71 research outputs found

    Mejorar la transparencia y la reproducibilidad de las revisiones sistemáticas y metanálisis

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    Incluye: PDF de la presentación y video del seminarioLas revisiones sistemáticas pretenden facilitar información creíble para tomar mejores decisiones. Hay evidencias que sugieren que muchas de ellas: No se adhieren a las principales guías y estándares, no presentan la información necesaria para que los usuarios pueden reproducirlas y pueden estar desactualizadas en el momento de la publicación. Una presentación completa y transparente de las revisiones sistemáticas y los metanálisis podría ayudar a mejorar el rigor, la credibilidad y su reproducibilidad.N

    Global mortality from dementia: Application of a new method and results from the Global Burden of Disease Study 2019

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    Introduction: Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. Methods: We meta-analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end-stage disease to calculate the total number of deaths that could be attributed to dementia. Results: We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41–4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27–2.71]) than men (0.56 million [0.14–1.51]), largely but not entirely due to the higher life expectancy in women (age-standardized female-tomale ratio 1.19 [1.10–1.26]). Due to population aging, there was a large increase in allage mortality rates from dementia between 1990 and 2019 (100.1% [89.1–117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. Discussion: Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally.This work was funded by the Bill and Melinda Gates Foundation, Seattle, WA, and by Gates Ventures, Seattle, WA. R. Akinyemi is supported as a FLAIR Research Fellow by the UK Royal Society and the African Academy of Science (Grants FLR/R1/191813 and FCG/R1/201034) U01HG010273 and from the National Institutes of Health (NIH), USA as part of the H3Africa Consortium. F. Carvalho and E. Fernandes acknowledge support from UID/MULTI/04378/2019 and UID/QUI/50006/2019 support with funding from FCT/MCTES, through national funds. L. F. S. Castro-de-Araujo is funded by The Wellcome Trust (Grant 202912/Z/16Z) via a research associate scholarship at Center of Data and Knowledge Integration for Health (CIDACS), Fundação Oswaldo Cruz (Fiocruz). A. Douiri acknowledges financial support from the National Institute for Health Research (NIHR) Biomedical Research and from the NIHR Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust. The views expressed are those of the author and not necessarily those of the King’s College London, NHS, the NIHR or the Department of Health. B. B. Duncan was supported in part by IATS/FAPERGS (465518/2014-1). A. P. Kengne is supported by the South African Medical Research Council. Y. J. Kim was funded by a grant from the Research Management Centre, Xiamen University Malaysia (Grant number: XMUMRF/2020-C6/ITCM/0004). M. Kivimäki reports grants from the UK Medical Research Council (MRC S011676), the US National Institutes on Ageing (NIA R01AG056477) and NordForsk. W. Kukull acknowledges support from U01 AG016976. M Kumar acknowledges support from FIC/NIMHK43 TW010716-03. I. Landires is member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. S. Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research; grant agreement number 01EA1808A). S. Mondello acknowledges support by grant number GR-2013-02354960 from the Italian Ministry of Health. M. R. Phillips is supported in part by Global Alliance for Chronic Diseases-National Natural Science Foundation of China (NSFC. No. 81761128031). P. S. Sachdev acknowledges funding support from NHMRC Australia (grant no 1093086). J. P. Silva acknowledges support from grant number UIDB/04378/2020 from the Applied Molecular Biosciences Unit (UCIBIO), supported through Portuguese national funds via FCT/MCTES. C. E. I. Szoeke is supported by the National Medical Health and Research Council, the Alzheimer’s Association, and The University of Melbourne. R. Tabarés-Seisdedos was supported in part by grant PI17/00719 from ISCIII-FEDER. C. Wu acknowledges support from the Ministry of Science and Technology (2020YFC2005600) and Suzhou Municipal Science and Technology Bureau (SS2019069).S

    Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

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    Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys.S

    Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

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    Background: Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. Methods: We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. Findings: We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4-65·1) million cases globally in 2019 to 152·8 (130·8-175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [-7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64-1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52-1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41-67]) and western Europe (74% [58-90]), and the largest in north Africa and the Middle East (367% [329-403]) and eastern sub-Saharan Africa (357% [323-395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia. Interpretation: Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.F Carvalho and E F Fernandes acknowledge support from the University of Porto (UID/MULTI/04378/2019 and UID/QUI/50006/2019 with funding from FCT/MCTES through national funds). L F S Castro-de-Araujo acknowledges support from the Medical Research Council (London; grant number MC_PC_MR/T03355X/1). V M Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória (DL57/2016/CP1334/CT0006). A Douiri acknowledges support from the NIHR Applied Research Collaboration (ARC) South London at King’s College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. N Ghith acknowledges her salary as a postdoc is covered by a grant to her research group provided by Novo Nordisk Foundation. V K Gupta and V B Gupta acknowledge funding support from National Health and Medical Research Council (NHMRC), Australia. S Haque acknowledges support from Jazan University, Saudi Arabia, for providing access to the Saudi Digital Library for this study. C Herteliu is partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084). Y J Kim was supported by the Research Management Centre, Xiamen University, Malaysia (No. XMUMRF/2020-C6/ITCM/0004). M Kivimäki was supported by the MRC (S011676) and the Wellcome Trust (221854/Z/20/Z). M Kumar acknowledges support from Fogarty International Center (K43 TW010716-04). S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research, grant agreement number 01EA1808A). S Mondello was supported by the Italian Ministry of Health (GR-2013-02354960). A Raggi acknowledges support from a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea – Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). D A S Silva acknowledges support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES; Finance Code 001 / CAPES-PRINT). J P Silva acknowledges support from the Applied Molecular Biosciences Unit (UCIBIO; grant number UIDB/04378/2020), supported through Portuguese national funds via FCT/MCTES.S

    Global, regional, and national mortality among young people aged 10-24 years, 1950-2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background: Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10-24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10-24 years by age group (10-14 years, 15-19 years, and 20-24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10-24 years with that in children aged 0-9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10-24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). Findings: In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39-1·59) worldwide in people aged 10-24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10-14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15-19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1-4 years (2·4%), and around a third less than in females aged 1-4 years (2·5%). The proportion of global deaths in people aged 0-24 years that occurred in people aged 10-24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%. Interpretation: Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10-24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group.Bill & Melinda Gates Foundation.S

    Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019

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    Importance: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. Objective: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. Evidence review: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). Findings: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. Conclusions and relevance: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context ofWorld Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042.S

    How to properly use the PRISMA Statement

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    EditorialN

    Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050.

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    Background: The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods: We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US,2020US, 2020 US per capita, purchasing-power parity-adjusted USpercapita,andasaproportionofgrossdomesticproduct.Weusedvariousmodelstogeneratefuturehealthspendingto2050.Findings:In2019,healthspendinggloballyreached per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings: In 2019, health spending globally reached 8·8 trillion (95% uncertainty interval [UI] 8·7-8·8) or 1132(1119−1143)perperson.Spendingonhealthvariedwithinandacrossincomegroupsandgeographicalregions.Ofthistotal,1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, 40·4 billion (0·5%, 95% UI 0·5-0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0-25·1) of total spending in low-income countries. We estimate that 54⋅8billionindevelopmentassistanceforhealthwasdisbursedin2020.Ofthis,54·8 billion in development assistance for health was disbursed in 2020. Of this, 13·7 billion was targeted toward the COVID-19 health response. 12⋅3billionwasnewlycommittedand12·3 billion was newly committed and 1·4 billion was repurposed from existing health projects. 3⋅1billion(22⋅43·1 billion (22·4%) of the funds focused on country-level coordination and 2·4 billion (17·9%) was for supply chain and logistics. Only 714⋅4million(7⋅7714·4 million (7·7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34·3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to 1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation: Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all.S

    Evaluating the online impact of reporting guidelines for randomised trial reports and protocols: a cross-sectional web-based data analysis of CONSORT and SPIRIT initiatives

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    Reporting guidelines are tools to help improve the transparency, completeness, and clarity of published articles in health research. Specifically, the CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) statements provide evidence-based guidance on what to include in randomised trial articles and protocols to guarantee the efficacy of interventions. These guidelines are subsequently described and discussed in journal articles and used to produce checklists. Determining the online impact (i.e., number and type of links received) of these articles can provide insights into the dissemination of reporting guidelines in broader environments (web-at-large) than simply that of the scientific publications that cite them. To address the technical limitations of link analysis, here the Debug-Validate-Access-Find (DVAF) method is designed and implemented to measure different facets of the guidelines' online impact. A total of 65 articles related to 38 reporting guidelines are taken as a baseline, providing 240,128 URL citations, which are then refined, analysed, and categorised using the DVAF method. A total of 15,582 links to journal articles related to the CONSORT and SPIRIT initiatives were identified. CONSORT 2010 and SPIRIT 2013 were the reporting guidelines that received most links (URL citations) from other online objects (5328 and 2190, respectively). Overall, the online impact obtained is scattered (URL citations are received by different article URL IDs, mainly from link-based DOIs), narrow (limited number of linking domain names, half of articles are linked from fewer than 29 domain names), concentrated (links come from just a few academic publishers, around 60% from publishers), non-reputed (84% of links come from dubious websites and fake domain names) and highly decayed (89% of linking domain names were not accessible at the time of the analysis). In light of these results, it is concluded that the online impact of these guidelines could be improved, and a set of recommendations are proposed to this end.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.S
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