scholarly journals Renal hemodynamic response to SGLT ‐2 inhibition does not depend on protein intake: an analysis of three randomized controlled trials

2021 ◽  
Author(s):  
Annemarie B. van der Aart‐van der Beek ◽  
David Cherney ◽  
Gozewijn D. Laverman ◽  
Bergur Stefansson ◽  
Daniel H. van Raalte ◽  
...  
Keyword(s):  
Randomized Controlled Trials ◽  
Protein Intake ◽  
Hemodynamic Response ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Renal Hemodynamic

scholarly journals Dose–response relationship between protein intake and muscle mass increase: a systematic review and meta-analysis of randomized controlled trials

2020 ◽  
Vol 79 (1) ◽  
pp. 66-75
Author(s):  
Ryoichi Tagawa ◽  
Daiki Watanabe ◽  
Kyoko Ito ◽  
Keisuke Ueda ◽  
Kyosuke Nakayama ◽  
...  
Keyword(s):  
Systematic Review ◽  
Randomized Controlled Trials ◽  
Lean Body Mass ◽  
Body Mass ◽  
Dose Response ◽  
Protein Intake ◽  
Controlled Trials ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Randomized Controlled

Abstract Context Lean body mass is essential for health, yet consensus regarding the effectiveness of protein interventions in increasing lean body mass is lacking. Objective The aim of this systematic review was to evaluate the dose–response relationship of the effects of protein intake on lean body mass. Data Sources The PubMed and Ichushi-Web databases were searched electronically, and reference lists of the literature included here and in other meta-analyses were searched manually. Study Selection Randomized controlled trials evaluating the effects of protein intake on lean body mass were included. Data Extraction Two authors independently screened the abstracts; 5 reviewed the full texts. Results A total of 5402 study participants from 105 articles were included. In the multivariate spline model, the mean increase in lean body mass associated with an increase in protein intake of 0.1 g/kg of body weight per day was 0.39 kg (95%CI, 0.36–0.41) and 0.12 kg (95%CI, 0.11–0.14) below and above the total protein intake of 1.3 g/kg/d, respectively. Conclusions These findings suggest that slightly increasing current protein intake for several months by 0.1 g/kg/d in a dose-dependent manner over a range of doses from 0.5 to 3.5 g/kg/d may increase or maintain lean body mass. Systematic Review Registration UMIN registration number UMIN000039285.

scholarly journals Dose-response relationship between protein intake and muscle mass increase: a systematic review and meta-analysis of randomized controlled trials

2020 ◽  
Author(s):  
Ryoichi Tagawa ◽  
Daiki Watanabe ◽  
Kyoko Ito ◽  
Keisuke Ueda ◽  
Kyosuke Nakayama ◽  
...  
Keyword(s):  
Randomized Controlled Trials ◽  
Dose Response ◽  
Protein Intake ◽  
Data Extraction ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Response Relationship ◽  
Dose Response Relationship ◽  
Randomized Controlled ◽  
Manual Search

AbstractBackgroundLean body mass (LBM) is essential for health; however, consensus regarding the effectiveness of protein interventions in increasing LBM is lacking.ObjectiveEvaluate the dose-response relationship of the effects of protein on LBM.Data SourcesPubMed and Ichushi-Web databases were searched. A manual search of the references of the literature included here and in other meta-analyses was conducted.Study SelectionRandomized controlled trials evaluating the effect of protein intake on LBM were included.Data ExtractionTwo researchers independently screened the abstracts; five reviewed the full-texts.Results5402 subjects from 105 articles were included. In the multivariate-spline model, the mean and corresponding 95% confidence intervals (CIs) for LBM increase for 0.1 g/kg body weight (BW)/day increment was 0.39 [95% CI, 0.36–0.41] kg and 0.12 [0.11–0.14] kg below and above total protein intake 1.3 g/kg BW/day, respectively.ConclusionsOur findings suggest that slightly increasing current protein intake for several months by 0.1 g/kg BW/day may increase or maintain LBM in a dose-response manner from 0.5 to 3.5 g/kg BW/day.

Abstract 023: The Effect of Dietary Protein on Blood Pressure: A Meta-Analysis of Randomized Controlled Trials

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Casey M Rebholz ◽  
Eleanor E Friedman ◽  
Lindsey J Powers ◽  
Whitney D Arroyave ◽  
Jiang He ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Randomized Controlled Trials ◽  
Diastolic Blood Pressure ◽  
Dietary Protein ◽  
Protein Intake ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Controlled Trials ◽  
Dietary Protein Intake ◽  
Randomized Controlled

Lifestyle modifications such as weight loss, increasing physical activity, and reducing alcohol consumption and salt intake have been consistently shown to decrease blood pressure. Less well understood is whether increased dietary protein intake may also reduce blood pressure and the risk of hypertension. We conducted a meta-analysis of randomized controlled trials to assess the hypothesis that increased dietary protein intake decreases systolic and diastolic blood pressure in adults. MEDLINE, EMBASE, Cochrane Library, Web of Science, a registry of soy research trials, bibliography review, and expert consultation were the sources of English and non-English articles published before April 2011. Search terms included randomized controlled trial, blood pressure, dietary proteins, dietary supplements, casein, soy, and meat. Forty randomized controlled trials including 3,277 participants in which amount or source of protein was the only difference between the intervention and comparison groups and that examined blood pressure were included. Using a standardized protocol and data extraction form, two investigators independently abstracted data on study design, participant characteristics, intervention, and treatment outcomes. Net effects of protein on blood pressure were pooled across trials and weighted by the inverse of the variance using random-effects models. Compared to carbohydrate, dietary protein was associated with significant decreases in mean systolic and diastolic blood pressure (95% confidence intervals) of -1.75 (-2.31, -1.19) and -1.16 (-1.60, -0.72) mmHg, respectively (all P<0.001). Blood pressure lowering effects of both vegetable and animal sources of protein were observed with significant decreases of -2.22 (-3.18, -1.26) and -2.54 (-3.55, -1.53) mmHg for systolic blood pressure, respectively (all P<0.001), and -1.25 (-2.12, -0.39) and -0.95 (-1.72, -0.19) mmHg for diastolic blood pressure, respectively (P=0.005 and 0.01, respectively). Blood pressure reduction was not significantly different when vegetable protein was compared directly to animal protein. In conclusion, dietary protein intake reduces systolic and diastolic blood pressure in adults. Replacement of carbohydrate intake with protein intake, from either vegetable or animal sources, could be an important strategy for helping to curb the growing pandemic of hypertension and related cardiovascular disease morbidity and mortality. Future research is indicated to assess potential differential effects of protein on blood pressure according to hypertension status.

scholarly journals Dietary Protein Intake and Blood Pressure: A Meta-Analysis of Randomized Controlled Trials

2012 ◽  
Vol 176 (suppl_7) ◽  
pp. S27-S43 ◽  
Author(s):  
Casey M. Rebholz ◽  
Eleanor E. Friedman ◽  
Lindsey J. Powers ◽  
Whitney D. Arroyave ◽  
Jiang He ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Randomized Controlled Trials ◽  
Dietary Protein ◽  
Protein Intake ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Dietary Protein Intake ◽  
Randomized Controlled

The Effect of Partly Missing Covariates on Statistical Power in Randomized Controlled Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani
Keyword(s):  
Randomized Controlled Trials ◽  
Discrete Time ◽  
Treatment Effect ◽  
Survival Data ◽  
Controlled Trials ◽  
Missing Covariates ◽  
Indicator Method ◽  
Imputation Methods ◽  
Randomized Controlled ◽  
Baseline Covariates

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.

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