Incidence Rate of Adverse Transfusion Reaction in Grade Three Class-A Hospitals in China: A Meta-analysis of Single rate

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1 Review Articles Chin J Evid-based Med 2015, 15(3): , * 2* PubMed EMbase The Cochrane Library CNKI VIP WanFang Data CBM R Meta Meta 0.58% 95%CI P< % 95%CI P< % 95%CI P< % 95%CI P< P< % 95%CI P< % 95%CI P< % 95%CI P< % 95%CI P< % 95%CI P< P<0.05 Meta Incidence Rate of Adverse Transfusion Reaction in Grade Three Class-A Hospitals in China: A Meta-analysis of Single rate TENG Fang 1,2, ZHANG Yan 2, SUN Gui-xiang 2, LIN Hui 1, XIONG Hong-yan 1*, WEN Ai-qing 2* 1. Department of Epidemiology, Faculty of Military Prevention Medicine, Third Military Medical University, Chongqing , China; 2. Department of Blood Transfusion, Daping Hospital, Third Military Medical University, Chongqing , China Abstract Objective To systematically review the characteristics of adverse transfusion reaction in Grade Three Class-A hospitals in China, and to provide scientific evidence for related control and prevention work. Methods databases as the PubMed, EMbase, The Cochrane Library (Issue 11, 2014), CNKI, VIP, WanFang Data and CBM were searched for studies investigating the characteristics of adverse transfusion reaction with6 months observation time in Grade Three Class-A hospitals in China up to November Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data and assessed the methodological quality of included studies. Then, meta-analysis was performed by using the R software. Results Seventy-two studies involving cases of blood transfusion were included. The results of pooled analysis showed that the total number of adverse transfusion reaction rate was 0.58% (95%CI 0.48 to 0.69). Sub-group analysis shows that the blood transfusion adverse reaction rates in the eastern, central and western regions were 0.42% (95%CI 0.31 to 0.55), 0.55% (95%CI 0.41 to 0.70), 0.56% (95%CI 0.43 to 0.70), respectively; and there were statistical differences between regions (P<0.05). Different types of adverse transfusion reaction rates were 38.85% (95%CI to 43.53) for non hemolytic febrile reaction and 55.67% (95%CI to 60.50) for allergic. The adverse reactions incidence of different kinds of blood products transfusion occurred were 0.41% (95%CI 0.32 to 0.50) in red blood cell, 0.57% (95%CI 0.43 to 0.72) in plasma, 1.00% (95%CI 0.73 to 1.30) in platelet. The incidence of adverse reaction of platelet transfusion was significantly higher than that of red blood cell and plasma (P<0.05). Conclusion There is a big gap between domestic and foreign blood transfusion adverse reaction reports, therefore comprehensive measures should be taken for further prevention and control. Key words Blood transfusion; Adverse reaction; Transfusion reaction; Incidence; Meta-analysis Such DOI: / tengzi831110@163.com * hongyanxiong@126.com dpyysxkwaq@hotmail.com Editorial Board of Chin J Evid-based Med

32 0.50P<0.000 1 0.57% 95%CI 0.43 0.72P<0.000 1 1.00% 95%CI 0.73 1.30P<0.000 1 P<0.

2 2015, 15(3): [1] [2] 2000 [3] Meta PubMed EMbase The Cochrane Library CNKI VIP WanFang Data CBM blood transfusion adverse reaction transfusion reaction incidence 2015 EMbase [4-6] <20% R Meta Freeman-Tukey 95%CI [7] Homogeneity test Q α=0.1 I 2 P 0.10 I 2 50% Meta Meta Eggers test Meta α= [8] EMbase #1 blood transfusion reaction /exp #2 china /exp or china #3 #1 AND #2 283

transfusion reaction incidence 2015 EMbase 1 1.3 2 [4-6] 5 1 0 <20% 4 1.4 R 3.1.1 Meta Freeman-Tukey 95%CI [7] Homogeneity test Q α=0.

3 Review Articles [9-80] Meta % [71] 6.22% [57] Meta 0.58% 95%CI P< Meta 0.42%95%CI P< %95%CI P< %95%CI P< Chin J Evid-based Med 2015, 15(3): χ 2 = P< %0.55%χ 2 = P< %χ 2 = P<0.05 [57] [12] [26] 6.22% 5.21% 6.09% Meta 38.85% 95%CI P< % 95%CI P< Meta 0.41% 95%CI P< % 95%CI P< % 95%CI P< n=8 045 PubMed n=269embase n=86the Cochrane Library n=27cnki n=1 838VIP n=1 931 WanFang Data n=2 307CBM n=1 587 n=0 n=4 849 n=4 849 n=4 607 n=366 n=4 241 n=242 n=170 n= n=3 n=3 n=70 4 n=1 n=72 Meta n= Editorial Board of Chin J Evid-based Med

159 P<0.05 3 0.42%0.55%χ 2 =207.159 P<0.05 0.56%χ 2 =28.634 P<0.05 [57] [12] [26] 6.22% 5.21% 6.09% 2.3.2 66 Meta 38.85% 95%CI 34.27 43.53P<0.000 1 55.67% 95%CI 50.79 60.50 P<0.000 1 4 2.3.3 49 48 44 460 321 434 726 78 393 1 903 2 176 643 Meta 0.

4 2015, 15(3): / 2006 [9] / / / [10] /257 16/ / / [11] [12] /149 0/13 9/ [13] /294 63/ / / [14] /56 13/ / / [15] /24 47/ / / [16] /86 72/ / / [17] /90 13/ / / [18] /105 69/ / / [19] /105 66/ / / [20] / / / / [21] / 105/ 119/ 17/ [22] / / /88 5 Chen 2009 [23] [24] / / / / [25] / / / [26] [27] /2 3/ /807 0/ [28] /15 73/ / / [29] /101 21/ / / [30] /105 8/ / / [31] / 63/ 117/ [32] /19 22/ / / [33] /209 39/ / / [34] /26 22/ / / [35] / / / / [36] / / / [37] / / / [38] /218 42/ / / [39] /46 9/ / / [40] /89 33/ / / [41] / / / [42] / 41/ 5/ [43] [44] [45] / 94/ 22/ 25/ [46] / 28/ 49/ 3/ [47] [48] / / / [49] / 10/ 83/ [50] / / / [51] /9 25/ / / [52] [53] /58 8/ / / [54] [55] / 22/ 54/ 7/

[15] 2006 2007 10 628 155 62 84 9 1/24 47/5 200 88/4 833 18/488 5 2008 [16] 2005 2007 8 117 99 78 13 8 1/86 72/4 170 22/3 629 1/113 4 2008 [17] 2007 8 111 42 20 18 4 2/90 13/4 090 22/3 601 5/330 4

5 Review Articles Chin J Evid-based Med 2015, 15(3): / 2013 [56] / / / [57] / / / / [58] [59] / / / [60] /199 33/ / / [61] / / / [62] [63] [64] [65] / / / [66] / 54/ 12/ 0/ [67] /2 7/ / / [68] [69] / / / [70] /150 35/ / / [71] / / / [72] / / / [73] [74] / 17/ 2/ [75] / / / [76] / / / [77] /101 21/ / / [78] / / / [79] / / / [80] / / / Meta Meta 95%CI P 72 [9-80] I 2 =98.7% P< % < Meta Meta 95%CI P 27 [9,15,17,19,23,25,27,30,31,34,36-38,41,45,47,49,53,56,61,62,64,67,71,77,78] I 2 =98.3% P< % < [10,18,21,28,29,32,50,52,60,63,68,69,70,73] I 2 =97% P< % < [11,13,14,16,20,22,24,33,35,39,40,42,43,44,46,48,51,54,55,58,59,65,66,72,74,75,76,79,80] I 2 =97.9% P< % < Meta Meta 95%CI P 66 [9-21,24,26,28-51,53-72,74,80] I 2 =92.9% P< % < [9-21,24,26,28-51,53-72,74,80] I 2 =93.3% P< % < Editorial Board of Chin J Evid-based Med

2012 6 693 30 18 12 0 21/4 070 6/1 259 3/1 364 4 2013 [62] 2009 2011 11 350 62 34 27 1 4 2013 [63] 2011 2012 23 828 48 30 16 2 5 2013 [64] 2007 2012 31 046 63 22 37 4 5 2013 [65] 2005 2012 18 060 150

6 2015, 15(3): Meta Meta 95%CI P 49 [9,10,12-20,22,24,25,27-30,32-41,48,50,51,53,56-61,65,67,69-72,75-80] I 2 =95.4% P< % < [9,10,13-20,22,24,25,27-30,32-41,48,50,51,53,56,57,59-61,65,67,69-72,75-80] I 2 =97.4% P< % < [9,10,13-20,24,25,28-30,32,35-41,48,50,51,56,57,59-61,65,67,69-72,76-80] I 2 =92.8% P< % < P<0.05 [57] 15.47% [12] 18.37% 2.4 Egger Eggers test P> Meta [81] Meta 0.58% 0.41% 0.57% 1.00% [82-84] [82] % 0.55%0.56% P< [85-87] [88-90] [91] [92] [93] 1,,.., 2011, 24(3):

000 1 44 [9,10,13-20,24,25,28-30,32,35-41,48,50,51,56,57,59-61,65,67,69-72,76-80] 643 78 393 I 2 =92.8% P<0.000 1 1.00% 0.73 1.30 <0.000 1 57 12 P<0.05 [57] 15.47% [12] 18.

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8 2015, 15(3): , 2013, 12(8): ,.., 2013, (12): , 2013, 34(11): ,,. 150., 2013, 37(9): ,.., 2013, 26(11): ,,,.., 2013, (36): , ,.. ( ), 2013, (6): , 2013, 13(18): ,,, , 2013, 6(12A): ,,.., 2013, 20(10): ,.., 2013, (41): ~2012., 2014, 16(2): ,,,. 32., 2014, 35(6): ,,,. 61., 2014, 16(2): ,,,. 61., 2014, 27(8): , 2014, (17): , 2014, 21(4): ,.., 2014, 11(19): ( ), 2014, 24(2): ,,. Meta Stata., 2012, 12(1): Siegenthaler MA, Schneider P, Vu DH, et al. Haemovigilance in a general university hospital: need for a more comprehensive classification and a codification of transfusion-related events Vox Sanguinis, 2005, 88: Andreu G, Morel P, Forestier F, et al. Hemovigilance network in France: organization and analysis of immediate transfusion incident reports from 1994 to1998. Transfusion, 2002, 42: Robillard P, Nawej KI, Jochem K. The Quebec hemovigilance system: description and results from the first two years. Transfusion and Apheresis Science, 2004, 31: Williamson LM, Lowe S, Love EM, et al. Serious hazards of transfusion (SHOT) initiative: analysis of the first two annual reports. BMJ, 1999, 319(7201): Rebibo D, Hauser L, Slimani A. The French Haemovigilance System: organizationand resultsfor Transfusion and Apheresis Science, 2004, 31: Keller-Stanislawski B, Lohmann A, Gunay S, et al. The German Haemovigilance System reports of serious adverse transfusion reactions between 1997 and Transfusion Medicine, 2009, 19: Flesland O. A comparison of complication rates based on published haemovigilance data. Intensive Care Med, 2007, 33(1): Dr Hannah Cohen, Ms Alison Watt, Ms Debbi Poles, et al. Annual SHOT Report United Kingdom: Manchester Blood Centre, Stainsby D, Jones H, Asher D, et al. Serious Hazards of Transfusion:A Decade of Hemovigilance in the UK. Transfusion Medicine Reviews, 2006, 20(4): ,,.., 2006, 19(3): ,.., 2009, 22(10): ,,.., 2004, 17(5):

74,,,. 32., 2014, 35(6):799-800. 75,,,. 61., 2014, 16(2): 166-167. 76,,,. 61., 2014, 27(8): 171-171. 77.., 2014, (17): 77-78. 78. 2008-2011., 2014, 21(4): 108-110. 79,.., 2014, 11(19): 2654-2655. 80.

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