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      Effect of increased potassium intake on cardiovascular risk factors and disease: systematic review and meta-analyses

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          Abstract

          Objective To conduct a systematic review of the literature and meta-analyses to fill the gaps in knowledge on potassium intake and health.

          Data sources Cochrane Central Register of Controlled Trials, Medline, Embase, WHO International Clinical Trials Registry Platform, Latin American and Caribbean Health Science Literature Database, and the reference lists of previous reviews.

          Study selection Randomised controlled trials and cohort studies reporting the effects of potassium intake on blood pressure, renal function, blood lipids, catecholamine concentrations, all cause mortality, cardiovascular disease, stroke, and coronary heart disease were included.

          Data extraction and synthesis Potential studies were independently screened in duplicate, and their characteristics and outcomes were extracted. When possible, meta-analysis was done to estimate the effects (mean difference or risk ratio with 95% confidence interval) of higher potassium intake by using the inverse variance method and a random effect model.

          Results 22 randomised controlled trials (including 1606 participants) reporting blood pressure, blood lipids, catecholamine concentrations, and renal function and 11 cohort studies (127 038 participants) reporting all cause mortality, cardiovascular disease, stroke, or coronary heart disease in adults were included in the meta-analyses. Increased potassium intake reduced systolic blood pressure by 3.49 (95% confidence interval 1.82 to 5.15) mm Hg and diastolic blood pressure by 1.96 (0.86 to 3.06) mm Hg in adults, an effect seen in people with hypertension but not in those without hypertension. Systolic blood pressure was reduced by 7.16 (1.91 to 12.41) mm Hg when the higher potassium intake was 90-120 mmol/day, without any dose response. Increased potassium intake had no significant adverse effect on renal function, blood lipids, or catecholamine concentrations in adults. An inverse statistically significant association was seen between potassium intake and risk of incident stroke (risk ratio 0.76, 0.66 to 0.89). Associations between potassium intake and incident cardiovascular disease (risk ratio 0.88, 0.70 to 1.11) or coronary heart disease (0.96, 0.78 to 1.19) were not statistically significant. In children, three controlled trials and one cohort study suggested that increased potassium intake reduced systolic blood pressure by a non-significant 0.28 (−0.49 to 1.05) mm Hg.

          Conclusions High quality evidence shows that increased potassium intake reduces blood pressure in people with hypertension and has no adverse effect on blood lipid concentrations, catecholamine concentrations, or renal function in adults. Higher potassium intake was associated with a 24% lower risk of stroke (moderate quality evidence). These results suggest that increased potassium intake is potentially beneficial to most people without impaired renal handling of potassium for the prevention and control of elevated blood pressure and stroke.

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          Most cited references 58

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          Quantifying heterogeneity in a meta-analysis.

          The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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            GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.

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              The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration

              Systematic reviews and meta-analyses are essential to summarise evidence relating to efficacy and safety of healthcare interventions accurately and reliably. The clarity and transparency of these reports, however, are not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (quality of reporting of meta-analysis) statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realising these issues, an international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and meta-analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this explanation and elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA statement, this document, and the associated website (www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.
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                Author and article information

                Contributors
                Role: scientist
                Role: intern
                Role: independent consultant
                Role: senior lecturer in research synthesis and nutrition
                Role: professor
                Role: Cephalon professor of cardiovascular medicine & epidemiology
                Journal
                BMJ
                BMJ
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2013
                4 April 2013
                : 346
                Affiliations
                [1 ]Nutrition Policy and Scientific Advice Unit, Department of Nutrition for Health and Development, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland
                [2 ]200 Wheeler Avenue, Staten Island, NY 10314, USA
                [3 ]Norwich Medical School, University of East Anglia, Norwich NR4 7TJ, UK
                [4 ]Department of Epidemiology and Biostatistics and MRC-HPA Centre for Environment and Health, Imperial College London, London, UK
                [5 ]World Health Organization Collaborating Centre for Nutrition, Warwick Medical School, Coventry CV2 2DX, UK
                Author notes
                Correspondence to: N J Aburto  nancy.aburto@ 123456wfp.org
                Article
                abun007498
                10.1136/bmj.f1378
                4816263
                23558164
                © Aburto et al 2013

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) 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 and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/.

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