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dc.contributor.authorIbrahim, Musa Saulawaen
dc.contributor.authorPang, Dongen
dc.contributor.authorRandhawa, Gurchen
dc.contributor.authorPappas, Yannisen
dc.date.accessioned2019-12-10T13:02:34Z
dc.date.available2019-12-10T13:02:34Z
dc.date.issued2019-09-27
dc.identifier.citationIbrahim MS, Pang D, Randhawa G, Pappas Y (2019) 'Risk models and scores for metabolic syndrome: systematic review protocol', BMJ Open, 9 (e027326)en
dc.identifier.issn2044-6055
dc.identifier.pmid31562141
dc.identifier.doi10.1136/bmjopen-2018-027326
dc.identifier.urihttp://hdl.handle.net/10547/623618
dc.description.abstractIntroduction Metabolic syndrome ‘a clustering of risk factors which includes hypertension central obesity, impaired glucose metabolism with insulin resistance and dyslipidaemia’ affects approximately 20%–25% of the global adult population. Individuals with metabolic syndrome have two to threefold risk of developing cardiovascular disease and a fivefold risk of developing developing diabetes and death from all causes. Although there is rapid proliferation of risk scores for predicting the risk of developing metabolic syndrome later in life, yet, these are seldom used in the practice. Therefore, the purpose of this review is to determine the performance of risk models and scores for predicting the metabolic syndrome. Methods and analysis Articles will be sought for from electronic databases (MEDLINE, CINAHL, PubMed and Web of Science) as well as the Cochrane Library. Further manual search of reference lists and grey literatures will be conducted. The search will cover from the start of indexing to 3 October 2018. Identified studies will be included if they fulfil the study selection criteria. Quality of studies will be appraised using suitable criteria for the risk models. The risk scores in the final sample of the review will be ranked/prioritised based on previous quality criteria for prognostic risk models. Lastly, the impact of the models will be ascertained by tracking citations on Google Scholar. Ethics and dissemination This study does not require formal ethical approval as primary data will not be collected. The results will be disseminated through a peer-reviewed publication and relevant conference presentations.
dc.language.isoenen
dc.publisherBMJen
dc.relation.urlhttps://bmjopen.bmj.com/content/9/9/e027326en
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773348/en
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectmetabolic syndromeen
dc.subjectpredictionen
dc.subjectrisk scoreen
dc.subjectsystematic review protocolen
dc.subjectH123 Public Health Engineeringen
dc.titleRisk models and scores for metabolic syndrome: systematic review protocolen
dc.typeArticleen
dc.contributor.departmentUniversity of Bedfordshireen
dc.identifier.journalBMJ Openen
dc.identifier.pmcidPMC6773348
dc.date.updated2019-12-10T12:59:33Z
dc.description.noteopen access article with cc licence
html.description.abstractIntroduction Metabolic syndrome ‘a clustering of risk factors which includes hypertension central obesity, impaired glucose metabolism with insulin resistance and dyslipidaemia’ affects approximately 20%–25% of the global adult population. Individuals with metabolic syndrome have two to threefold risk of developing cardiovascular disease and a fivefold risk of developing developing diabetes and death from all causes. Although there is rapid proliferation of risk scores for predicting the risk of developing metabolic syndrome later in life, yet, these are seldom used in the practice. Therefore, the purpose of this review is to determine the performance of risk models and scores for predicting the metabolic syndrome. Methods and analysis Articles will be sought for from electronic databases (MEDLINE, CINAHL, PubMed and Web of Science) as well as the Cochrane Library. Further manual search of reference lists and grey literatures will be conducted. The search will cover from the start of indexing to 3 October 2018. Identified studies will be included if they fulfil the study selection criteria. Quality of studies will be appraised using suitable criteria for the risk models. The risk scores in the final sample of the review will be ranked/prioritised based on previous quality criteria for prognostic risk models. Lastly, the impact of the models will be ascertained by tracking citations on Google Scholar. Ethics and dissemination This study does not require formal ethical approval as primary data will not be collected. The results will be disseminated through a peer-reviewed publication and relevant conference presentations.


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