目的观察右美托咪定用于椎间孔镜手术的效果。方法选取安徽医科大学第一附属医院2020年9月至2021年5月收治的腰椎间盘突出症患者75例为研究对象,3组均行单节段单侧入路的椎间孔镜手术,A组为单纯关节突浸润麻醉组,B组及C组患者术前予以0....目的观察右美托咪定用于椎间孔镜手术的效果。方法选取安徽医科大学第一附属医院2020年9月至2021年5月收治的腰椎间盘突出症患者75例为研究对象,3组均行单节段单侧入路的椎间孔镜手术,A组为单纯关节突浸润麻醉组,B组及C组患者术前予以0.5μg·kg^(-1)·h^(-1)右美托咪定泵注,泵注时间为20 min,手术开始后调整B组为关节突浸润麻醉复合0.4μg·kg^(-1)·h^(-1)右美托咪定,C组为关节突浸润麻醉复合0.6μg·kg^(-1)·h^(-1)右美托咪定持续泵注至手术结束。观察比较术中患者生命体征、镇静情况、术中患者镇静评分、术后两组患者住院时长、术后即时疼痛评分(VAS)、术后3 h、术后6 h疼痛评分,术中不同节点生命体征变化等。结果3组患者在年龄、性别及手术节段等一般资料方面差异均无统计学意义(均P>0.05);3组患者术后住院时间分别为(5.12±1.15)d、(3.02±0.42)d、(3.82±0.54)d,差异有统计学意义(F=32.04,P<0.01);手术开始时3组镇静评分分别为(1.22±0.29)分、(1.28±0.36)分、(1.46±0.38)分,差异有统计学意义(F=3.28,P<0.05);手术开始30 min后3组镇静评分分别为(2.12±0.22)分、(2.16±0.24)分、(2.20±0.24)分,差异有统计学意义(F=3.72,P<0.01);3组术后即时疼痛VAS评分分别为(3.52±0.33)分、(2.92±0.55)分、(2.82±0.54)分,差异有统计学意义(F=15.16,P<0.01);3组术后3 h VAS评分分别为(3.64±0.39)分、(2.60±0.58)分、(2.74±0.54)分,差异有统计学意义(F=30.47,P<0.01);3组术后6 h VAS评分分别为(3.78±0.43)分、(2.52±0.47)分、(2.74±0.52)分,差异有统计学意义(F=49.90,P<0.01)。3组在关节突穿刺时、套管扩张椎间孔时、抓取神经周围突出髓核时VAS评分、心率以及平均动脉压差异均有统计学意义(F=34.59、148.65、164.08、5.08、10.81、38.06、43.62、37.46、38.76,均P<0.05)。结论腰椎间盘突出症椎间孔镜手术前予以右美托咪定可有效维持血流动力学稳定,维持患者镇静,减轻患者疼痛,进而加快术后康复。展开更多
In recent years,deep neural network has achieved great success in solving many natural language processing tasks.Particularly,substantial progress has been made on neural text generation,which takes the linguistic and...In recent years,deep neural network has achieved great success in solving many natural language processing tasks.Particularly,substantial progress has been made on neural text generation,which takes the linguistic and non-linguistic input,and generates natural language text.This survey aims to provide an up-to-date synthesis of core tasks in neural text generation and the architectures adopted to handle these tasks,and draw attention to the challenges in neural text generation.We first outline the mainstream neural text generation frameworks,and then introduce datasets,advanced models and challenges of four core text generation tasks in detail,including AMR-to-text generation,data-to-text generation,and two text-to-text generation tasks(i.e.,text summarization and paraphrase generation).Finally,we present future research directions for neural text generation.This survey can be used as a guide and reference for researchers and practitioners in this area.展开更多
文摘目的观察右美托咪定用于椎间孔镜手术的效果。方法选取安徽医科大学第一附属医院2020年9月至2021年5月收治的腰椎间盘突出症患者75例为研究对象,3组均行单节段单侧入路的椎间孔镜手术,A组为单纯关节突浸润麻醉组,B组及C组患者术前予以0.5μg·kg^(-1)·h^(-1)右美托咪定泵注,泵注时间为20 min,手术开始后调整B组为关节突浸润麻醉复合0.4μg·kg^(-1)·h^(-1)右美托咪定,C组为关节突浸润麻醉复合0.6μg·kg^(-1)·h^(-1)右美托咪定持续泵注至手术结束。观察比较术中患者生命体征、镇静情况、术中患者镇静评分、术后两组患者住院时长、术后即时疼痛评分(VAS)、术后3 h、术后6 h疼痛评分,术中不同节点生命体征变化等。结果3组患者在年龄、性别及手术节段等一般资料方面差异均无统计学意义(均P>0.05);3组患者术后住院时间分别为(5.12±1.15)d、(3.02±0.42)d、(3.82±0.54)d,差异有统计学意义(F=32.04,P<0.01);手术开始时3组镇静评分分别为(1.22±0.29)分、(1.28±0.36)分、(1.46±0.38)分,差异有统计学意义(F=3.28,P<0.05);手术开始30 min后3组镇静评分分别为(2.12±0.22)分、(2.16±0.24)分、(2.20±0.24)分,差异有统计学意义(F=3.72,P<0.01);3组术后即时疼痛VAS评分分别为(3.52±0.33)分、(2.92±0.55)分、(2.82±0.54)分,差异有统计学意义(F=15.16,P<0.01);3组术后3 h VAS评分分别为(3.64±0.39)分、(2.60±0.58)分、(2.74±0.54)分,差异有统计学意义(F=30.47,P<0.01);3组术后6 h VAS评分分别为(3.78±0.43)分、(2.52±0.47)分、(2.74±0.52)分,差异有统计学意义(F=49.90,P<0.01)。3组在关节突穿刺时、套管扩张椎间孔时、抓取神经周围突出髓核时VAS评分、心率以及平均动脉压差异均有统计学意义(F=34.59、148.65、164.08、5.08、10.81、38.06、43.62、37.46、38.76,均P<0.05)。结论腰椎间盘突出症椎间孔镜手术前予以右美托咪定可有效维持血流动力学稳定,维持患者镇静,减轻患者疼痛,进而加快术后康复。
基金the National Natural Science Foundation of China(Grant No.61772036)the Key Laboratory of Science,Technology and Standard in Press Industry(Key Laboratory of Intelligent Press Media Technology)。
文摘In recent years,deep neural network has achieved great success in solving many natural language processing tasks.Particularly,substantial progress has been made on neural text generation,which takes the linguistic and non-linguistic input,and generates natural language text.This survey aims to provide an up-to-date synthesis of core tasks in neural text generation and the architectures adopted to handle these tasks,and draw attention to the challenges in neural text generation.We first outline the mainstream neural text generation frameworks,and then introduce datasets,advanced models and challenges of four core text generation tasks in detail,including AMR-to-text generation,data-to-text generation,and two text-to-text generation tasks(i.e.,text summarization and paraphrase generation).Finally,we present future research directions for neural text generation.This survey can be used as a guide and reference for researchers and practitioners in this area.
