Computational protocol: Effects of combined high-intensity aerobic interval training program and Mediterranean diet recommendations after myocardial infarction (INTERFARCT Project): study protocol for a randomized controlled trial

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Protocol publication

[…] The primary outcome variable of this study is VO2peak. A priori power analysis (G*Power 3 statistical software) [] was performed to calculate the average sample size. Due to the lack of any source on the effect of VO2peak in MI patients, we speculate a similar increase based on a study of coronary artery disease []. Therefore, we assume a mean change of 5.0 mL kg−1 min−1 and a common standard deviation (SD) of 4.0 for participants allocated to the HIIT groups and a mean change of 3.0 ± 4.0 mL kg−1 min−1 for participants allocated to the AC group. Based on 1:1:1 randomization to three treatment arms with equal group size, we expect that pre-post intervention differences in our design would be achieved with 177 people (59 each group, α = 0.05, Cohen medium effect size f = 0.23, 80% power). Assuming a maximum loss of follow-up of 10%, the plan will be to recruit a total of 194 individuals. The statistical analysis will be performed using IBM SPSS Statistics, Version 22.0 (IBM Corp., Armonk, NY, USA). In the final analysis, four comparisons will be made: HIIT groups vs AC; HV-HIIT vs LV-HIIT; HV-HIIT vs AC; and LV-HITT vs AC. Two parametric tests will be performed after all assumptions for each test are met. For comparisons between groups at baseline, one-way analysis of variance (ANOVA) or the non-parametric method of Kruskal–Wallis and Chi-square test will be used. A linear regression model with ANOVA will be used to assess training effects on the primary and secondary study outcomes. We will examine the delta (Δ) score for each group (AC, HV-HIIT, LV-HIIT), adjusting for age, sex, changes in body mass, and the initial value of each of the dependent variables. Helmert contrasts will be performed to analyze the difference between the two exercise groups pooled together and the AC group. Bonferroni correction was used to determine the level of significance when a significant main effect was found. The differences between dropouts and participants who remain in the study will be examined; the data will be analyzed according to the intention-to-treat principle []. For each outcome variable, the effect size and the level of significance corresponding to the main group (between-subjects), time (within-subjects), and interaction (group × time) will be reported. To prevent type I error, post hoc comparisons (pre vs post by group) will be performed when a significant interaction effect is present. Values will be expressed as mean ± SD. The significance level will be set at 5% (α = 0.05). Practical significance will be assessed by calculating Cohen’s d effect size. Effect sizes (d) > 0.8, in the range of 0.5–0.8, in the range of 0.2–0.5, and < 0.2 will be considered as large, moderate, small, and trivial, respectively. […]

Pipeline specifications

Software tools G*Power, SPSS
Application Miscellaneous
Organisms Homo sapiens
Diseases Myocardial Infarction