| Literature DB >> 35469165 |
Lin Guo1, Huaien Bu2, Maojuan Guo1, Yue Zhang1, Qun Yu1, Bin Yu3, Xijuan Jiang1, Lin Yang1.
Abstract
Objective: To evaluate the effectiveness and safety of thrombolytic therapy combined with mild hypothermia in patients with acute cerebral infarction (ACI), based on a meta-analysis of randomized controlled trials (RCTs).Entities:
Year: 2022 PMID: 35469165 PMCID: PMC9034919 DOI: 10.1155/2022/4044826
Source DB: PubMed Journal: Evid Based Complement Alternat Med ISSN: 1741-427X Impact factor: 2.650
Figure 1Flow chart of literature retrieval and selection.
Figure 2Details of risk of bias.
Figure 3Risk of bias statistics: percentage of each risk of bias item across all included studies.
Details of the 26 RCTs.
| Study (published year) | Study type | Country | Sex (M/F) | Females (%) | Age (years) (mean ± SD) | Duration (hours) | Initial NIHSS | Follow-up (days) |
|---|---|---|---|---|---|---|---|---|
| Bi (2011) [ | RCT | China | T: 10/21 | T: 32.3 | T: 68.45 ± 6.89 | T: 2.5 ± 1 | T: 11.4 ± 2.8 | 90 |
| C: 13/18 | C: 58.1 | C: 68.55 ± 6.28 | C: 2.5 ± 1 | C: 11.0 ± 2.7 | ||||
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| Patrick (2017) [ | RCT | America | T: 34/29 | T: 46 | T: 65.5 ± 10.3 | T: 2.0 ± 0.5 | T: 14.1 ± 4.8 | 90 |
| C: 35/22 | C: 39 | C: 67.5 ± 11.1 | C: 2.15 ± 0.5 | C: 14.5 ± 4.9 | ||||
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| Katja (2014) [ | RCT | Australia | T: 12/6 | T: 33 | T: 70 | — | T: 11 | 90 |
| C: 8/10 | C: 56 | C: 66 | C: 14 | |||||
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| Ovesen (2013) [ | RCT | Denmark | T: 9/8 | T: 47.1 | T: 62.3 | T: 1.68 | T: 8 | 90 |
| C: 8/6 | C: 42.9 | C: 65.9 | C: 3.74 | C: 9 | ||||
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| De (2004) [ | RCT | America | T: 13/5 | T: 28 | T: 60.9 ± 12.1 | T: 3.0 ± 0.5 | T: 15.2 ± 4.4 | 37 |
| C: 6/16 | C: 71 | C: 67.3 ± 12.5 | C: 4.0 ± 0.25 | C: 14.6 ± 5.6 | ||||
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| Derk (2001) [ | RCT | America | T: 5/5 | T: 50 | T: 71.1 ± 14.3 | T: 3.1 ± 1.4 | 19.86 ± 3.3 | 90 |
| C: 5/4 | C: 44 | C: 68.2 ± 12.3 | C: 4.4 ± 1.7 | |||||
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| Hong (2014) [ | RCT | South Korea | T: 23/16 | T: 41 | T: 64.5 ± 17.0 | <5 | T: 16 | 90 |
| C: 18/18 | C: 64 | C: 68.1 ± 13.3 | C: 17 | |||||
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| Thomas (2010) [ | RCT | California | T: 24 | 45 | 65.5 ± 12.1 | <6 | 14.0 ± 5.0 | 90 |
| C: 24 | ||||||||
| H Bart (2019) [ | RCT | Netherlands | T: 28/21 | T: 37 | T: 69.6 | <6 | T: 11 | 91 |
| C: 27/22 | C: 39 | C: 71.1 | C: 11 | |||||
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| Cui (2020) [ | RCT | China | T: 26/15 | T: 37 | T: 55.16 ± 6.57 | 2.48 ± 0.60 | — | 14 |
| C: 25/16 | C: 39 | C: 55.29 ± 6.65 | ||||||
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| Li (2018) [ | RCT | China | T: 28 | — | 62.6 ± 5.1 | <4.5 | T: 15.75 ± 6.43 | 14 |
| C: 16.15 ± 4.06 | ||||||||
| C: 22 | ||||||||
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| Yang (2020) [ | RCT | China | T: 23/17 | T: 37 | T: 64.5 ± 12.3 | T: 3.5 ± 0.3 | T: 8.1 ± 3.2 | 7 |
| C: 25/15 | C: 39 | C: 62.1 ± 13.9 | C: 3.2 ± 0.2 | C: 8.2 ± 2.7 | ||||
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| Jin (2017) [ | RCT | China | T: 45 | — | — | — | — | 30 |
| C: 45 | ||||||||
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| Wang (2018) [ | RCT | China | T: 28/25 | T: 37 | T: 51.29 ± 9.14 | T: 3.29 ± 0.81 | T: 15.47 ± 3.89 | — |
| C: 29/24 | C: 39 | C: 52.08 ± 8.62 | C: 3.70 ± 0.97 | C: 15.83 ± 6.57 | ||||
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| Li (2014) [ | RCT | China | T: 16/6 | T: 37 | T: 65.48 ± 7.66 | <3 | T: 17.4 ± 3.8 | 30 |
| C: 14/8 | C: 39 | C: 63.24 ± 7.74 | C: 16.6 ± 6.2 | |||||
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| Wang (2018) [ | RCT | China | T: 51/49 | T: 37 | T: 55.2 ± 1.2 | T: 1.50 ± 1.10 | T: 16.23 ± 1.56 | — |
| C: 58/42 | C: 39 | C: 53.7 ± 1.5 | C: 1.30 ± 0.60 | C: 16.23 ± 1.31 | ||||
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| Sun (2018) [ | RCT | China | T: 10/15 | T: 58 | T: 64.25 ± 10.47 | T: 3.14 ± 0.55 | T: 15.89 ± 7.08 | 7 |
| C: 12/13 | C: 52 | C: 62.14 ± 9.35 | C: 3.09 ± 0.71 | C: 15.69 ± 6.39 | ||||
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| Pei (2018) [ | RCT | China | T: 23/17 | T: 37 | T: 61.11 ± 7.31 | T: 3.29 ± 0.81 | T: 16.33 ± 5.67 | 7 |
| C: 23/17 | C: 39 | C: 61.47 ± 7.02 | C: 3.70 ± 0.97 | C: 16.85 ± 5.31 | ||||
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| Hu (2016) [ | RCT | China | T: 31 | — | 60.18 ± 10.18 | 3.56 ± 0.79 | T: 15.22 ± 7.57 | 90 |
| C: 29 | C: 15.74 ± 6.42 | |||||||
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| Cai (2020) [ | RCT | China | T: 60 | — | 61.3 ± 4.1 | 3.65 ± 0.64 | T: 12.03 ± 2.56 | 7 |
| C: 34 | C: 12.01 ± 2.45 | |||||||
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| Zhao (2018) [ | RCT | China | T: 18/15 | T: 37 | T: 60.33 ± 6.29 | — | T: 14.78 ± 3.01 | 45 |
| C: 17/16 | C: 39 | C: 61.24 ± 6.44 | C: 14.23 ± 2.28 | |||||
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| Wei (2020) [ | RCT | China | T: 27/21 | T: 37 | T: 64.5 ± 9.4 | T: 2.80 ± 1.00 | T: 14.2 ± 3.7 | 28 |
| C: 30/19 | C: 39 | C: 63.8 ± 10.2 | C: 2.70 ± 1.20 | C: 13.9 ± 3.0 | ||||
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| Yang (2020) [ | RCT | China | T: 35/33 | T: 37 | T: 62.43 ± 12.06 | <4.5 | — | — |
| C: 36/32 | C: 39 | C: 62.75 ± 11.82 | ||||||
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| Ma (2017) [ | RCT | China | T: 8/7 | T: 37 | T: 66.33 ± 9.81 | T: 4.66 ± 0.54 | — | — |
| C: 7/8 | C: 39 | C: 68.26 ± 9.53 | C: 4.81 ± 0.35 | |||||
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| Zhu (2019) [ | RCT | China | T: 19/14 | T: 37 | T: 64 ± 13 | <4.5 | T: 23.7 ± 2.2 | — |
| C: 17/16 | C: 39 | C: 62 ± 13 | C: 24.3 ± 3.2 | |||||
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| Liu (2019) [ | RCT | China | T: 28/38 | T: 37 | T: 64.26 ± 10.46 | T: 3.08 ± 0.72 | — | — |
| C: 32/34 | C: 39 | C: 62.13 ± 9.36 | C: 3.13 ± 0.56 | |||||
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| Zhang (2021) [ | RCT | China | T: 25/16 | T: 39 | T: 59.6 ± 3.2 | T: 3.47 ± 0.5 | T: 12.01 ± 2.65 | 7 |
| C: 25/13 | C: 34 | C: 60.5 ± 3.3 | C: 3.52 ± 0.48 | C: 12.02 ± 2.47 | ||||
T, treatment group; C, control group; Age and initial NIHSS shown as median values. “—” indicates data not specified RCT randomized controlled trial, NIHSS National Institutes of Health Stroke Scale.
Cooling characteristics of included studies.
| Study (published year) | From ACI (h) | Drugs | Type of TH | Target temperature (C) | Duration of TH (h) | Rewarming done | Rewarming rate (C/h) | Duration of Dewarming (h) | Outcomes |
|---|---|---|---|---|---|---|---|---|---|
| Bi (2011) [ | 6 | rtPA | Systemic surface | — | 24 | Yes | — | — | ② ⑧ |
| Patrick (2017) [ | 3 | rtPA | Systemic surface | 33 | 24 | Yes | 0.5/1 | 12 | ② ⑧ |
| Katja (2014) [ | 6 | rtPA | Systemic surface | 35 | 12 | Yes | 0.2/1 | 7 | ⑧ |
| Ovesen (2013) [ | 12.24 | rtPA | Endovascular cooling | 33 | 24 | Yes | 0.25–0.5/1 | — | ② ⑧ |
| De (2004) [ | 8.6 | rtPA | Endovascular cooling | 33 | 24 | Yes | 0.2/1 | — | ② ⑧ |
| Derk (2001) [ | 6.2 ± 1.3 | rtPA | Systemic surface | 32 | 47.4 ± 20 | Yes | 0.21/1 | 23 | ⑧ |
| Hong (2014) [ | <5.5 | rtPA | Systemic combined | 34.5 | 48 | Yes | 0.5/12 | 48 | ⑧ |
| Thomas (2010) [ | <5 | rtPA | Systemic surface | 33 | 24 | Yes | 0.30/1 | 12 | ⑧ |
| Bart (2019) [ | — | rtPA | Systemic surface | 34–35 | 18 | Yes | 0.2 ± 0.1/1 | — | ⑧ |
| Cui (2020) [ | 2.84 | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.25/1 | 12–20 | ① ⑥ ⑦ ⑧ |
| Li (2018) [ | <4.5 | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.5/1 | 12–20 | ① ② ④ ⑤ ⑥ ⑦ ⑧ |
| Yang (2020) [ | <6 | rtPA | Systemic surface | 33 | — | Yes | 0.3/1 | 12 | ② ④ ⑤ |
| Jin (2017) [ | — | rtPA | Systemic surface | 33–35 | 48–72 | Yes | <0.1 | 24–28 | ① ⑧ |
| Wang (2018) [ | <6 | rtPA | Systemic surface | 34 | 24 | Yes | 0.25/1 | — | ① ② ⑧ |
| Li (2014) [ | 3 | rtPA | Endovascular cooling | 33 | 24 | Yes | 0.3 | 12 | ② ⑧ |
| Wang (2018) [ | <6 | rtPA | Systemic surface | 32–35 | 24 | Yes | 0.25 | — | ② ④ ⑤ |
| Sun (2018) [ | 3.14 | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.2 | 12–24 | ① ② ④ ⑤ |
| Pei (2018) [ | — | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.25 | — | ① ② ④ ⑤ ⑧ |
| Hu (2016) [ | — | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.15–0.25 | 12–20 | ① ② ④ ⑤ ⑧ |
| Cai (2020) [ | 3 | rtPA | Systemic surface | 33–35 | 24 | Yes | 0.5 | 12–20 | ② ④ ⑤ ⑧ |
| Zhao (2018) [ | — | rtPA | Systemic surface | 33–35 | 48–72 | Yes | 0.1 | 24–48 | ① ② ⑧ |
| Wei (2020) [ | — | rtPA | Systemic surface | 33–35 | 48–72 | Yes | 0.1 | 24–48 | ② ③ ⑤ ⑥ ⑧ |
| Yang (2020) [ | — | rtPA | Systemic surface | 33–35 | 24 | — | — | — | ① ③ ④ ⑤ ⑧ |
| Ma (2017) [ | 4.66 | rtPA | Systemic surface | 33–35 | 24 | Yea | 0.15 | 48 | ② |
| Zhu (2019) [ | — | rtPA | Systemic surface | 33–35 | 72 | Yes | 0.1 | 24–48 | ① ② ③ ④ ⑤ ⑥ ⑦ |
| Liu (2019) [ | <5 | rtPA | Systemic surface | 34–35 | 24 | Yes | 0.25 | — | ① ② ④ ⑤ |
| Zhang (2021) [ | 0.5–3 | rtPA | Endovascular cooling | 33–35 | 24 | Yes | 0.5 | 12–20 | ② ④ ⑤ ⑧ |
T, treatment group; C, control group. Outcomes: ① clinical efficacy; ② NIHSS; ③ GSH-Px; ④ SOD; ⑤ MDA; ⑥ IL-1β; ⑦ TNF-α; ⑧ adverse drug reaction. “–” indicates data not specified.
Figure 4Effective rate of clinical efficacy rate between two groups.
Figure 5Compare change of NIHSS between two groups using meta-analysis.
Figure 6Compare change of serum GSH-Px levels between two groups.
Figure 7Compare change of serum SOD levels between two groups.
Figure 8Compare change of serum MDA levels between two groups.
Figure 9Compare change of serum IL-1β levels between two groups.
Figure 10Compare change of serum TNF- α levels between two groups.
Figure 11Adverse drug reaction between two groups.
Figure 12The forest plot of clinical efficiency.