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Supplementary material
ContentsForest plots and funnel plots.................................................................................3
Robot assisted.....................................................................................................3Mehrholz 2015...............................................................................................3Norouzi-Gheidari 2012...................................................................................5Veerbeek 2017...............................................................................................7
Slings.................................................................................................................14Chen 2016 (SMD)........................................................................................14Chen 2016 (MD as presented in original paper)...........................................15
Nintendo Wii.......................................................................................................17Cheok 2015..................................................................................................17
tDCS..................................................................................................................18Elsner 2016..................................................................................................18Triccas 2015.................................................................................................19Triccas 2015.................................................................................................20Triccas 2015.................................................................................................21Bachet 2017.................................................................................................22
Moxibustion........................................................................................................23Han 2018 (MD as presented in original paper).............................................23Han 2018 (SMD)..........................................................................................24
Acupuncture.......................................................................................................25Lee 2013......................................................................................................25Li 2014 (MD as presented in original paper)................................................29Li 2014 (SMD)..............................................................................................30Yang 2016 (MD as presented in original paper)...........................................31Yang 2016 (SMD).........................................................................................32Peng 2017....................................................................................................33
Constraint Induced Movement...........................................................................35Corbetta 2010...............................................................................................35Peurala 2012 (MD as presented in original paper).......................................36Peurala 2012(SMD)......................................................................................37Peurala 2012 (MD as presented in original paper).......................................39Peurala 2012(SMD)......................................................................................40Peurala 2012................................................................................................42Shi 2011.......................................................................................................44Shi 2011 (MD as original paper)...................................................................45Shi 2011 (SMD)............................................................................................46
Virtual Reality.....................................................................................................48Laver 2012...................................................................................................48Laver 2015...................................................................................................49
FES....................................................................................................................51
Rehabilitation in sub-acute stroke for ADLs
Eraifej 2017..................................................................................................51Repetitive task training.......................................................................................52
French 2010.................................................................................................52French 2016.................................................................................................53
Bilateral training.................................................................................................54Lee 2017......................................................................................................54
Augmented exercise therapy.............................................................................55Veerbeek 2011.............................................................................................55
Motor imagery....................................................................................................56Fernandes 2017...........................................................................................56
Electroacupunture..............................................................................................57Yiyi 2017 (MD as in original paper)..............................................................57Yiyi 2017 (SMD)...........................................................................................58
Tai chi................................................................................................................59Lyu 2018......................................................................................................59
Water based training..........................................................................................63Mehrholz 2011 (MD as in original paper).....................................................63Mehrholz 2011 (SMD)..................................................................................63
Mirror therapy.....................................................................................................64Thieme 2018................................................................................................64
rTMS..................................................................................................................65Hao 2013 (MD as in original paper).............................................................65Hao 2013 (SMD)..........................................................................................65
Circuit class therapy...........................................................................................66English 2017 (MD as in original paper)........................................................66English 2017 (SMD).....................................................................................66
rPMS..................................................................................................................67Momosaki 2017 (MD as original paper)........................................................67Momosaki 2017 (SMD).................................................................................67
Meta regressions...................................................................................................69Thieme 2018................................................................................................69Li 2014.........................................................................................................70French 2016.................................................................................................72Elsner 2016..................................................................................................74Han 2018......................................................................................................76Yang 2016....................................................................................................78
Sensitivity analysis................................................................................................80Han 2018......................................................................................................80Li 2014.........................................................................................................81Yang 2016....................................................................................................82
Subgroup Analysis................................................................................................83Thieme 2018................................................................................................83Yang 2016....................................................................................................84Han 2018......................................................................................................85Li 2014.........................................................................................................86
2
Rehabilitation in sub-acute stroke for ADLs
Forest plots and funnel plots
Robot assisted
Mehrholz 2015Distal training (finger, hand and radio-ulnar joints)
3
Rehabilitation in sub-acute stroke for ADLs
Proximal training (shoulder and elbow joints)
4
Rehabilitation in sub-acute stroke for ADLs
Norouzi-Gheidari 2012 Additional RT
5
Rehabilitation in sub-acute stroke for ADLs
Same duration/intensity therapy
6
Rehabilitation in sub-acute stroke for ADLs
Veerbeek 2017 all RT-UL vs any type of control
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Rehabilitation in sub-acute stroke for ADLs
8
Rehabilitation in sub-acute stroke for ADLs
shoulder/elbow RT-UL versus any type of control for outcome of basic ADL post intervention
9
Rehabilitation in sub-acute stroke for ADLs
End-effector RT-UL versus any type of control for outcome of basic ADL post intervention
10
Rehabilitation in sub-acute stroke for ADLs
RT-UL <3 months poststroke versus any type of control for outcome of basic ADL post intervention
11
Rehabilitation in sub-acute stroke for ADLs
dose-matched RT-UL trials versus any type of control for outcome of basic ADL post intervention
12
Rehabilitation in sub-acute stroke for ADLs
Non dose-matched RT-UL trials versus any type of control for outcome of basic ADL post intervention
13
Rehabilitation in sub-acute stroke for ADLs
Slings
Chen 2016 (SMD)
14
Rehabilitation in sub-acute stroke for ADLs
Chen 2016 (MD as presented in original paper)
(this is the original paper)
(Favours control and Favours experimental labels changed)
(this is the original paper)
15
Rehabilitation in sub-acute stroke for ADLs
(Favours control and Favours experimental labels changed)
16
Rehabilitation in sub-acute stroke for ADLs
Nintendo Wii
Cheok 2015
17
Rehabilitation in sub-acute stroke for ADLs
tDCS
Elsner 2016
18
Rehabilitation in sub-acute stroke for ADLs
Triccas 2015 real tDCS versus sham tDCS
19
Rehabilitation in sub-acute stroke for ADLs
Triccas 2015 anodal tDCS versus sham tDCS
20
Rehabilitation in sub-acute stroke for ADLs
Triccas 2015 cathodal tDCS versus sham tDCS
21
Rehabilitation in sub-acute stroke for ADLs
Bachet 2017
22
Rehabilitation in sub-acute stroke for ADLs
Moxibustion
Han 2018 (MD as presented in original paper)
23
Rehabilitation in sub-acute stroke for ADLs
Han 2018 (SMD)
24
Rehabilitation in sub-acute stroke for ADLs
Acupuncture
Lee 2013 SA vs Rehab
25
Rehabilitation in sub-acute stroke for ADLs
SA + medication vs medication
26
Rehabilitation in sub-acute stroke for ADLs
SA + rehabilitation vs rehabilitation (MD as presented in original paper)
27
Rehabilitation in sub-acute stroke for ADLs
SA + rehabilitation vs rehabilitation (SMD)
28
Rehabilitation in sub-acute stroke for ADLs
Li 2014 (MD as presented in original paper)
29
Rehabilitation in sub-acute stroke for ADLs
Li 2014 (SMD)
30
Rehabilitation in sub-acute stroke for ADLs
Yang 2016 (MD as presented in original paper)
31
Rehabilitation in sub-acute stroke for ADLs
Yang 2016 (SMD)
32
Rehabilitation in sub-acute stroke for ADLs
Peng 2017
33
Rehabilitation in sub-acute stroke for ADLs
34
Rehabilitation in sub-acute stroke for ADLs
Constraint Induced Movement
Corbetta 2010
35
Rehabilitation in sub-acute stroke for ADLs
Peurala 2012 (MD as presented in original paper) Motor Activity Log (MAL) – amount of use
36
Rehabilitation in sub-acute stroke for ADLs
Peurala 2012(SMD)
Motor Activity Log (MAL) – amount of use
37
Rehabilitation in sub-acute stroke for ADLs
38
Rehabilitation in sub-acute stroke for ADLs
Peurala 2012 (MD as presented in original paper) Motor Activity Log (MAL) – quality of use
39
Rehabilitation in sub-acute stroke for ADLs
Peurala 2012(SMD)
Motor Activity Log (MAL) – quality of use
40
Rehabilitation in sub-acute stroke for ADLs
41
Rehabilitation in sub-acute stroke for ADLs
Peurala 2012 FIM
42
Rehabilitation in sub-acute stroke for ADLs
43
Rehabilitation in sub-acute stroke for ADLs
Shi 2011 FIM
44
Rehabilitation in sub-acute stroke for ADLs
Shi 2011 (MD as original paper) MAL
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Rehabilitation in sub-acute stroke for ADLs
Shi 2011 (SMD) MAL
46
Rehabilitation in sub-acute stroke for ADLs
47
Rehabilitation in sub-acute stroke for ADLs
Virtual Reality
Laver 2012
48
Rehabilitation in sub-acute stroke for ADLs
Laver 2015
49
Rehabilitation in sub-acute stroke for ADLs
Additional virtual reality intervention
50
Rehabilitation in sub-acute stroke for ADLs
FES
Eraifej 2017
51
Rehabilitation in sub-acute stroke for ADLs
Repetitive task training
French 2010
52
Rehabilitation in sub-acute stroke for ADLs
French 2016
53
Rehabilitation in sub-acute stroke for ADLs
Bilateral training
Lee 2017
54
Rehabilitation in sub-acute stroke for ADLs
Augmented exercise therapy
Veerbeek 2011
55
Rehabilitation in sub-acute stroke for ADLs
Motor imagery
Fernandes 2017
56
Rehabilitation in sub-acute stroke for ADLs
Electroacupunture
Yiyi 2017 (MD as in original paper)
57
Rehabilitation in sub-acute stroke for ADLs
Yiyi 2017 (SMD)
58
Rehabilitation in sub-acute stroke for ADLs
Tai chi
Lyu 2018 (MD as in original paper) studies comparing TC plus conventional rehabilitation therapy with conventional rehabilitation therapy alone
59
Rehabilitation in sub-acute stroke for ADLs
Lyu 2018
(SMD) studies comparing TC plus conventional rehabilitation therapy with conventional rehabilitation therapy alone
60
Rehabilitation in sub-acute stroke for ADLs
Lyu 2018
(MD as in original paper) studies comparing TC with conventional rehabilitation therapy
61
Rehabilitation in sub-acute stroke for ADLs
Lyu 2018
(SMD) studies comparing TC with conventional rehabilitation therapy
62
Rehabilitation in sub-acute stroke for ADLs
Water based training
Mehrholz 2011 (MD as in original paper)
Mehrholz 2011 (SMD)
63
Rehabilitation in sub-acute stroke for ADLs
Mirror therapy
Thieme 2018
64
Rehabilitation in sub-acute stroke for ADLs
rTMS
Hao 2013 (MD as in original paper)
Hao 2013 (SMD)
65
Rehabilitation in sub-acute stroke for ADLs
Circuit class therapy
English 2017 (MD as in original paper)
English 2017 (SMD)
66
Rehabilitation in sub-acute stroke for ADLs
rPMS
Momosaki 2017 (MD as original paper)
Momosaki 2017 (SMD)
67
Rehabilitation in sub-acute stroke for ADLs
68
Rehabilitation in sub-acute stroke for ADLs
Meta regressions
Thieme 2018 Covariate: total participants in experimental group
Mixed-Effects Model (k = 19; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0465)tau (square root of estimated tau^2 value): 0I^2 (residual heterogeneity / unaccounted variability): 0.00%H^2 (unaccounted variability / sampling variability): 1.00R^2 (amount of heterogeneity accounted for): 100.00%
Test for Residual Heterogeneity: QE(df = 17) = 15.5359, p-val = 0.5569
Test of Moderators (coefficient(s) 2): QM(df = 1) = 5.6772, p-val = 0.0172
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt 0.9324 0.2133 4.3718 <.0001 0.5144 1.3504 ***total.e -0.0228 0.0096 -2.3827 0.0172 -0.0415 -0.0040 *
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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Rehabilitation in sub-acute stroke for ADLs
Covariate: year of publication
Mixed-Effects Model (k = 19; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.0332 (SE = 0.0577)tau (square root of estimated tau^2 value): 0.1821I^2 (residual heterogeneity / unaccounted variability): 19.77%H^2 (unaccounted variability / sampling variability): 1.25R^2 (amount of heterogeneity accounted for): 0.00%
Test for Residual Heterogeneity: QE(df = 17) = 21.1894, p-val = 0.2179
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.0212, p-val = 0.8843
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt -9.3195 67.3059 -0.1385 0.8899 -141.2366 122.5976 year 0.0049 0.0334 0.1456 0.8843 -0.0607 0.0704
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Li 2014 Covariate: total participants in experimental group
Mixed-Effects Model (k = 12; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 1.5597 (SE = 0.7976)tau (square root of estimated tau^2 value): 1.2489I^2 (residual heterogeneity / unaccounted variability): 95.84%H^2 (unaccounted variability / sampling variability): 24.06
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Rehabilitation in sub-acute stroke for ADLs
R^2 (amount of heterogeneity accounted for): 0.00%
Test for Residual Heterogeneity: QE(df = 10) = 240.6116, p-val < .0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.1780, p-val = 0.6731
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt 1.7166 0.6968 2.4635 0.0138 0.3509 3.0824 *total.e -0.0050 0.0120 -0.4219 0.6731 -0.0285 0.0184
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Covariate: year of publication
Mixed-Effects Model (k = 12; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 1.2539 (SE = 0.6903)tau (square root of estimated tau^2 value): 1.1198I^2 (residual heterogeneity / unaccounted variability): 95.66%H^2 (unaccounted variability / sampling variability): 23.05R^2 (amount of heterogeneity accounted for): 0.00%
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Rehabilitation in sub-acute stroke for ADLs
Test for Residual Heterogeneity: QE(df = 10) = 230.4639, p-val < .0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.1227, p-val = 0.7262
Model Results:
estimate se zval pval ci.lbintrcpt 66.9130 187.0938 0.3576 0.7206 -299.7841year -0.0326 0.0932 -0.3502 0.7262 -0.2152 ci.ub intrcpt 433.6100 year 0.1500
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
French 2016 Covariate: total participants in experimental group
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0 (SE = 0.0393)tau (square root of estimated tau^2 value): 0I^2 (residual heterogeneity / unaccounted variability): 0.00%H^2 (unaccounted variability / sampling variability): 1.00R^2 (amount of heterogeneity accounted for): NA%
72
Rehabilitation in sub-acute stroke for ADLs
Test for Residual Heterogeneity: QE(df = 7) = 5.9790, p-val = 0.5422
Test of Moderators (coefficient(s) 2): QM(df = 1) = 1.6741, p-val = 0.1957
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt -0.0084 0.2382 -0.0354 0.9717 -0.4754 0.4585 total.e 0.0072 0.0056 1.2939 0.1957 -0.0037 0.0181
Covariate: year of publication
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.0010 (SE = 0.0420)tau (square root of estimated tau^2 value): 0.0318I^2 (residual heterogeneity / unaccounted variability): 1.28%H^2 (unaccounted variability / sampling variability): 1.01R^2 (amount of heterogeneity accounted for): NA%
73
Rehabilitation in sub-acute stroke for ADLs
Test for Residual Heterogeneity: QE(df = 7) = 7.0911, p-val = 0.4195
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.5531, p-val = 0.4570
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt 24.8685 33.0649 0.7521 0.4520 -39.9376 89.6745 year -0.0123 0.0165 -0.7437 0.4570 -0.0446 0.0200
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Elsner 2016 Covariate: total participants in experimental group
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.0021 (SE = 0.0598)tau (square root of estimated tau^2 value): 0.0454I^2 (residual heterogeneity / unaccounted variability): 1.85%H^2 (unaccounted variability / sampling variability): 1.02R^2 (amount of heterogeneity accounted for): NA%
Test for Residual Heterogeneity: QE(df = 7) = 7.1316, p-val = 0.4153
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.0511, p-val = 0.8211
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Rehabilitation in sub-acute stroke for ADLs
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt 0.2857 0.2361 1.2097 0.2264 -0.1772 0.7485 total.e -0.0013 0.0056 -0.2261 0.8211 -0.0123 0.0097
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Covariate: year of publication
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.0028 (SE = 0.0601)tau (square root of estimated tau^2 value): 0.0526I^2 (residual heterogeneity / unaccounted variability): 2.46%H^2 (unaccounted variability / sampling variability): 1.03R^2 (amount of heterogeneity accounted for): NA%
Test for Residual Heterogeneity: QE(df = 7) = 7.1764, p-val = 0.4108
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.0151, p-val = 0.9021
Model Results:
estimate se zval pval ci.lb ci.ubintrcpt 18.0985 145.1570 0.1247 0.9008 -266.4040 302.6011year -0.0089 0.0721 -0.1230 0.9021 -0.1502 0.1325
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
75
Rehabilitation in sub-acute stroke for ADLs
Han 2018 Covariate: total participants in experimental group
Mixed-Effects Model (k = 14; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.5838 (SE = 0.2784)tau (square root of estimated tau^2 value): 0.7641I^2 (residual heterogeneity / unaccounted variability): 87.92%H^2 (unaccounted variability / sampling variability): 8.28R^2 (amount of heterogeneity accounted for): 1.50%
Test for Residual Heterogeneity: QE(df = 12) = 99.3263, p-val < .0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 1.1180, p-val = 0.2904
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt 1.8562 0.7776 2.3872 0.0170 0.3322 3.3802 *total.e -0.0238 0.0225 -1.0573 0.2904 -0.0680 0.0203
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
76
Rehabilitation in sub-acute stroke for ADLs
Covariate: year of publication
Mixed-Effects Model (k = 14; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.6408 (SE = 0.3061)tau (square root of estimated tau^2 value): 0.8005I^2 (residual heterogeneity / unaccounted variability): 89.28%H^2 (unaccounted variability / sampling variability): 9.33R^2 (amount of heterogeneity accounted for): 0.00%
Test for Residual Heterogeneity: QE(df = 12) = 111.9237, p-val < .0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.7772, p-val = 0.3780
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt -400.7202 455.7544 -0.8792 0.3793 -1293.9824 492.5420 year 0.1995 0.2263 0.8816 0.3780 -0.2440 0.6430
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
77
Rehabilitation in sub-acute stroke for ADLs
Yang 2016 Covariate: total participants in experimental group
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 0.2504 (SE = 0.1757)tau (square root of estimated tau^2 value): 0.5004I^2 (residual heterogeneity / unaccounted variability): 76.45%H^2 (unaccounted variability / sampling variability): 4.25R^2 (amount of heterogeneity accounted for): 78.65%
Test for Residual Heterogeneity: QE(df = 7) = 29.7232, p-val = 0.0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 23.9608, p-val < .0001
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt -1.5609 0.6061 -2.5753 0.0100 -2.7488 -0.3730 *total.e 0.0821 0.0168 4.8950 <.0001 0.0492 0.1150 ***
---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
78
Rehabilitation in sub-acute stroke for ADLs
Covariate: year of publication
Mixed-Effects Model (k = 9; tau^2 estimator: DL)
tau^2 (estimated amount of residual heterogeneity): 1.3374 (SE = 0.7597)tau (square root of estimated tau^2 value): 1.1565I^2 (residual heterogeneity / unaccounted variability): 94.54%H^2 (unaccounted variability / sampling variability): 18.30R^2 (amount of heterogeneity accounted for): 0.00%
Test for Residual Heterogeneity: QE(df = 7) = 128.1066, p-val < .0001
Test of Moderators (coefficient(s) 2): QM(df = 1) = 0.0316, p-val = 0.8590
Model Results:
estimate se zval pval ci.lb ci.ub intrcpt -60.1517 345.6822 -0.1740 0.8619 -737.6763 617.3730 year 0.0305 0.1718 0.1777 0.8590 -0.3061 0.3672
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
79
Rehabilitation in sub-acute stroke for ADLs
Sensitivity analysis
Han 2018
Influential analysis (Random effects model)
SMD 95%-CI p-value tau^2 I^2Omitting Chen 2012 1.1354 [0.6827; 1.5881] < 0.0001 0.6073 88.7%Omitting Feng 2014 0.9711 [0.5511; 1.3911] < 0.0001 0.5146 87.4%Omitting Feng 2015 1.0239 [0.5741; 1.4737] < 0.0001 0.6004 88.8%Omitting Liu 2015 1.1459 [0.7014; 1.5904] < 0.0001 0.5859 88.7%Omitting Luo 2014 0.9998 [0.5622; 1.4373] < 0.0001 0.5646 88.3%Omitting Luo 2014 1.1014 [0.6367; 1.5661] < 0.0001 0.6451 89.4%Omitting Qi 2015 1.0029 [0.5656; 1.4403] < 0.0001 0.5618 88.0%Omitting Wen 2014 1.1367 [0.6849; 1.5885] < 0.0001 0.6047 88.7%Omitting Wen 2015 1.1476 [0.7113; 1.5839] < 0.0001 0.5553 87.0%Omitting Wu 2015 1.1115 [0.6481; 1.5749] < 0.0001 0.6406 89.3%Omitting Xie 2013 1.1154 [0.6532; 1.5776] < 0.0001 0.6368 89.2%Omitting Xu 2013 1.0204 [0.5723; 1.4686] < 0.0001 0.5955 88.8%Omitting Yu 2014 1.0572 [0.5904; 1.5241] < 0.0001 0.6507 89.3%Omitting Zhou 2016 0.9784 [0.5499; 1.4069] < 0.0001 0.5430 88.2% Pooled estimate 1.0675 [0.6363; 1.4986] < 0.0001 0.5927 88.6%
80
Rehabilitation in sub-acute stroke for ADLs
Li 2014
Influential analysis (Random effects model)
SMD 95%-CI p-value tau^2 I^2Omitting Cheng 2011 1.4487 [0.7412; 2.1561] < 0.0001 1.2622 95.9%Omitting Hsing 2012 1.5061 [0.8102; 2.2019] < 0.0001 1.2179 95.7%Omitting Huang 2008 1.3782 [0.6759; 2.0805] 0.0001 1.2418 95.8%Omitting Pei 2001 1.0711 [0.4687; 1.6735] 0.0005 0.8992 94.5%Omitting Rao 2006 1.4942 [0.8028; 2.1856] < 0.0001 1.2047 95.8%Omitting Schuler 2005 1.5125 [0.8126; 2.2125] < 0.0001 1.2315 95.6%Omitting Shen 2012 1.5592 [0.7724; 2.3460] 0.0001 1.5751 95.8%Omitting Shu 2011 1.4864 [0.7522; 2.2205] < 0.0001 1.3618 95.9%Omitting Tong 2013 1.4354 [0.7192; 2.1517] < 0.0001 1.2938 95.9%Omitting Wu 2011 0.9172 [0.4961; 1.3384] < 0.0001 0.4460 89.9%Omitting Xie 2004 1.4326 [0.7246; 2.1406] < 0.0001 1.2641 95.9%Omitting Zhang 2008 1.4045 [0.6935; 2.1155] 0.0001 1.2739 95.8% Pooled estimate 1.3577 [0.7083; 2.0070] < 0.0001 1.1615 95.5%
81
Rehabilitation in sub-acute stroke for ADLs
Yang 2016
Influential analysis (Random effects model)
SMD 95%-CI p-value tau^2 I^2Omitting Bao 2012 1.3333 [0.5104; 2.1562] 0.0015 1.3303 94.4%Omitting Huang 2008 1.2111 [0.4014; 2.0207] 0.0034 1.2879 94.4%Omitting Ke 2015 1.1573 [0.3717; 1.9429] 0.0039 1.2064 93.9%Omitting Li 2010 1.3275 [0.5143; 2.1407] 0.0014 1.3002 94.5%Omitting Wu 2011 1.3241 [0.4987; 2.1495] 0.0017 1.3390 94.4%Omitting Yao 2014 1.4205 [0.6601; 2.1809] 0.0003 1.1237 93.4%Omitting Zhan 2014 0.9579 [0.4659; 1.4499] 0.0001 0.4261 84.7%Omitting Zhang 2015 1.3965 [0.6116; 2.1814] 0.0005 1.2025 93.8%Omitting Zheng 2014 1.2742 [0.4465; 2.1018] 0.0025 1.3476 94.5% Pooled estimate 1.2671 [0.5362; 1.9980] 0.0007 1.1726 93.8%
82
Rehabilitation in sub-acute stroke for ADLs
Subgroup Analysis
Thieme 2018
83
Rehabilitation in sub-acute stroke for ADLs
Yang 2016
84
Rehabilitation in sub-acute stroke for ADLs
85
Rehabilitation in sub-acute stroke for ADLs
Han 2018
86
Rehabilitation in sub-acute stroke for ADLs
Li 2014
APPENDIX EXCLUDED
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Rehabilitation in sub-acute stroke for ADLs
Broderick P, Horgan F, Blake C, Ehrensberger M, Simpson D, Monaghan K. Mirror therapy for improving lower limb motor function and mobility after stroke: A systematic review and meta-analysis. Gait Posture. 2018 Jun;63:208-220. doi: 10.1016/j.gaitpost.2018.05.017.
Li Y Wei Q, Gou W, He C Effects of mirror therapy on walking ability, balance and lower limb motor recovery after stroke: a systematic review and meta-analysis of randomized controlled trials. Clin Rehabil. 2018 Aug;32(8):1007-1021. doi: 10.1177/0269215518766642.
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APPENDIX Search strategy
Theme 1.: Stroke"Stroke"[Mesh] OR cva[tiab] OR cvas[tiab] OR poststroke*[tiab] OR stroke*[tiab] OR apoplex*[tiab]
Theme 3 RCTsSearch randomized controlled trial[pt] OR controlled clinical trial[pt] OR randomized[tiab] OR placebo[tiab] OR randomly[tiab] OR trial[tiab] OR groups[tiab]
Therapy , Search “ADLs” OR “activities of daily living” OR “ADL”OR “FIM”OR ”Functional” OR ”Independence”OR “Barthel” AND ("Physical Therapy Modalities"[MeSH] OR "Exercise Therapy"[Mesh] OR "Exercise Movement Techniques"[Mesh] OR "Physical Therapy (Specialty)"[MeSH] OR "Recovery of Function"[Mesh] OR "rehabilitation"[SH] OR rehabilitati*[tiab] OR physiotherap*[tiab] OR (physical[tiab] AND (therapy[tiab] OR therapies[tiab] OR activity[tiab] OR activities[tiab])) OR exercis*[tiab] OR training[tiab] OR (occupational[tiab] AND (therapy[tiab] OR therapies[tiab])))
Check wordsArticle type: ReviewFilter: meta-analysis
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Supplementary Figure 1. Funnel plots of ( > 1 study) publications in Figure 3
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Supplementary Figure 2. Work design diagram taking as starting point the outcome of PRISMA Flow diagram of the study selection process presented in Figure 1
APPENDIX
Supplementary Table 1. PICOS criteria used in the present umbrella review
Parameter
Description
Population
Inclusion: stroke patients >18 yearsExclusion: children and pregnant women
Intervention
Inclusion: sub-acute phase physical rehabilitation Exclusion: other rehabilitation (cognitive, language,..)
Comparis Randomized clinical trials: Rehabilitation intervention versus no
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on intervention or standard rehabilitation or usual care
Outcome Inclusion: ADLs outcomes scales, regarded as continuous scaled, where usually higher scores indicate a good outcome, for example Functional Independence Measure (FIM), Barthel Index (BI), modified Rankin Scale (mRS), Frenchay Activities Index (FAI), Rivermead ADL Assessment, Katz Index of Independence in Activities of Daily Living, Motor Activity Log (MAL), modified Barthel Index (mBI).)Exclusion: not ADLs-related outcomes
Study design
Inclusion: systematic reviews including meta-analyses (quantitative analysis) of randomized clinical trials Exclusion: studies not published as peer-reviewed meta-analyses in international scientific journals, systematic reviews without quantitative analysis
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Supplementary Table 2. Cases and controls grouped by intervention
INTERVENTION CASE CONTROL TOTALACUPUNCT 1442 1425 2867ROBOT 1524 1303 2827
CIM 724 721 1445
tDCS 565 428 993
MOXIBUS 459 434 893
RTT 448 404 852
MIRROR THERAPY
333 289 622
TAI CHI 280 277 557
ELECTROACU 262 260 522
VR 276 231 507
mCIM 219 215 434
CIRCUIT 147 149 296
rTMS 93 90 183
SLING 88 88 176
IMAGERY 81 81 162
AUGMENTED 66 72 138
BILATERAL 61 56 117
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FES 32 33 65
rPMS 31 32 63
Wii 20 17 37
HYDROTHERAPY 16 15 31
APPENDIXSupplementary Table 3. Quality assessment (AMSTAR) of included meta-analyses
Author, Year 1 2 3 4 5 6 7 8 9 10 11 Total ScoreMehrholz 2015 [31] Y Y Y Y Y Y Y Y Y Y Y 11Norouzi 2012 [32] Y Y Y Y Y Y Y Y Y N N 9Veerbeek 2017 [1] Y Y Y Y Y Y Y Y Y N Y 10Chen 2016 [33] Y Y Y Y N Y Y Y Y Y N 9Cheok 2015 [34] Y Y Y Y N Y Y Y Y Y Y 10Elsner 2016 [10] Y Y Y Y Y Y Y Y Y Y Y 11Triccas 2015 [35] Y Y Y Y N Y Y Y Y N Y 9Banchetti 2017 [36] Y Y Y N N Y Y Y Y N N 7Han 2018 [37] Y Y Y N N Y Y Y Y Y Y 9Lee 2013 [38] Y Y Y Y N Y Y Y Y Y Y 10Li 2014 [39] Y Y Y Y N Y Y Y Y Y Y 10Yang 2016 [40] Y Y Y Y Y Y Y Y Y Y Y 11Peng 2018 [41] Y Y Y N N Y Y Y Y N Y 8Corbetta 2010 [42] Y Y Y N N Y Y Y Y N Y 8Peurala 2012 [43] Y Y Y N N Y Y Y Y N N 7Shi 2011 [44] Y Y Y Y N Y Y Y Y N Y 9Laver 2012 [45] Y Y Y Y Y Y Y Y Y Y Y 11Laver 2015 [46] Y Y Y Y Y Y Y Y Y Y Y 11Eraifej 2017 [47] Y Y Y Y Y Y Y Y Y Y Y 11French 2010 [48] Y Y Y N N Y Y Y Y N Y 8French 2016 [49] Y Y Y Y Y Y Y Y Y Y Y 11Lee 2017 [50] Y Y Y N N Y Y Y Y N Y 8Veerbeek 2011 [51] Y Y Y N N Y Y Y Y N Y 8Fernandes 2017[52]
Y Y Y N N Y Y Y Y Y Y 9
Cai 2017 [53] Y Y Y N N Y Y Y Y Y Y 9Lyu 2018 [54] Y Y Y N N Y Y Y Y Y Y 9Mehrholz 2011 [55] Y Y Y Y Y Y Y Y Y Y Y 11Thieme 2018 [56] Y Y Y Y Y Y Y Y Y Y Y 11Hao 2013 [57] Y Y Y Y Y Y Y Y Y Y Y 11English 2017 [58] Y Y Y Y Y Y Y Y Y Y Y 11Momosaki 2017[11] Y Y Y Y Y Y Y Y Y Y Y 11
Y = Yes, criteria met (1 point), N = No, criteria not met (0 points), UA = unable to answer (0 points)1. Was an ’a priori’ design provided?2. Was there duplicate study selection and data extraction?3. Was a comprehensive literature search performed?4. Was the status of publication (i.e. grey literature) used as an inclusion criterion?5. Was a list of studies (included and excluded) provided?6. Were the characteristics of the included studies provided?7. Was the scientific quality of the included studies assessed and documented?8. Was the scientific quality of the included studies used appropriately in formulating conclusions?9. Were the methods used to combine the findings of studies appropriate?10. Was the likelihood of publication bias assessed?
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11. Was the conflict of interest stated?
APPENDIXSupplementary Table 4. Mean AMSTAR score grouped by intervention of included meta-analyses
Intervention MeanCIM 7,5AUGMENTED 8
BILATERAL 8
tDCS 8
ELECTROACU 9
IMAGERY 9
mCIM 9
MOXIBUSTION 9
SLING 9
TAI-CHI 9
RTT 9,5
ACUPUNCTURE 9,75
ROBOTIC 10
Wii 10
CIRCUIT 11
FES 11
HYDROTHERAPY 11
MIRROR THERAPY
11
rPMS 11
rTMS 11
tCDS 11
VR 11
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Supplementary Table 5. Regression models with pval < 0.05 for the total participants in experimental group covariate (for meta-analysis with ≥ 9 studies)
estimate se zval pval ci.lb ci.ub Study-0.0228 0.0096 -2.3827 0.0172 -0.0415 -0.0040 Thieme
20180.0821 0.0168 4.8950 <.0001 0.0492 0.1150 Yang 2016
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2.28% and 8.21% respectively of effect size is explained by the number of participants in the experimental group.
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