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      Effectiveness and safety of immune response to SARS‑CoV‑2 vaccine in patients with chronic kidney disease and dialysis: A systematic review and meta‑analysis

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          Abstract

          The coronavirus disease 2019 (COVID-19) vaccination is the most effective way to prevent COVID-19. However, for chronic kidney disease patients on long-term dialysis, there is a lack of evidence regarding the efficacy and safety of the immune response to the vaccine. The present meta-analysis explores the efficacy and safety of COVID-19 vaccine in the immune response of patients with chronic kidney disease (CKD) undergoing dialysis. PubMed, Web of Science, Science Direct, and Cochrane Library databases were systematically searched from January 1, 2020, to December 31, 2022. Data analysis was performed using REVMAN 5.1s and Stata14 software. Baseline data and endpoint events were extracted, mainly including age, sex, dialysis vintage, body mass index (BMI), vaccine type and dose, history of COVID-19 infection, seropositivity rate, antibody titer, pain at injection site, headache and other safety events. The meta-analysis included 33 trials involving 81,348 patients. The immune efficacy of patients with CKD and dialysis was 80% (95 CI, 73-87%). The seropositivity rate of individuals without COVID-19 infection was 76.48% (3,824/5,000), while the seropositivity rate of individuals with COVID-19 infection was 80.82% (1,858/2,299). The standard mean difference of antibody titers in CKD and dialysis patients with or without COVID-19 infection was 27.73 (95% CI, -19.58-75.04). A total of nine studies reported the most common adverse events: Pain at the injection site, accounting for 18% (95 CI, 6-29%), followed by fatigue and headache, accounting for 8 (95 CI, 4-13%) and 6% (95 CI, 2-9%), respectively. COVID-19 vaccine benefitted patients with CKD undergoing dialysis with seropositivity rate ≥80%. Adverse events such as fatigue, headache, and pain at the injection site may occur after COVID-19 vaccination but the incidence is low.

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          A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster

          Summary Background An ongoing outbreak of pneumonia associated with a novel coronavirus was reported in Wuhan city, Hubei province, China. Affected patients were geographically linked with a local wet market as a potential source. No data on person-to-person or nosocomial transmission have been published to date. Methods In this study, we report the epidemiological, clinical, laboratory, radiological, and microbiological findings of five patients in a family cluster who presented with unexplained pneumonia after returning to Shenzhen, Guangdong province, China, after a visit to Wuhan, and an additional family member who did not travel to Wuhan. Phylogenetic analysis of genetic sequences from these patients were done. Findings From Jan 10, 2020, we enrolled a family of six patients who travelled to Wuhan from Shenzhen between Dec 29, 2019 and Jan 4, 2020. Of six family members who travelled to Wuhan, five were identified as infected with the novel coronavirus. Additionally, one family member, who did not travel to Wuhan, became infected with the virus after several days of contact with four of the family members. None of the family members had contacts with Wuhan markets or animals, although two had visited a Wuhan hospital. Five family members (aged 36–66 years) presented with fever, upper or lower respiratory tract symptoms, or diarrhoea, or a combination of these 3–6 days after exposure. They presented to our hospital (The University of Hong Kong-Shenzhen Hospital, Shenzhen) 6–10 days after symptom onset. They and one asymptomatic child (aged 10 years) had radiological ground-glass lung opacities. Older patients (aged >60 years) had more systemic symptoms, extensive radiological ground-glass lung changes, lymphopenia, thrombocytopenia, and increased C-reactive protein and lactate dehydrogenase levels. The nasopharyngeal or throat swabs of these six patients were negative for known respiratory microbes by point-of-care multiplex RT-PCR, but five patients (four adults and the child) were RT-PCR positive for genes encoding the internal RNA-dependent RNA polymerase and surface Spike protein of this novel coronavirus, which were confirmed by Sanger sequencing. Phylogenetic analysis of these five patients' RT-PCR amplicons and two full genomes by next-generation sequencing showed that this is a novel coronavirus, which is closest to the bat severe acute respiatory syndrome (SARS)-related coronaviruses found in Chinese horseshoe bats. Interpretation Our findings are consistent with person-to-person transmission of this novel coronavirus in hospital and family settings, and the reports of infected travellers in other geographical regions. Funding The Shaw Foundation Hong Kong, Michael Seak-Kan Tong, Respiratory Viral Research Foundation Limited, Hui Ming, Hui Hoy and Chow Sin Lan Charity Fund Limited, Marina Man-Wai Lee, the Hong Kong Hainan Commercial Association South China Microbiology Research Fund, Sanming Project of Medicine (Shenzhen), and High Level-Hospital Program (Guangdong Health Commission).
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            ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

            Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
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              Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

              Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Biomed Rep
                Biomed Rep
                BR
                Biomedical Reports
                D.A. Spandidos
                2049-9434
                2049-9442
                May 2024
                19 March 2024
                19 March 2024
                : 20
                : 5
                : 78
                Affiliations
                Department of Nephrology, The First People's Hospital of Jiashan, Jiaxing, Zhejiang 314100, P.R. China
                Author notes
                Correspondence to: Dr Kejia Li, Department of Nephrology, The First People's Hospital of Jiashan, 1218 Tiyu South Road, Jiaxing Zhejiang 314100, P.R. China shaoyang_wtju.edu.cn xuyunze2012@ 123456sina.com

                *Contributed equally

                Article
                BR-20-5-01766
                10.3892/br.2024.1766
                10999903
                38590946
                ab3bd273-e8c2-48be-a0b6-260384409712
                Copyright: © 2024 Li et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 18 October 2023
                : 02 February 2024
                Funding
                Funding: No funding was received.
                Categories
                Articles

                coronavirus disease 2019 vaccine,chronic kidney disease,dialysis,immune response,safety,meta-analysis

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