目的探究超声联合神经刺激仪定位腰丛及坐骨神经阻滞在椎管内麻醉禁忌证患者中的应用效果。方法选取本院2019年6月至2019年10月收治72例的下肢手术患者作为研究对象,随机分为观察组与对照组,各36例。对照组采用全身麻醉,观察组采用超声...目的探究超声联合神经刺激仪定位腰丛及坐骨神经阻滞在椎管内麻醉禁忌证患者中的应用效果。方法选取本院2019年6月至2019年10月收治72例的下肢手术患者作为研究对象,随机分为观察组与对照组,各36例。对照组采用全身麻醉,观察组采用超声联合神经刺激仪定位并麻醉,对比两组患者术后不良反应及疗效。结果观察组患者在阻滞前、阻滞后10 min及30 min MAP及HR比较差异无统计学意义,对照组在阻滞后10 min与30 min HR及MAP均明显低于阻滞前(P<0.05);观察组不良反应发生率(8.33%)明显低于对照组(36.11%)(P<0.05);观察组阻滞完成时间、麻醉起效时间均明显短于对照组(P<0.05),镇痛维持时间明显长于对照组(P<0.05)。结论超声联合神经刺激仪定位腰丛及坐骨神经阻滞效果显著,生理功能干扰小,可在短时间内完成阻滞,快速起效,且镇痛持续时间长,是椎管内麻醉禁忌证患者可用的有效麻醉方法。展开更多
We present a novel adaptive finite element method(AFEM)for elliptic equations which is based upon the Centroidal Voronoi Tessellation(CVT)and superconvergent gradient recovery.The constructions of CVT and its dual Cen...We present a novel adaptive finite element method(AFEM)for elliptic equations which is based upon the Centroidal Voronoi Tessellation(CVT)and superconvergent gradient recovery.The constructions of CVT and its dual Centroidal Voronoi Delaunay Triangulation(CVDT)are facilitated by a localized Lloyd iteration to produce almost equilateral two dimensional meshes.Working with finite element solutions on such high quality triangulations,superconvergent recovery methods become particularly effective so that asymptotically exact a posteriori error estimations can be obtained.Through a seamless integration of these techniques,a convergent adaptive procedure is developed.As demonstrated by the numerical examples,the new AFEM is capable of solving a variety of model problems and has great potential in practical applications.展开更多
文摘目的探究超声联合神经刺激仪定位腰丛及坐骨神经阻滞在椎管内麻醉禁忌证患者中的应用效果。方法选取本院2019年6月至2019年10月收治72例的下肢手术患者作为研究对象,随机分为观察组与对照组,各36例。对照组采用全身麻醉,观察组采用超声联合神经刺激仪定位并麻醉,对比两组患者术后不良反应及疗效。结果观察组患者在阻滞前、阻滞后10 min及30 min MAP及HR比较差异无统计学意义,对照组在阻滞后10 min与30 min HR及MAP均明显低于阻滞前(P<0.05);观察组不良反应发生率(8.33%)明显低于对照组(36.11%)(P<0.05);观察组阻滞完成时间、麻醉起效时间均明显短于对照组(P<0.05),镇痛维持时间明显长于对照组(P<0.05)。结论超声联合神经刺激仪定位腰丛及坐骨神经阻滞效果显著,生理功能干扰小,可在短时间内完成阻滞,快速起效,且镇痛持续时间长,是椎管内麻醉禁忌证患者可用的有效麻醉方法。
基金supported in part by the NSFC Key Project(11031006)Hunan Provincial NSF Project(10JJ7001)+2 种基金supported in part by Hunan Education Department Key Project 10A117supported in part by NTU star-up grant M58110011,MOE RG 59/08 M52110092 and NRF 2007IDM-IDM 002-010,Singaporesupported partially by NSF DMS-0712744 and NSF DMS-1016073.
文摘We present a novel adaptive finite element method(AFEM)for elliptic equations which is based upon the Centroidal Voronoi Tessellation(CVT)and superconvergent gradient recovery.The constructions of CVT and its dual Centroidal Voronoi Delaunay Triangulation(CVDT)are facilitated by a localized Lloyd iteration to produce almost equilateral two dimensional meshes.Working with finite element solutions on such high quality triangulations,superconvergent recovery methods become particularly effective so that asymptotically exact a posteriori error estimations can be obtained.Through a seamless integration of these techniques,a convergent adaptive procedure is developed.As demonstrated by the numerical examples,the new AFEM is capable of solving a variety of model problems and has great potential in practical applications.
