| Literature DB >> 35578329 |
Alireza Hosseinpour1, Fatemeh Kheshti2, Asma Kazemi3, Armin Attar4.
Abstract
BACKGROUND: The effect of transplantation of bone-marrow mononuclear cells (BM-MNCs) and mesenchymal stem cells (MSCs) on ejection fraction (LVEF) has been studied in patients with acute myocardial infarction (AMI) in clinical trials. This raises the question that which type of cell may help improve LVEF better in AMI patients. No meta-analysis of clinical trials has yet addressed this question.Entities:
Keywords: Acute myocardial infarction; Bone-marrow mononuclear cells; Mesenchymal stem cells; Stem cells
Mesh:
Year: 2022 PMID: 35578329 PMCID: PMC9109324 DOI: 10.1186/s13287-022-02883-3
Source DB: PubMed Journal: Stem Cell Res Ther ISSN: 1757-6512 Impact factor: 8.079
Fig. 1PRISMA flow diagram of the study search and inclusion process
Characteristics of the included trials
| Study | Country | Type of cell | Sample size | Mean age | Male% | Baseline LVEF (%) | Injection time (days) | Modality | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Inv | Cont | Inv | Cont | Inv | Cont | Inv | Cont | |||||
| Assmus [ | Germany | BM-MNCs | 101 | 103 | 55 ± 11 | 57 ± 11 | 82 | 82 | 47.5 ± 10 | 46.7 ± 10.3 | 4.4 ± 1.3 | LV angiography |
| Beitnes [ | Norway | BM-MNCs | 50 | 50 | 58.1 ± 8.5 | 56.7 ± 9.6 | 84 | 84 | 45.7 ± 9.4 | 46.9 ± 9.6 | 4–8 | Echo/CMR |
| Cao [ | China | BM-MNCs | 41 | 45 | 50.7 ± 1.1 | 51.0 ± 1.0 | 95 | 93 | 39 ± 3 | 38.6 ± 3 | 7 | Echo/SPECT |
| Ge [ | China | BM-MNCs | 10 | 10 | 58 ± 11 | 59 ± 8 | 80 | 100 | 53.8 ± 9.2 | 58.2 ± 7.5 | 0–1 | Echo/SPECT |
| Grajek [ | Poland | BM-MNCs | 31 | 14 | 49.9 ± 8.4 | 50.9 ± 9.3 | 87 | 86 | 50.32 ± 9.8 | 50.84 ± 11.97 | 4–5 | Echo/SPECT |
| Hirsch [ | Netherlands | BM-MNCs | 69 | 65 | 56 ± 9 | 55 ± 10 | 84 | 86 | 43.7 ± 9 | 42.4 ± 8.3 | 8 | CMR |
| Hu [ | China | BM-MNCs | 22 | 14 | 60.45 ± 11.4 | 60.62 ± 10.85 | 86 | 64 | 53.8 ± 11.5 | 57.1 ± 11.6 | 5 | Echo/SPECT |
| Huang [ | China | BM-MNCs | 79 | 25 | 58.55 ± 8.72 | 58.8 ± 8.4 | 91 | 88 | 43.65 ± 5.21 | 43.5 ± 3.5 | 1–30 | Echo/SPECT |
| Huikuri [ | Finland | BM-MNCs | 40 | 40 | 60 ± 10 | 59 ± 10 | 90 | 85 | 59 ± 11 | 62 ± 12 | 2–6 | Echo/LV angiography |
| Janssens [ | Belgium | BM-MNCs | 33 | 34 | 55.8 ± 11 | 57.9 ± 10 | 82 | 82 | 48.5 ± 7.2 | 46.9 ± 8.2 | 1 | Echo/CMR |
| Meluzin [ | Czech | BM-MNCs | 40 | 20 | 54 ± 2 | 55 ± 2 | 92 | 90 | 40.5 ± 8.94 | 40 ± 8.94 | 3–8 | Echo/SPECT |
| Meyer [ | Germany | BM-MNCs | 30 | 30 | 53.4 ± 14.8 | 59.2 ± 13.5 | 67 | 73 | 50 ± 10 | 51.3 ± 9.3 | 4.8 ± 1.3 | CMR |
| Nicolau [ | Brazil | BM-MNCs | 66 | 55 | 59.23 ± 9.44 | 58.72 ± 9.3 | 80 | 82 | 44.63 ± 10.74 | 42.23 ± 10.33 | 6–9 | CMR |
| Nogueira [ | Brazil | BM-MNCs | 24 | 6 | 57.2 ± 10.9 | 57.2 ± 10.8 | 71 | 67 | 48.41 ± 8.28 | 47.59 ± 14.31 | 4–7.5 | Echo |
| Piepoli [ | Italy | BM-MNCs | 19 | 19 | 63.1 ± 2.4 | 67 ± 2.7 | 68.4 | 68.4 | 38.9 ± 1.3 | 38.4 ± 1.5 | 4–7 | Echo/SPECT |
| Plewka [ | Poland | BM-MNCs | 40 | 20 | 56 ± 9 | 56 ± 9 | 67 | 75 | 35 ± 6 | 33 ± 7 | 7 | Echo/SPECT |
| San Roman [ | Spain | BM-MNCs | 30 | 31 | 54 ± 11 | 57 ± 11 | 97 | 90 | 49 ± 8 | 47 ± 8 | 3–5 | CMR/LV angiography |
| Skalicka [ | Czech | BM-MNCs | 17 | 10 | 61 ± 14 | 54 ± 10 | 71 | 100 | 39.2 ± 9.2 | 39.4 ± 5.6 | 4–11 | Echo/SPECT |
| Sürder [ | Switzerland | BM-MNCs | 128 | 67 | 58.44 ± 10.92 | 56 ± 10.74 | 84 | 84 | 36.4 ± 8.92 | 40 ± 9.9 | 5–28 | CMR |
| Traverse [ | USA | BM-MNCs | 58 | 29 | 57.6 ± 11 | 54.6 ± 11 | 79 | 90 | 48.7 ± 12 | 45.3 ± 9.9 | 14–21 | CMR |
| Traverse [ | USA | BM-MNCs | 30 | 10 | 52.5 ± 15.56 | 57.5 ± 3.7 | 83 | 60 | 49 ± 9.5 | 48.6 ± 8.5 | 3–10 | CMR/Echo |
| Traverse [ | USA | BM-MNCs | 58 | 27 | 55.9 ± 11 | 56.4 ± 10.4 | 88 | 86 | 45.9 ± 9.4 | 46.9 ± 8.7 | 3–7 | CMR |
| Turan [ | Germany | BM-MNCs | 42 | 20 | 61 ± 15 | 60 ± 11 | 67 | 70 | 43 ± 10 | 45 ± 10 | 7 | Left Ventriculography |
| Wöhrle [ | Germany | BM-MNCs | 29 | 13 | 61 ± 8.1 | 61.1 ± 9.3 | 90 | 62 | 53.5 ± 9.3 | 55.7 ± 9.4 | 5–7 | CMR |
| Wollert [ | Germany | BM-MNCs | 127 | 26 | 55.46 ± 9.83 | 55 ± 9 | 85 | 92 | 44.3 ± 8.48 | 47.8 ± 6.7 | 7.1 ± 2.6 | CMR |
| Yao [ | China | BM-MNCs | 27 | 12 | 51.7 ± 6.4 | 52.7 ± 7.8 | 81 | 92 | 33.2 ± 3.9 | 32.3 ± 2 | 3d–3 m | CMR |
| Chullikana [ | India | MSCs | 10 | 10 | 47.31 ± 12.1 | 47.79 ± 6.48 | 100 | 80 | 43 ± 3.63 | 43.44 ± 4.4 | 2 | Echo |
| Gao [ | China | MSCs | 21 | 22 | 55.0 ± 1.6 | 58.6 ± 2.5 | 100 | 86 | 50.2 ± 6.87 | 51.2 ± 7 | 17.1 ± 0.6 | Echo |
| Gao [ | China | MSCs | 58 | 58 | 57.3 ± 1.3 | 56.7 ± 1.7 | 95 | 88 | 52 ± 0.9 | 51.1 ± 1 | 5–7 | Echo |
| Hare [ | USA | MSCs | 34 | 19 | 59 ± 12.3 | 55.1 ± 10.2 | 79 | 82 | 48.7 ± 9.6 | 50.4 ± 10.6 | – | Echo |
| Houtgraaf [ | Netherlands | MSCs | 9 | 4 | 61 ± 2.1 | 55 ± 7.5 | 78 | 100 | 52.1 ± 2.5 | 52 ± 10 | 1 | SPECT |
| Kim [ | South Korea | MSCs | 14 | 12 | 55.3 ± 8.6 | 57.8 ± 8.9 | 100 | 100 | 35.1 ± 4.5 | 37.4 ± 1.7 | 30 ± 1.3 | Echo/SPECT |
| Lee [ | South Korea | MSCs | 30 | 28 | 53.9 ± 10.5 | 54.2 ± 7.7 | 90 | 89 | 48.1 ± 8 | 51 ± 9.2 | 25 ± 2.4 | Echo/SPECT |
| Penn [ | USA | MSCs | 19 | 6 | 56.8 ± 8.7 | 53 ± 8 | 63 | 83 | 47.9 ± 10.2 | 42.3 ± 6.4 | 3.3 | Echo |
| Rodrigo [ | Netherlands | MSCs | 9 | 45 | 56 ± 8 | 61 ± 11 | 78 | 78 | 48 ± 2 | 45 ± 9 | 21 ± 3 | Echo |
| Zhang ( | China | MSCs | 21 | 22 | 59.3 ± 9 | 58.6 ± 11 | 95 | 86 | 57.2 ± 10.2 | 53.7 ± 6.4 | 14 ± 9.5 | Echo |
Assessment of credibility of subgroup difference based on ICEMAN
| Variable | Q1 | Q2 | Q3 | Q4 | Q5 | Q6 | Q7 | Q8 | Overall interpretation | |
|---|---|---|---|---|---|---|---|---|---|---|
| LVEF | Completely between | NA | Large | Definitely yes | Chance a very likely explanation (0.1) | Definitely yes | Definitely yes | NA | Maximum usually moderate | Likely effect modification. Use separate effects for each subgroup but note remaining uncertainty |
| LVEF (sensitivity analysis) | Completely between | NA | Rather small or unclear | Definitely yes | Chance a very likely explanation (0.06) | Definitely yes | Definitely yes | NA | Maximum usually low | Likely no effect modification. Use overall effect for each subgroup but note remaining uncertainty |
| LVESV | Completely between | NA | Rather large | Definitely no | Chance a very likely explanation (0.92) | Definitely yes | Definitely yes | NA | Maximum usually low | Likely no effect modification. Use overall effect for each subgroup but note remaining uncertainty |
| LVESV (sensitivity analysis) | Completely between | NA | Very small | Definitely yes | Chance a very likely explanation (0.15) | Definitely yes | Definitely yes | NA | Maximum usually low | Likely no effect modification. Use overall effect for each subgroup but note remaining uncertainty |
| LVEDV | Completely between | NA | Rather large | Definitely no | Chance a very likely explanation (0.84) | Definitely yes | Definitely yes | NA | Maximum usually low | Likely no effect modification. Use overall effect for each subgroup but note remaining uncertainty |
| LVEDV (sensitivity analysis) | Completely between | NA | Very small | Definitely yes | Chance may not explain (0.007) | Definitely yes | Definitely yes | NA | Maximum usually moderate | Likely effect modification. Use separate effects for each subgroup but note remaining uncertainty |
| Hospitalization | Completely between | NA | Rather large | Definitely no | Chance a very likely explanation (0.26) | Definitely yes | Definitely yes | NA | Maximum usually low | Likely no effect modification. Use overall effect for each subgroup but note remaining uncertainty |
Q1, Is the analysis of effect modification based on comparison within rather than between trials? Q2, for within-trial comparisons, is the effect modification similar from trial to trial? Q3, for between-trial comparisons, is the number of trials large? Q4, Was the direction of the effect modification correctly hypothesized priori? Q5, does a test for interaction suggest that chance is an unlikely explanation of the apparent effect modification? Q6, Did the authors test only a small number of effect modifiers? Q7, Did the authors use a random effects model? Q8, If the effect modifier is a continuous variable, were arbitrary cut points avoided?
Fig. 2Forest plot of the effect sizes of changes in LVEF from baseline during the short-term follow-up (4–6 months) in acute MI patients who received injection of either BM-MNCs or MSCs compared to the control group who received standard therapy with or without placebo injection
Fig. 3Forest plot of LVEDV changes in acute MI patients who received either standard therapy (with or without placebo injection) or autologous injection of stem cells based on the type of cell (BM-MNCs or MSCs)
Fig. 4Forest plot of comparison of changes in LVESV over the follow-up period in patients with acute MI who received stem cell therapy based on the type of cells (BM-MNCs or MSCs) compared to the control group
Fig. 5Forest plot of comparison of the rate of hospitalization due to heart failure in acute MI patients who received stem cell therapy (BM-MNCs or MSCs) compared to the control group who received standard therapy with or without placebo injection