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Risk models and scores for metabolic syndrome: systematic review protocol

INTRODUCTION: 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 r...

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Autores principales: Ibrahim, Musa Saulawa, Pang, Dong, Randhawa, Gurch, Pappas, Yannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773348/
https://www.ncbi.nlm.nih.gov/pubmed/31562141
http://dx.doi.org/10.1136/bmjopen-2018-027326
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author Ibrahim, Musa Saulawa
Pang, Dong
Randhawa, Gurch
Pappas, Yannis
author_facet Ibrahim, Musa Saulawa
Pang, Dong
Randhawa, Gurch
Pappas, Yannis
author_sort Ibrahim, Musa Saulawa
collection PubMed
description INTRODUCTION: 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. PROSPERO REGISTRATION NUMBER: CRD42019139326
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spelling pubmed-67733482019-10-21 Risk models and scores for metabolic syndrome: systematic review protocol Ibrahim, Musa Saulawa Pang, Dong Randhawa, Gurch Pappas, Yannis BMJ Open Diabetes and Endocrinology INTRODUCTION: 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. PROSPERO REGISTRATION NUMBER: CRD42019139326 BMJ Publishing Group 2019-09-27 /pmc/articles/PMC6773348/ /pubmed/31562141 http://dx.doi.org/10.1136/bmjopen-2018-027326 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Diabetes and Endocrinology
Ibrahim, Musa Saulawa
Pang, Dong
Randhawa, Gurch
Pappas, Yannis
Risk models and scores for metabolic syndrome: systematic review protocol
title Risk models and scores for metabolic syndrome: systematic review protocol
title_full Risk models and scores for metabolic syndrome: systematic review protocol
title_fullStr Risk models and scores for metabolic syndrome: systematic review protocol
title_full_unstemmed Risk models and scores for metabolic syndrome: systematic review protocol
title_short Risk models and scores for metabolic syndrome: systematic review protocol
title_sort risk models and scores for metabolic syndrome: systematic review protocol
topic Diabetes and Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773348/
https://www.ncbi.nlm.nih.gov/pubmed/31562141
http://dx.doi.org/10.1136/bmjopen-2018-027326
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