Chinese patients with chronic HCV infection, and to identify significant predictors of the HRQoL in these patients of China. In this cross-sectional observational study, treatment-naïve Han ethnic adults with chronic HCV infection were enrolled. Adopting European Quality of Life scale (EQ-5D) and EuroQOL visual analogue scale (EQ-VAS) were used to qualify HRQoL. Results were reported in descriptive analyses to describe sociodemographic and clinical characteristics. Multiple linear regression analysis was applied to investigate the associations of these variables with HRQoL. Binary logistic regression analysis was performed to identify associations of these variables with HRQoL by dimensions of EQ-5D. Nine hundred ninety-seven patients were enrolled in the study [median age 46.0 (37.0, 56.0) years; male 54.8%]. Mean EQ-5D index and EQ-VAS score were 0.780 ± 0.083 and 77.2 ± 14.8. Multiple Linear regression analysis showed that income (< 2000 RMB, β = - 0.134; 2000-4999 RMB, β = - 0.085), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.090), disease profile (cirrhosis, β = - 0.114), hyperlipidemia (β = - 0.065) and depression (β = - 0.065) were independently associated with EQ-5D index. Residence (the west, β = 0.087), income (< 2000 RMB, β = - 0.129; 2000-4999 RMB, β = - 0.052), moderate or severe symptoms of discomfort (more than one symptoms, β = - 0.091), disease profile and depression (β = - 0.316) were the influencing factors on EQ-VAS. Binary logistic regression indicated that disease profile and clinical depression were the major influencing factors on all five dimensions of EQ-5D. In this cross-sectional assessment of HCV patients in China, we indicated HRQoL of Chinese HCV patients. Significant negative associations between HRQoL and sociodemographic and clinical factors such as moderate or severe symptoms of discomfort, disease profile and depression emerged. We have to focus on optimally managing care of HCV patients and improving their HRQoL. ClinicalTrials.gov identifier NCT01293279. Date of registration: February 10, 2011.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 11%
Student > Master 9 11%
Student > Bachelor 7 9%
Researcher 7 9%
Student > Doctoral Student 3 4%
Other 12 15%
Unknown 34 42%
Readers by discipline Count As %
Medicine and Dentistry 21 26%
Psychology 6 7%
Nursing and Health Professions 5 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Agricultural and Biological Sciences 3 4%
Other 9 11%
Unknown 33 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 June 2018.
All research outputs
#3,981,376
of 23,090,520 outputs
Outputs from Health and Quality of Life Outcomes
#398
of 2,188 outputs
Outputs of similar age
#76,986
of 328,710 outputs
Outputs of similar age from Health and Quality of Life Outcomes
#33
of 71 outputs
Altmetric has tracked 23,090,520 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,188 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 328,710 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.