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 x 21 #> study endpoint population age category_age duration category_durati… #> <chr> <chr> <fct> <dbl> <fct> <dbl> <fct> #> 1 Abde… BMI T2D 54.6 > 50 y 8 5 - 10 weeks #> 2 Abde… HbA1c T2D 54.6 > 50 y 8 5 - 10 weeks #> 3 Abde… HDL T2D 54.6 > 50 y 8 5 - 10 weeks #> 4 Abde… HOMA-IR T2D 54.6 > 50 y 8 5 - 10 weeks #> 5 Abde… LDL T2D 54.6 > 50 y 8 5 - 10 weeks #> 6 Abde… Total C… T2D 54.6 > 50 y 8 5 - 10 weeks #> 7 Abde… Triglyc… T2D 54.6 > 50 y 8 5 - 10 weeks #> 8 Bækk… Body Ma… Overweigh… 40 30 - 50 y 6 5 - 10 weeks #> 9 Bækk… Flow-me… Overweigh… 40 30 - 50 y 6 5 - 10 weeks #> 10 Bækk… 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 x 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>, #> # endpoints_body_fat <chr>, endpoints_sbp <chr>, endpoints_dbp <chr>, #> # endpoints_hdl <chr>, endpoints_ldl <chr>, endpoints_triglycerides <chr>, #> # endpoints_total_cholesterol <chr>, endpoints_insulin <chr>, #> # endpoints_glucose <chr>, endpoints_homa <chr>, endpoints_bmi <chr>, #> # endpoints_crp <chr>, endpoints_hba1c <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 x 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>
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}, #> }
