目的通过累积Meta分析方法评价核心稳定性训练对腰椎间盘突出患者疼痛、功能障碍的影响。方法计算机检索中国知网、万方数据库、维普数据库、MEDLINE、Embase、CINAHL、PEDro、Rehabilitation&Sports Medicine Source、Cochrane Lib...目的通过累积Meta分析方法评价核心稳定性训练对腰椎间盘突出患者疼痛、功能障碍的影响。方法计算机检索中国知网、万方数据库、维普数据库、MEDLINE、Embase、CINAHL、PEDro、Rehabilitation&Sports Medicine Source、Cochrane Library中关于采用核心稳定性训练干预腰椎间盘突出症患者的随机对照试验,并追踪其参考文献。由两名研究者独立筛选文献,并采用PEDro量表对纳入的文献进行偏倚风险评价。采用Stata MP 16.0软件进行累积Meta分析。结果共纳入18篇文献,共纳入1347例患者。累积Meta分析显示,与常规康复治疗相比,核心稳定性训练可以改善腰椎间盘突出症患者的腰椎功能[MD=2.58(95%CI:1.60,3.56),P<0.001],减轻功能障碍的严重程度[MD=-5.82(95%CI:-8.72,-2.86),P<0.001],减轻疼痛[MD=-0.89(95%CI:-1.20,-0.58),P<0.001]。结论现有的研究已证实核心稳定性训练可以改善腰椎间盘突出患者的腰椎功能,减轻疼痛,但对功能障碍的改善程度尚需要更多可靠的随机对照实验予以验证。展开更多
Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast.The quality of rainfall data in terms of both intensity and dis...Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast.The quality of rainfall data in terms of both intensity and distribution is very important for establishing a reliable meteo-hydrological forecasting model.To improve the accuracy of rainfall data,the successive correction method is introduced to correct the bias of rainfall,and a meteo-hydrological forecasting model based on WRF and WRF-Hydro is applied for streamflow forecast over the Zhanghe River catchment in China.The performance of WRF rainfall is compared with the China Meteorological Administration Multi-source Precipitation Analysis System(CMPAS),and the simulated streamflow from the model is further studied.It shows that the corrected WRF rainfall is more similar to the CMPAS in both temporal and spatial distribution than the original WRF rainfall.By contrast,the statistical metrics of the corrected WRF rainfall are better.When the corrected WRF rainfall is used to drive the WRF-Hydro model,the simulated streamflow of most events is significantly improved in both hydrographs and volume than that of using the original WRF rainfall.Among the studied events,the largest improvement of the NSE is from-0.68 to 0.67.It proves that correcting the bias of WRF rainfall with the successive correction method can greatly improve the performance of streamflow forecast.In general,the WRF/WRF-Hydro meteo-hydrological forecasting model based on the successive correction method has the potential to provide better streamflow forecast in the Zhanghe River catchment.展开更多
基金Program of Key Laboratory of Meteorological Disaster(KLME202209)National Key R&D Program of China(2017YFC1502102)。
文摘Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast.The quality of rainfall data in terms of both intensity and distribution is very important for establishing a reliable meteo-hydrological forecasting model.To improve the accuracy of rainfall data,the successive correction method is introduced to correct the bias of rainfall,and a meteo-hydrological forecasting model based on WRF and WRF-Hydro is applied for streamflow forecast over the Zhanghe River catchment in China.The performance of WRF rainfall is compared with the China Meteorological Administration Multi-source Precipitation Analysis System(CMPAS),and the simulated streamflow from the model is further studied.It shows that the corrected WRF rainfall is more similar to the CMPAS in both temporal and spatial distribution than the original WRF rainfall.By contrast,the statistical metrics of the corrected WRF rainfall are better.When the corrected WRF rainfall is used to drive the WRF-Hydro model,the simulated streamflow of most events is significantly improved in both hydrographs and volume than that of using the original WRF rainfall.Among the studied events,the largest improvement of the NSE is from-0.68 to 0.67.It proves that correcting the bias of WRF rainfall with the successive correction method can greatly improve the performance of streamflow forecast.In general,the WRF/WRF-Hydro meteo-hydrological forecasting model based on the successive correction method has the potential to provide better streamflow forecast in the Zhanghe River catchment.
