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 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>

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/10.1249/MSS.0000000000002506>.
#> 
#> 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/10.1249/MSS.0000000000002506},
#>     doi = {10.1249/MSS.0000000000002506},
#>   }