Indexed on: 06 Oct '16Published on: 18 Sep '16Published in: Complementary Therapies in Medicine
Publication date: Available online 12 September 2016 Source:Complementary Therapies in Medicine Author(s): Da-long Wang, Xiao-guang Lu, Wen-xiu Guo, Tuo Chen, Yi Song, Zhi-wei Fan Background Chinese herbal medicine (CHM) has been widely used in the treatment of hemorrhagic shock (HS) in China. Many controlled trials have been undertaken to investigate its efficacy. Objective To evaluate the effectiveness and safety of CHM for Hemorrhagic Shock patients. Methods We screening the Web of ScienceDirect database, PubMed, the Cochrane Library, EMBASE, China Biomedical Database web (CBM), China National Knowledge Infrastructure (CNKI) and WanFang database (WF), from inception to January, 2015. All the randomized controlled trials (RCTs) that compared CHM plus conventional therapy with conventional therapy alone for HS patients were included. Meta-analysis on included studies was performed using fixed-effects model with RevMan5.2. Risk ratio (RR) or mean difference (MD) with a 95% confidence interval (CI) was used as effect measure. STATA 12.0 was used for publication bias. Results Fifteen RCTs involving 1076 participants were included in the meta-analysis. CHM combined with conventional therapy was tested to be more effective in reduce mortality (RR=0.24,95%CI:0.13- 0.46, P <0.0001), reduce the incidence of MODS (RR=0.47, 95%CI: 0.34- 0.66,P <0.00001), symptomatic improvement: increase blood pressure(BP)(MD=8.83,95%CI:6.82-10.84,P<0.00001), regulate heart rate (MD=−7.6,95%CI:-9.17—-6.02,P<0.00001), increase urine volume (MD=7.26,95%CI:5.00-9.53,P<0.00001), compared with conventional therapy alone. No serious adverse events were reported. Conclusions CHM combined with conventional therapy seems to be more effective on HS patients. However, the analysis results should be interpreted with caution due to the low methodological quality of the included trials. Future, the rigorously designed, high methodological quality, multicenter and large-scale trials are needed to confirm these conclusions.