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Journal ArticleDOI

Global burden of influenza-associated lower respiratory tract infections and hospitalizations among adults: A systematic review and meta-analysis

01 Mar 2021-PLOS Medicine (Public Library of Science)-Vol. 18, Iss: 3
TL;DR: In this paper, the authors used meta-analytic proportions to global estimates of lower respiratory infections (LRIs) and hospitalizations from the Global Burden of Disease study in adults ≥20 years and by age groups (20−64 years and ≥65 years) to obtain the number of influenza-associated LRI episodes and hospitalization for 2016.
Abstract: Background Influenza illness burden is substantial, particularly among young children, older adults, and those with underlying conditions. Initiatives are underway to develop better global estimates for influenza-associated hospitalizations and deaths. Knowledge gaps remain regarding the role of influenza viruses in severe respiratory disease and hospitalizations among adults, particularly in lower-income settings. Methods and findings We aggregated published data from a systematic review and unpublished data from surveillance platforms to generate global meta-analytic estimates for the proportion of acute respiratory hospitalizations associated with influenza viruses among adults. We searched 9 online databases (Medline, Embase, CINAHL, Cochrane Library, Scopus, Global Health, LILACS, WHOLIS, and CNKI; 1 January 1996–31 December 2016) to identify observational studies of influenza-associated hospitalizations in adults, and assessed eligible papers for bias using a simplified Newcastle–Ottawa scale for observational data. We applied meta-analytic proportions to global estimates of lower respiratory infections (LRIs) and hospitalizations from the Global Burden of Disease study in adults ≥20 years and by age groups (20–64 years and ≥65 years) to obtain the number of influenza-associated LRI episodes and hospitalizations for 2016. Data from 63 sources showed that influenza was associated with 14.1% (95% CI 12.1%–16.5%) of acute respiratory hospitalizations among all adults, with no significant differences by age group. The 63 data sources represent published observational studies (n = 28) and unpublished surveillance data (n = 35), from all World Health Organization regions (Africa, n = 8; Americas, n = 11; Eastern Mediterranean, n = 7; Europe, n = 8; Southeast Asia, n = 11; Western Pacific, n = 18). Data quality for published data sources was predominantly moderate or high (75%, n = 56/75). We estimate 32,126,000 (95% CI 20,484,000–46,129,000) influenza-associated LRI episodes and 5,678,000 (95% CI 3,205,000–9,432,000) LRI hospitalizations occur each year among adults. While adults <65 years contribute most influenza-associated LRI hospitalizations and episodes (3,464,000 [95% CI 1,885,000–5,978,000] LRI hospitalizations and 31,087,000 [95% CI 19,987,000–44,444,000] LRI episodes), hospitalization rates were highest in those ≥65 years (437/100,000 person-years [95% CI 265–612/100,000 person-years]). For this analysis, published articles were limited in their inclusion of stratified testing data by year and age group. Lack of information regarding influenza vaccination of the study population was also a limitation across both types of data sources. Conclusions In this meta-analysis, we estimated that influenza viruses are associated with over 5 million hospitalizations worldwide per year. Inclusion of both published and unpublished findings allowed for increased power to generate stratified estimates, and improved representation from lower-income countries. Together, the available data demonstrate the importance of influenza viruses as a cause of severe disease and hospitalizations in younger and older adults worldwide.

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TL;DR: A narrative review of the changing paradigms and latest data regarding the complex relationship between COVID-19 and cerebrovascular disease, and recommendations for the conduct of stroke research and clinical trial planning during the ongoing CO VID-19 pandemic, and for future healthcare crises.
Abstract: As of May 2022, there have been more than 400 million cases (including re-infections) of the systemic acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), and nearly 5 million deaths worldwide. Not only has the coronavirus disease 2019 (COVID-19) pandemic been responsible for diagnosis and treatment delays of a wide variety of conditions, and overwhelmed the allocation of healthcare resources, it has impacted the epidemiology and management of cerebrovascular disease. In this narrative review, we summarize the changing paradigms and latest data regarding the complex relationship between COVID-19 and cerebrovascular disease. Paradoxically, although SARS-CoV-2 has been associated with many thrombotic complications—including ischemic stroke—there have been global declines in ischemic stroke and other cerebrovascular diseases. These epidemiologic shifts may be attributed to patient avoidance of healthcare institutions due to fear of contracting the novel human coronavirus, and also related to declines in other transmissible infectious illnesses which may trigger ischemic stroke. Despite the association between SARS-CoV-2 and thrombotic events, there are inconsistent data regarding targeted antithrombotics to prevent venous and arterial events. In addition, we provide recommendations for the conduct of stroke research and clinical trial planning during the ongoing COVID-19 pandemic, and for future healthcare crises.

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References
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Journal Article
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.

272,030 citations

Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal ArticleDOI
TL;DR: In this article, a model is described in an lmer call by a formula, in this case including both fixed-and random-effects terms, and the formula and data together determine a numerical representation of the model from which the profiled deviance or the profeatured REML criterion can be evaluated as a function of some of model parameters.
Abstract: Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.

50,607 citations

Journal Article
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1 Conceptual issues in the evolution from QUOROM to PRISMA

46,935 citations

01 Jan 2014
TL;DR: The Newcastle-Ottawa Scale (NOS) as discussed by the authors was developed to assess the quality of nonrandomised studies with its design, content and ease of use directed to the task of incorporating the quality assessments in the interpretation of meta-analytic results.
Abstract: Nonrandomised studies, including case-control and cohort studies, can be challenging to implement and conduct. Assessment of the quality of such studies is essential for a proper understanding of nonrandomised studies. The Newcastle-Ottawa Scale (NOS) is an ongoing collaboration between the Universities of Newcastle, Australia and Ottawa, Canada. It was developed to assess the quality of nonrandomised studies with its design, content and ease of use directed to the task of incorporating the quality assessments in the interpretation of meta-analytic results. A 'star system' has been developed in which a study is judged on three broad perspectives: the selection of the study groups; the comparability of the groups; and the ascertainment of either the exposure or outcome of interest for case-control or cohort studies respectively. The goal of this project is to develop an instrument providing an easy and convenient tool for quality assessment of nonrandomised studies to be used in a systematic review.

17,590 citations

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