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      Assessment of the quality of life of COVID-19 recovered patients at the Ghana Infectious Disease Centre

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          Abstract

          Background

          The Coronavirus Disease (COVID-19), initially thought to be a respiratory disease, is now known to affect multiple organ systems with variable presentation and devastating or fatal complications. Despite the large numbers of people who have suffered this disease globally, the mid- to long-term impact of COVID-19 on a person’s general well-being and physical function has not been fully investigated in Ghana.

          Aim

          This study sought to determine the Quality of Life (QoL) and associated factors among Ghanaian patients following clinical recovery from COVID-19 infection.

          Methods

          This was a cross-sectional quantitative study involving 150 COVID-19 recovered patients attending the review clinic of the Ghana Infectious Disease Centre. Quality of life was estimated using the EuroQol Group Association five-domain, five-level questionnaire (EQ-5D-5L) while participants’ overall health status was measured on a visual analogue scale (EQ-VAS): a scale ranging from 0 (worst health) to 100 (best health). Kruskal-Wallis tests were used to assess differences in domain and overall QoL scores while quantile regression was used to determine demographic and clinical factors associated with QoL scores.

          Results

          The mean QoL from the EQ-5D-5L assessment tool was (81.5 ± 12.0) %, while the self-reported QoL from the EQ-VAS tool (75.6 ± 22.0) %. Persistence of symptoms after 30 days was significantly associated with EQ-5D-5L QoL (Adjusted median difference [95% CI] = -9.40 [-14.19, -4.61], p<0.001) while access to rehabilitative centres was significantly associated with EQ-VAS QoL (Adjusted median difference [95% CI] = -29.60 [-48.92, -10.29], p = 0.003).

          Conclusion

          Quality of life was relatively good among the COVID-19 recovered patients. Persistence of symptoms and access to rehabilitative centres significantly predicted one’s QoL.

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          Most cited references47

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

            Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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              Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

              There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                18 July 2024
                2024
                : 19
                : 7
                : e0306118
                Affiliations
                [1 ] Department of Anaesthesia, Korle Bu Teaching Hospital, Accra, Ghana
                [2 ] Department of Health Policy, Planning and Management, School of Public Health, Colleges of Health Sciences, University of Ghana, Legon, Accra, Ghana
                [3 ] Department of Biostatistics, School of Public Health, University of Ghana, Legon, Accra, Ghana
                [4 ] Department of Community and Preventative Dentistry, University of Ghana Dental School, Korle Bu, Accra, Ghana
                The Hong Kong Polytechnic University, HONG KONG
                Author notes

                Competing Interests: The authors also declare no competing interests in the submission of this manuscript.

                Author information
                https://orcid.org/0009-0007-8904-2061
                https://orcid.org/0000-0002-0530-8675
                https://orcid.org/0000-0002-7892-4495
                Article
                PONE-D-23-33323
                10.1371/journal.pone.0306118
                11257348
                39024249
                ab38d8d3-f8cf-4e17-ba30-ad05e3cfb22a
                © 2024 Amedewonu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 October 2023
                : 10 June 2024
                Page count
                Figures: 2, Tables: 5, Pages: 17
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Medicine and Health Sciences
                Health Care
                Quality of Life
                People and Places
                Geographical Locations
                Africa
                Ghana
                Medicine and Health Sciences
                Epidemiology
                Pandemics
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                Mental Health and Psychiatry
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Regression Analysis
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
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                All relevant data are within the paper and its Supporting Information files. Dataset is available from the Dryad database (DOI: https://doi.org/10.5061/dryad.fttdz091f).

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