Data synthesis/analysis

A systematic review of the literature will be performed, combined into forest plots and meta-analyzed.

The overall analysis will combine the data from the use of all bioactive scaffolds and compared with cell-only controls. Data will be further analyzed by subgroup analysis based on three major criteria: type of scaffold, stem cell, and animal model. Therefore, a separate subgroup meta regression will be performed for these criteria.

LVEF: raw mean difference

End systolic volume: standardized mean difference

End diastolic volume: standardized mean difference

Infarct size: standardized mean difference

Left ventricular wall thickness: standardized mean difference

Fractional shortening: raw mean difference

Scaffold type (hydrogels, patches)

Cell type (embryonic, mesenchymal, cardiac progenitor)

Cell characterization through gene/protein expression analysis

Animal characteristics (species, sex, age, weight, comorbidities)

Type of MI model (permanent ligation, ischemia-reperfusion injury)

Duration of MI model

Follow-up

Randomization

Blinding

Immunosuppressive therapy

Pooled analyses will be conducted using the DerSimonian-Laird random effects or Mantel-Haenszel fixed-effect models. In case of statistically significant between-studies heterogeneity, random-effect models will be applied [31–33]. Data will be expressed as mean differences (MD) with 95% CI and considered significant at P < 0.05. Forest plots will be used to display the relative treatment effect and its 95% CI for each trial, scaffold type, cell type, animal model, and for the overall random-effects meta-analyses. Data will be analyzed using Review Manager (RevMan) 5.3 (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark) for primary analyses. Meta-regressions will be performed to assess the significance of subgroup effects with STATA software, v13 (StataCorp, College Station, TX) with a significance level set at P < 0.05. Publication bias will be assessed by visual inspection of funnel plots and formally complemented by Begg’s and Egger’s statistical tests [34], where P < 0.05 was considered evidence of small study effects. Between-studies heterogeneity will be quantified and determined via the Tau² and I² statistics with the significance level set at P < 0.10 [33]. Sources of heterogeneity will be explored by sensitivity analysis via systematic removal of individual trials.