Dataset Information

Risk models and scores for metabolic syndrome: systematic review protocol.

ABSTRACT:

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.

SUBMITTER: Ibrahim MS

PROVIDER: S-EPMC6773348 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Risk models and scores for metabolic syndrome: systematic review protocol.

Ibrahim Musa Saulawa MS Pang Dong D Randhawa Gurch G Pappas Yannis Y

BMJ open 20190927 9

<h4>Introduction</h4>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 ...[more]

PMID: 31562141

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Project description:ObjectiveTo evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice.DesignSystematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes.Data sourcesMedline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact.Data extractionData were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes.Results8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as "simple" or "easily implemented," although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse.ConclusionMuch work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk "hotspots" for targeted public health interventions.

Project description:BACKGROUND: While many studies have demonstrated positive associations between childhood obesity and adult metabolic risk, important questions remain as to the nature of the relationship. In particular, it is unclear whether the associations reflect the tracking of body mass index (BMI) from childhood to adulthood or an independent level of risk. This systematic review aimed to investigate the relationship between childhood obesity and a range of metabolic risk factors during adult life. OBJECTIVE: To perform an unbiased systematic review to investigate the association between childhood BMI and risk of developing components of metabolic disease in adulthood, and whether the associations observed are independent of adult BMI. DESIGN: Electronic databases were searched from inception until July 2010 for studies investigating the association between childhood BMI and adult metabolic risk. Two investigators independently reviewed studies for eligibility according to the inclusion/exclusion criteria, extracted the data and assessed study quality using the Newcastle-Ottawa Scale. RESULTS: The search process identified 11 articles that fulfilled the inclusion and exclusion criteria. Although several identified weak positive associations between childhood BMI and adult total cholesterol, low-density lipo protein-cholesterol, triglyceride and insulin concentrations, these associations were ameliorated or inversed when adjusted for adult BMI or body fatness. Of the four papers that considered metabolic syndrome as an end point, none showed evidence of an independent association with childhood obesity. CONCLUSIONS: Little evidence was found to support the view that childhood obesity is an independent risk factor for adult blood lipid status, insulin levels, metabolic syndrome or type 2 diabetes. The majority of studies failed to adjust for adult BMI and therefore the associations observed may reflect the tracking of BMI across the lifespan. Interestingly, where adult BMI was adjusted for, the data showed a weak negative association between childhood BMI and metabolic variables, with those at the lower end of the BMI range in childhood, but obese during adulthood at particular risk.

Project description:BACKGROUND:Metabolic syndrome (MetS) is defined as an accumulation of risk factors that include chronic hypertension, dyslipidaemia, insulin resistance and obesity and leads to an increased risk for diabetes, cardiovascular disease and stroke. MetS is widespread and estimated to affect up to a quarter of the global population. Patients with MetS who undergo surgery are associated with an increased risk of postoperative complications when compared with patients with a non-MetS profile. An emerging body of literature points to MetS being associated with a greater risk of postoperative pulmonary complications (PPC) in the surgical patient. PPC are associated with increased postoperative morbidity and mortality, Intensive care unit (ICU) admission, length of stay (ICU and hospital), health care costs, resource usage, unplanned re-intubation and prolonged ventilatory time. METHODS/DESIGN:We will search for relevant studies in the following electronic bibliographic databases: EMBASE, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Scopus as well as scan the reference lists of included studies for potential additional literature. Two authors will independently screen titles and abstracts to identify potentially relevant studies for inclusion based on predefined inclusion and exclusion criteria. The Cochrane Collaboration Review Manager (Review Manager 5) statistical software will be used to conduct this systematic review and meta-analysis and generate forest plots to demonstrate comparison of findings across studies included for meta-analysis. Subgroup and sensitivity analysis will be performed to assess the heterogeneity of included studies. A descriptive synthesis of the statistical data will be provided to summarise the results and findings of the systematic review and meta-analysis. DISCUSSION:This review will be the first to report and summarise the risk for and incidence of PPC in adult patients with MetS undergoing surgery across a range of surgical specialities. The results have the potential to inform the development of evidenced-based interventions to improve the management of PPC in the surgical patient with MetS. Findings from this systematic review and meta-analysis will inform a subsequent Delphi study on priorities and responses to PPC in patients with MetS. We will also disseminate our results through publication in scientific peer-reviewed journals, conference presentations and promotion throughout our network of surgical safety champions in clinical settings. SYSTEMATIC REVIEW REGISTRATION:PROSPERO CRD42019120279.

Dataset Information

Risk models and scores for metabolic syndrome: systematic review protocol.

Introduction

Methods and analysis

Ethics and dissemination

Prospero registration number

Publications

Risk models and scores for metabolic syndrome: systematic review protocol.

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