| Literature DB >> 35964075 |
Gustavo Waclawovsky1, Maximiliano I Schaun2, Raphael S N da Silva1, Diego S da Silva1.
Abstract
INTRODUCTION: Aging is an independent risk factor for cardiovascular events. It promotes vascular dysfunction which is associated with risk factors for cardiovascular diseases (CVDs). Exercise can modulate vascular function parameters, but little is known about the effects of different modalities of training (aerobic, resistance, and combined) on endothelial function and arterial stiffness in older adults.Entities:
Keywords: Aging; Endothelium; Exercise; Pulse wave analysis; Reactive hyperemia; Vascular stiffness
Mesh:
Year: 2022 PMID: 35964075 PMCID: PMC9375352 DOI: 10.1186/s13643-022-02036-w
Source DB: PubMed Journal: Syst Rev ISSN: 2046-4053
Fig. 1Flowchart of the study design
Search strategy
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Interpretation of heterogeneity results
| Interpretation of | |
|---|---|
| 0 to 40%: might not be important | |
| 30 to 60%: may represent moderate heterogeneitya | |
| 50 to 90%: may represent substantial heterogeneitya | |
| 75 to 100%: considerable heterogeneitya |
aThe importance of the value of I2 depends on the magnitude and direction of effects and the strength of evidence for heterogeneity (I confidence interval: uncertainty of the value of I2 is substantial when there is a small number of studies)
Script used for the meta-analysis of data from systematic review
• library (readxl) • FMD_RV <- read_excel ("C:/Metanalysis_Raphael/database_analysis/FMD_RV.xlsx") • View (FMD_RV) • Meta_1 = FMD_RV <- metacont (t_n, t_mean, t_dp, c_n, c_mean, c_dp, Study, predict = TRUE, data = FMD_RV, sm = "MD") • Meta_1 • forest (Meta_1, sortvar = Study, xlim = c (-10.0, 10.0), predict = TRUE, col.square = "grey", col.diamond = "black", digits = 2) • forest (Meta_1, comb.fixed = FALSE, sortvar = Study, xlim = c (-10.0, 10.0), digits.sd = 2, digits.I2= 2, print.I2.ci = TRUE , digits.tau2 = 2, digits.pval.Q = 3, squaresize = 0.5, lab.e = "Experimental", lab.c = "Control", col.inside = "black", col.square = "grey", col.diamond = "black", col.predict = "transparent", digits = 2) • baujat (Meta_1, ylim = c (-1.0, 1.0), xlim = c (-200, 200)) • metainf (Meta_1, pooled = "random") • metabias (Meta_1, method.bias = "linreg") • funnel (meta_Rapha1) |