Description
Datasets and Functions for Reproducing Meta-Analyses.
Description
Dataset and functions from the meta-analysis published in Medicine & Science in Sports & Exercise. It contains all the data and functions to reproduce the analysis. "Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis". Felipe Mattioni Maturana, Peter Martus, Stephan Zipfel, Andreas M Nieß (2020) <doi:10.1249/MSS.0000000000002506>.
README.md
metabolic 
The goal of metabolic is to provide all the data and the tools necessary to reproduce the meta-analysis published in Medicine & Science in Sports & Exercise.
Installation
You can install the released version of metabolic from CRAN with:
install.packages("metabolic")
You can install the development version of metabolic from from GitHub with:
# install.packages("remotes")
remotes::install_github("fmmattioni/metabolic")
Datasets
Dataset to reproduce meta-analyses
metabolic::metabolic_meta
#> # A tibble: 391 × 21
#> study endpoint population age category_age duration category_durati…
#> <chr> <chr> <fct> <dbl> <fct> <dbl> <fct>
#> 1 Abdelbasset… BMI T2D 54.6 > 50 y 8 5 - 10 weeks
#> 2 Abdelbasset… HbA1c T2D 54.6 > 50 y 8 5 - 10 weeks
#> 3 Abdelbasset… HDL T2D 54.6 > 50 y 8 5 - 10 weeks
#> 4 Abdelbasset… HOMA-IR T2D 54.6 > 50 y 8 5 - 10 weeks
#> 5 Abdelbasset… LDL T2D 54.6 > 50 y 8 5 - 10 weeks
#> 6 Abdelbasset… Total C… T2D 54.6 > 50 y 8 5 - 10 weeks
#> 7 Abdelbasset… Triglyc… T2D 54.6 > 50 y 8 5 - 10 weeks
#> 8 Bækkerud 20… Body Ma… Overweigh… 40 30 - 50 y 6 5 - 10 weeks
#> 9 Bækkerud 20… Flow-me… Overweigh… 40 30 - 50 y 6 5 - 10 weeks
#> 10 Bækkerud 20… VO2max Overweigh… 40 30 - 50 y 6 5 - 10 weeks
#> # … with 381 more rows, and 14 more variables: men_ratio <dbl>,
#> # category_men_ratio <fct>, type_exercise <chr>, bsln <dbl>,
#> # bsln_adjusted <dbl>, category_bsln <fct>, N_HIIE <dbl>, Mean_HIIE <dbl>,
#> # SD_HIIE <dbl>, N_MICT <dbl>, Mean_MICT <dbl>, SD_MICT <dbl>, HIIE <chr>,
#> # desired_effect <chr>
Dataset to build the GOfER diagram
metabolic::metabolic_gofer
#> # A tibble: 115 × 33
#> study groups sample_populati… sample_fitness sample_men_ratio anamnese_smoker
#> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 Abde… HIIT "T2D" N/R 0.63 N
#> 2 Abde… MICT "T2D" N/R 0.53 N
#> 3 Bækk… HIIT "Overweight\nOb… Sedentary 0.41 N/R
#> 4 Bækk… MICT "Overweight\nOb… Sedentary 0.41 N/R
#> 5 Beet… HIIT "Overweight\nOb… Active 0.66 N/R
#> 6 Beet… MICT "Overweight\nOb… Active 0.8 N/R
#> 7 Burg… SIT "Healthy" Sedentary 0.5 N/R
#> 8 Burg… MICT "Healthy" Sedentary 0.5 N/R
#> 9 Ciol… HIIT "Healthy" Sedentary 0 N
#> 10 Ciol… MICT "Healthy" Sedentary 0 N
#> # … with 105 more rows, and 27 more variables:
#> # anamnese_medicines_to_control_BP <chr>, age <dbl>,
#> # design_type_of_exercise <chr>, design_sample_size <chr>,
#> # design_training_duration <dbl>, design_training_frequency <chr>,
#> # design_exercise_intensity <chr>, hiie_n_reps <chr>,
#> # hiie_rep_duration <chr>, hiie_work_rest_ratio <chr>, compliance <dbl>,
#> # endpoints_vo2max <chr>, endpoints_fmd <chr>, endpoints_body_mass <chr>, …
Reproduce meta-analysis for each clinical endpoint
library(metabolic)
perform_meta(endpoint = "VO2max")
#> ────────────────────────── * VO2max meta-analysis * ──────────────────────────
#> ✔ 'Overall'
#> ✔ └─ Performing meta-analysis
#> ✔ └─ Performing sensitivity analysis
#> ✔ └─ Meta-analysis results are robust! Keep going!
#> ✔ Performing meta-analysis and meta-regression on the Population subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Age subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Training Duration subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Men Ratio subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Type of Exercise subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Baseline subgroup
#>
#> ✔ Performing meta-analysis and meta-regression on the Type of HIIE subgroup
#>
#> ────────────────────────────────── * DONE * ──────────────────────────────────
#> # A tibble: 8 × 4
#> subgroup meta_analysis sensitivity_analysis meta_regression
#> <chr> <named list> <named list> <named list>
#> 1 Overall <metacont> <metainf> <lgl [1]>
#> 2 Population <metacont> <lgl [1]> <metareg>
#> 3 Age <metacont> <lgl [1]> <metareg>
#> 4 Training Duration <metacont> <lgl [1]> <metareg>
#> 5 Men Ratio <metacont> <lgl [1]> <metareg>
#> 6 Type of Exercise <metacont> <lgl [1]> <metareg>
#> 7 Baseline Values <metacont> <lgl [1]> <metareg>
#> 8 Type of HIIE <metacont> <lgl [1]> <metareg>
Build a GOfER (Graphical Overview for Evidence Reviews) diagram
Citation
citation("metabolic")
#>
#> To cite metabolic in publications use:
#>
#> Maturana M, Felipe, Martus, Peter, Zipfel, Stephan, Nieß, M A (2020).
#> "Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk
#> Factors in Health and Disease: a meta-anaylsis." _Medicine & Science in
#> Sports & Exercise_, *Published Ahead of Print*. doi:
#> 10.1249/MSS.0000000000002506 (URL:
#> https://doi.org/10.1249/MSS.0000000000002506), <URL:
#> https://journals.lww.com/acsm-msse/Abstract/9000/Effectiveness_of_HIIE_versus_MICT_in_Improving.96194.aspx>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: a meta-anaylsis},
#> author = {Mattioni Maturana and {Felipe} and {Martus} and {Peter} and {Zipfel} and {Stephan} and {Nieß} and Andreas M},
#> journal = {Medicine & Science in Sports & Exercise},
#> volume = {Published Ahead of Print},
#> year = {2020},
#> url = {https://journals.lww.com/acsm-msse/Abstract/9000/Effectiveness_of_HIIE_versus_MICT_in_Improving.96194.aspx},
#> doi = {10.1249/MSS.0000000000002506},
#> }