Combined Optimal Dispatch of Thermal Power Generators and Energy Storage Considering Thermal Power Deep Peak Clipping and Wind Energy Emission Grading Punishment

Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.

Relationship between neonatal respiratory distress syndrome pulmonary ultrasonography and respiratory distress score,oxygenation index,and chest radiography grading

BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a less harmful method for assessing the health of neonates with RDS is needed.AIM To analyze the relationships between pulmonary ultrasonography and respiratory distress scores,oxygenation index,and chest X-ray grade of neonatal RDS to identify predictors of neonatal RDS severity.METHODS This retrospective study analyzed the medical information of 73 neonates with RDS admitted to the neonatal intensive care unit of Liupanshui Maternal and Child Care Service Center between April and December 2022.The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest Xray grade of each newborn before and after treatment were collected.Spearman correlation analysis was performed to determine the relationships among these values and neonatal RDS severity.RESULTS The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest X-ray RDS grade of the neonates were significantly lower after treatment than before treatment(P<0.05).Spearman correlation analysis showed that before and after treatment,the pulmonary ultrasonography score of neonates with RDS was positively correlated with the respiratory distress score,oxygenation index,and chest X-ray grade(ρ=0.429–0.859,P<0.05).Receiver operating characteristic curve analysis indicated that pulmonary ultrasonography screening effectively predicted the severity of neonatal RDS(area under the curve=0.805–1.000,P<0.05).CONCLUSION The pulmonary ultrasonography score was significantly associated with the neonatal RDS score,oxygenation index,and chest X-ray grade.The pulmonary ultrasonography score was an effective predictor of neonatal RDS severity.

Retrospective analysis based on a clinical grading system for patients with hepatic hemangioma:A single center experience

BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.METHODS A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018.Patients were classified into four groups based on the clinical grading system and treatment:(1)Observation group with score<4(Obs score<4);(2)Surgical group with score<4(Sur score<4);(3)Observation group with score≥4(Obs score≥4);and(4)Surgical group with score≥4(Sur score≥4).The clinico-pathological index and outcomes were evaluated.RESULTS There were significantly fewer symptomatic patients in surgical groups(Sur score≥4 vs Obs score≥4,P<0.001;Sur score<4 vs Obs score<4,χ^(2)=8.60,P=0.004;Sur score≥4 vs Obs score<4,P<0.001).The patients in Sur score≥4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score≥4(P<0.001;P<0.001).Nevertheless,there was no significant difference in need for intervention and total patients with adverse event between the Sur score<4 and Obs score<4(P>0.05;χ^(2)=1.68,P>0.05).CONCLUSION This clinical grading system appeared as a practical tool for hepatic hemangioma.Surgery can be suggested for patients with a score≥4.For those with<4,follow-up should be proposed.

Catalyst grading technology for promoting the diesel hydrocracking to naphtha

This paper reports the application of multi-component hydrocracking catalyst grading technology in diesel hydrocracking system to increase naphtha,and studies the influence of catalyst systems with different number of graded beds on the reaction process of diesel hydrocracking.Three hydrocracking catalysts with different physicochemical properties as gradation components,the diesel hydrocracking reaction on catalyst systems of one-component,two-component and three-component graded beds with different loading sequences are carried out and evaluated,respectively.The catalytic mechanism of the multi-component grading system is analyzed.The results show that,with the increase of the number of grading beds,the space velocity of reaction on each catalyst increases,which can effectively control the overreaction process;along the flow direction of feedstock,the loading sequences of catalysts with acidity decreasing and pore properties increasing can satisfy the demand of different catalytic activity for the conversion of reactant with changing composition to naphtha,which has a guiding role in the conversion of feedstock to target products.Therefore,the conversion of diesel,the selectivity and yield of naphtha all increase significantly on the multi-component catalyst system.The research on the grading technology of multi-component catalysts is of great significance to the promotion and application of catalyst systems in various catalytic fields.

LuNet-LightGBM:An Effective Hybrid Approach for Lesion Segmentation and DR Grading

Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the DR and determine the stages,medical tests are very labor-intensive,expensive,and timeconsuming.To address the issue,a hybrid deep and machine learning techniquebased autonomous diagnostic system is provided in this paper.Our proposal is based on lesion segmentation of the fundus images based on the LuNet network.Then a Refined Attention Pyramid Network(RAPNet)is used for extracting global and local features.To increase the performance of the classifier,the unique features are selected from the extracted feature set using Aquila Optimizer(AO)algorithm.Finally,the LightGBM model is applied to classify the input image based on the severity.Several investigations have been done to analyze the performance of the proposed framework on three publically available datasets(MESSIDOR,APTOS,and IDRiD)using several performance metrics such as accuracy,precision,recall,and f1-score.The proposed classifier achieves 99.29%,99.35%,and 99.31%accuracy for these three datasets respectively.The outcomes of the experiments demonstrate that the suggested technique is effective for disease identification and reliable DR grading.

Deep learning-based automated grading of visual impairment in cataract patients using fundus images

Cataract is the leading cause of visual impairment globally.The scarcity and uneven distribution of ophthalmologists seriously hinder early visual impairment grading for cataract patients in the clin-ic.In this study,a deep learning-based automated grading system of visual impairment in cataract patients is proposed using a multi-scale efficient channel attention convolutional neural network(MECA_CNN).First,the efficient channel attention mechanism is applied in the MECA_CNN to extract multi-scale features of fundus images,which can effectively focus on lesion-related regions.Then,the asymmetric convolutional modules are embedded in the residual unit to reduce the infor-mation loss of fine-grained features in fundus images.In addition,the asymmetric loss function is applied to address the problem of a higher false-negative rate and weak generalization ability caused by the imbalanced dataset.A total of 7299 fundus images derived from two clinical centers are em-ployed to develop and evaluate the MECA_CNN for identifying mild visual impairment caused by cataract(MVICC),moderate to severe visual impairment caused by cataract(MSVICC),and nor-mal sample.The experimental results demonstrate that the MECA_CNN provides clinically meaning-ful performance for visual impairment grading in the internal test dataset:MVICC(accuracy,sensi-tivity,and specificity;91.3%,89.9%,and 92%),MSVICC(93.2%,78.5%,and 96.7%),and normal sample(98.1%,98.0%,and 98.1%).The comparable performance in the external test dataset is achieved,further verifying the effectiveness and generalizability of the MECA_CNN model.This study provides a deep learning-based practical system for the automated grading of visu-al impairment in cataract patients,facilitating the formulation of treatment strategies in a timely man-ner and improving patients’vision prognosis.

YOLO-Banana:An Effective Grading Method for Banana Appearance Quality

The increasing trend towards independent fruit packaging demands a high appearance quality of individually packed fruits.In this paper,we propose an improved YOLOv5-based model,YOLO-Banana,to effectively grade banana appearance quality based on the number of banana defect points.Due to the minor and dense defects on the surface of bananas,existing detection algorithms have poor detection results and high missing rates.To address this,we propose a densitybased spatial clustering of applications with noise(DBSCAN)and K-means fusion clustering method that utilizes refined anchor points to obtain better initial anchor values,thereby enhancing the network’s recognition accuracy.Moreover,the optimized progressive aggregated network(PANet)enables better multi-level feature fusion.Additionally,the non-maximum suppression function is replaced with a weighted non-maximum suppression(weighted NMS)function based on distance intersection over union(DIoU).Experimental results show that the model’s accuracy is improved by 2.3%compared to the original YOLOv5 network model,thereby effectively grading the banana appearance quality.

An Automatic Classification Grading of Spinach Seedlings Water Stress Based on N-MobileNetXt

To solve inefficient water stress classification of spinach seedlings under complex background,this study proposed an automatic classification method for the water stress level of spinach seedlings based on the N-MobileNetXt(NCAM+MobileNetXt)network.Firstly,this study recon-structed the Sandglass Block to effectively increase the model accuracy;secondly,this study introduced the group convolution module and a two-dimensional adaptive average pool,which can significantly compress the model parameters and enhance the model robustness separately;finally,this study innovatively proposed the Normalization-based Channel Attention Module(NCAM)to enhance the image features obviously.The experimental results showed that the classification accuracy of N-MobileNetXt model for spinach seedlings under the natural environment reached 90.35%,and the number of parameters was decreased by 66%compared with the original MobileNetXt model.The N-MobileNetXt model was superior to other net-work models such as ShuffleNet and GhostNet in terms of parameters and accuracy of identification.It can provide a theoretical basis and technical support for automatic irrigation.

乌梅丸及加减方治疗大肠疾病的系统评价再评价

[目的]评价乌梅丸及加减方治疗大肠疾病的相关系统评价(SRs),为临床提供循证医学依据。[方法]计算机检索PubMed、Cochrane Library、Embase、中国期刊全文数据库(CNKI)、维普中文期刊数据库(VIP)、万方数据知识服务平台(WanFang Data)和中国生物医学文献数据库(CBM),搜集乌梅丸及加减方治疗大肠疾病的SRs,检索时限为建库至2022年12月31日。两名研究者独立筛选文献、提取资料,分别采用AMSTAR 2、PRISMA 2020和GRADE评价纳入研究的方法学质量、报告质量及证据质量,并对结果进行综合分析。[结果]共纳入12篇SRs,涉及4种疾病,有溃疡性结肠炎(UC)、肠易激综合征(IBS)、泄泻和大肠腺瘤性息肉术后。AMSTAR 2评价结果显示,10篇SRs为低质量,2篇SRs为极低质量;PRISMA 2020评分为19.5~30分,其中6篇SRs为中质量,6篇SRs为低质量。纳入SRs共报告了51个结局指标,GRADE评价结果为30个中质量,19个低质量,2个极低质量。现有证据显示,与常规治疗、空白对照/安慰剂相比,乌梅丸及加减方或联合常规治疗治疗UC、IBS、泄泻和大肠腺瘤性息肉术后的疗效更佳。[结论]乌梅丸及加减方治疗大肠疾病具有较好的疗效,鉴于所纳入研究的样本量及疾病种类较少,其方法学质量、报告质量和证据质量相对较低,应慎重对待该结论,期待今后开展更多高质量研究证实。

热敏灸治疗颈型颈椎病的Meta分析及GRADE证据等级评价

目的系统评价热敏灸及其综合疗法用于颈型颈椎病的临床效果,为热敏灸治疗颈型颈椎病提供更好的证据来源。方法收集国内外各大数据库热敏灸及其综合疗法用于颈型颈椎病的随机对照试验(RCT),通过Revman 5.3软件进行Meta分析,按照GRADE标准对结局指标进行证据质量评价。结果纳入9篇文献共855例患者,Meta分析结果提示:热敏灸及其综合疗法组在提高总有效率(RR=1.19,P<0.01)和治愈率(RR=1.73,P<0.01)、降低视觉模拟量表(VAS)评分(SMD=-0.73,P<0.01)、简化McGill疼痛问卷(SF-MPQ)评分(SMD=-1.28,P<0.05)以及NPQ颈痛量表评分(SMD=-0.81,P<0.05)方面都优于对照组;GRADE证据等级评价提示:前三者为低质量证据,后二者为极低质量证据。结论热敏灸及其综合疗法用于颈型颈椎病在提高临床效果、镇痛以及改善患者生活质量方面更具优势。

移动医疗管理高血压患者服药依从性效果的系统评价再评价

目的研究表明,移动医疗护理能使高血压患者在降低心血管风险等方面受益,目前已有较多关于移动医疗管理高血压患者服药依从性效果的系统评价/Meta分析,但其方法学质量和证据强度有待进一步系统性评估。因此,本研究对移动医疗干预高血压患者服药依从性效果的系统评价进行再评价,为临床决策提供指导。方法计算机检索中国知网、万方、维普、中国生物医学文献数据库、PubMed、Web of Science、CINAHL、EMbase、the Cochrane Library、澳大利亚乔安娜布里格斯研究所(Joanna Briggs Institute,JBI)循证卫生保健中心数据库,收集关于移动医疗管理高血压患者服药依从性相关的系统评价/Meta分析。检索时限为建库至2023年1月31日。由2名研究者独立进行文献筛选、资料提取,并评价文献质量与证据分级。结果共纳入11篇系统评价/Meta分析,方法学质量评价结果显示1篇文献质量中等,2篇为低级,8篇为极低。采用GRADE评价结果显示定量分析中23项指标包括中级证据9项,低级证据5项,极低级证据9项。结论移动医疗技术在改善高血压管理中发挥积极作用,但相关系统评价/Meta分析方法学质量与结局指标证据等级普遍不高。未来进行相关临床决策时,需要具体问题具体分析;同时研究人员应提供更多设计严谨、报告规范的系统评价,作为高质量证据帮助临床决策。

正确理解和应用低质量证据形成指南推荐意见

推荐意见是临床实践指南的核心。基于低质量证据作出强推荐意见是当前国内外指南普遍存在的现象。医务人员认为缺乏高质量的证据就无法制订高质量的指南或仅可制订专家共识是典型的误解。本文以GRADE分级系统为切入点,阐述低质量证据的基本内涵和临床作用,介绍基于低质量证据形成指南推荐意见的方法,以期为我国指南制订者和使用者提供参考。

刮痧改善腰椎间盘突出疼痛症状的系统评价及GRADE证据质量评价

目的系统评价刮痧干预腰椎间盘突出疼痛症状的疗效与安全性,为其临床治疗提供循证依据。方法计算机检索自建库到2022年8月29日前公开发表在中国知网、万方、维普、中国生物医学文献服务系统、PubMed、Embase、Web of Science、The Cochrane Library数据库,收集关于刮痧干预腰椎间盘突出的随机对照试验(Randomized controlled trial,RCT)。文章由两名研究者独立筛选,根据Cochrane Reviewers Handbook 6.2的偏倚风险评估工具对纳入文献进行质量评价,应用RevMan 5.4软件对纳入文献的结局指标进行Meta分析,并采用GRADE系统对结局指标进行证据质量等级评价。结果最终纳入10篇RCT,共1087例患者。Meta分析结果显示:刮痧试验组治疗腰椎间盘突出患者在疼痛VAS评分[MD=-1.11,95%CI(-1.58,-0.64),P<0.00001]、日本骨科协会(JOA)评分[MD=4.47,95%CI(3.76,5.17),P<0.00001]、临床有效率[relative risk(RR)=1.13,95%CI(1.08,1.19),P<0.00001]和护理满意度[RR=1.21,95%CI(1.09,1.34),P=0.0005]方面,明显优于对照组,差异均有统计学意义(P<0.00001)。本文结局指标的证据质量为极低。结论当前证据表明,刮痧治疗腰椎间盘突出患者的疼痛症状具有良好临床疗效,并有助于提高临床护理满意度。由于部分结局证据质量较低,有待严谨的多中心、大样本随机对照试验来进一步验证其有效性,提升临床证据。

复方金钱草颗粒临床应用专家共识

复方金钱草颗粒为国家医保目录乙类中成药,在临床上广泛应用于泌尿系结石和尿路感染,经过长期的临床治疗经验,基于问卷调查、专家访谈及研究文献系统分析的基础上,认为复方金钱草颗粒对泌尿系结石和尿路感染疾病有良好的临床疗效,为指南推荐用药。本共识严格遵循中成药临床应用专家共识步骤进行研制,针对泌尿系结石和尿路感染的治疗而制定;采用调查问卷的形式,调查有临床经验的医生,通过对循证医学证据进行综合分析,并采用名义组法原则,汇总分析结果为24条推荐意见和共识建议。进一步明确复方金钱草颗粒治疗泌尿系结石和尿路感染的适应症、用法用药、疗程、介入时间、联合用药等,说明了临床应用的安全性,并分别进行30以上的专家组进行了征求意见和同行评议。本共识旨在指导临床正确使用复方金钱草颗粒治疗泌尿系结石和尿路感染。

The Identification and Assessment on Genetic Characteristics in Grading Breeding Sheep Populations with Microsatellite Markers

[Objective] The aim of the research was to identify and assess the genetic characteristics of grading breeding sheep populations in Ba Yan Nur City. [Method] Genetic polymorphism and aggregation of seven sheep populations, including three breeding sheep populations (breeding F1, F2 and Bamei mutton sheep), three introduced mutton sheep breeds (Texel, Dorset and German Merino sheep) and one local female parent population (Mongolia sheep), were assessed using 10 microsatellite markers. [Result] By cluster analysis, the seven sheep populations can be divided into two groups. The F1 and German Merino sheep were closely related, which were clustered with F2, Bamei mutton sheep and Mongolia sheep to form one group while Texel and Dorset to form another group. The genetic aggregation of the seven breeds was assessed by Bayesian discrimination. And the results show that the genetic aggregation of F1 and F2 were lower while that of Bamei mutton sheep, Texel, Dorset and German Merino sheep were higher. [Conclusion] Better genetic stability has been formed in Bamei mutton sheep.

《中成药治疗优势病种临床应用指南》少数基于低质量证据的强推荐现状及其合理性分析

目的分析中成药治疗优势病种临床应用指南中对低质量证据给予强推荐的现状并探讨其推荐意见的合理性。方法指南选择:纳入国家中医药管理局立项、中国中药协会承担的“中成药治疗优势病种临床应用指南”项目(项目标号SATCM-2015-BZ402)于2019年2月至2022年8月公开发表的29部指南。数据提取:由2名研究人员独立提取资料,提取内容包括:推荐意见类型(共识意见或循证意见)、制订推荐意见的分级系统、推荐强度和证据质量。结果本研究共纳入29部指南,所有的指南均采用GRADE方法进行证据质量评价及推荐强度评级。在纳入的262条推荐意见中,低/极低证据质量强推荐的条目共计27条(10.3%),仅6.8%(2/29)的指南低/极低质量强推荐条目超过总推荐意见条目的50%。无循证证据支持、依据专家共识法达成的推荐条目共计36条(13.7%)。结论中成药循证指南的制定应遵循证据质量与推荐强度的一致性和合理性的循证基本原则。基于古籍文献和专家经验的推荐意见应有令人信服的理由,以增强中成药循证指南的可信赖性。

Variation and Probability Grading of Fruit Firmness in Peach Germplasm Resource

Objective The aim was to provide basis for further studies on fruit firmness in peach fruits and the standardization and standardization of peach germplasm resource. [ Method] The analysis of fruit firmness of peach germplasm resource was based on the improved firmness measurement, and the probability grading of characteristics was carried out on peach fruit firmness. [Result] The coefficient of variation of peach fruit firmness with skin was less than that of fruit firmness without skin; the fruit firmness with skin and fruit firmness without skin were both fitted the normal distribution; the probability grading of characteristics were divided into five series based on four points of （X-1. 281 8s）, （X-0. 524 6s）, （X＋0. 524 6s） and （X＋1.281 8s）, so that the probability of 1 -5 were 10%, 20%, 40%, 20% and 10%. [Conclusion] There was more abundant genetic basis in fruit firmness, which held a potential for greater choice.

穴位埋线治疗功能性便秘疗效与安全性Meta分析及GRADE评价

目的:系统评价穴位埋线治疗功能性便秘(FC)的疗效和安全性及纳入证据的质量,以期为临床决策提供循证医学证据。方法:检索中国知网(CNKI)、万方知识服务平台(WANFANG)、维普中文期刊数据库(VIP)、中国生物医学文献服务系统(SinoMed)、Embase、PubMed和Cochrane Library数据库,搜集穴位埋线治疗FC的随机对照试验(RCT),检索时间均从建库至2023年10月16日。由2名研究者独立完成文献筛选、资料提取及偏倚风险评估,采用RevMan 5.4软件进行Meta分析,并采用GRADE评价方法对各项结局指标进行证据质量评价。结果:最终共纳入19项RCT,包括1673例患者。Meta分析结果显示,与对照组比较,穴位埋线治疗FC可提高总有效率[RR=1.23,95%CI=(1.17,1.29),P<0.00001],增加完全自发排便(CSBM)次数[MD=0.61,95%CI=(0.11,1.10),P=0.02],改善粪便性状[MD=0.53,95%CI=(0.31,0.76),P<0.00001]及排便困难[MD=-0.71,95%CI=(-1.03,-0.40),P<0.00001],缩短排便时间[MD=-0.50,95%CI=(-0.72,-0.29),P<0.00001],改善便秘生活质量评估量表(PAC-QOL)评分[MD=-7.72,95%CI=(-12.83,-2.61),P<0.003];两组不良反应发生率比较,差异无统计学意义[RR=0.37,95%CI=(0.10,1.38),P=0.14]。GRADE证据级别评价结果显示:总有效率为中级别证据质量,不良反应发生率、粪便性状评分、排便困难评分为低级别证据质量,CSBM次数、排便时间、PACQOL评分为极低级别证据质量。结论:穴位埋线治疗FC具有一定的疗效,可改善便秘相关症状,且未增加不良反应发生率。但纳入研究质量总体偏低,上述结论尚需开展更多高质量的研究予以验证。

腕踝针干预术后疼痛疗效的Meta分析和Grade评价

目的运用循证医学方法对腕踝针干预术后疼痛的疗效和安全性进行系统评价和Grade评价。方法计算机检索中国知网、万方、维普、中国生物医学文献数据库、PubMed、Embase、Web of Science、Cochrane Library中关于腕踝针干预术后疼痛的随机对照试验,检索时限为建库至2023年10月。采用RevMan 5.4软件进行Meta分析。结果纳入23篇文献,共计1968例患者,Meta分析结果显示,与常规治疗相比,腕踝针能够提高术后疼痛患者的总有效率[OR=4.42,95%CI(2.60,7.50),P<0.001],术后镇痛泵药量使用减少[MD=-9.03,95%CI(-12.09,-5.98),P<0.001],术后疼痛评分降低[MD=-1.39,95%CI(-1.68,-1.09),P<0.001],可减少不良反应发生率[RR=0.40,95%CI(0.32,0.48),P<0.001]以及临床满意度[OR=3.94,95%CI(2.40,6.48),P<0.001]。Grade证据分级结果显示:总有效率、不良反应发生率和临床满意度3项结局指标为中等质量证据,VAS评分指标为低质量证据,镇痛泵药量使用指标为极低质量证据。结论腕踝针可提高总有效率,减少术后镇痛药用量,不良反应少,安全性高,为患者提供了一种安全有效的镇痛方式。

乌梅丸加减治疗帕金森病的Meta分析及GRADE评价

目的 系统评估乌梅丸加减治疗帕金森病(parkinson's disease, PD)的疗效和安全性。方法 计算机检索Cochrane Library、EMBASE、Web of Science、PubMed、CNKI、CBM等中英文数据库及临床试验中心,关于乌梅丸治疗PD的临床随机对照试验(randomized controlled trial, RCT),检索时限从建库至2023年4月。进行资料整理及数据提取等工作后,最终纳入8项研究,治疗组(乌梅丸)和对照组分别纳入226例。使用RevMan 5.3及stata14软件进行荟萃分析,使用GRADEpro GDT评估各项结局指标的证据质量。结果 治疗组降低PD统一评分量表(unified Parkinson's disease rating scale, UPDRS)的各项量表积分较对照组明显,其中在改善UPDRS Ⅰ、Ⅲ、Ⅳ方面具有统计学意义,结果分别为[MD=-0.769,95%CI(-1.213~-0.324),P=0.001]、[MD=-2.211,95%CI(-2.713~-1.708),P=0]、[MD=-0.526,95%CI(-1.041~-0.012),P=0.045]。2组在改善UPDRS总分方面差异无统计学意义[MD=3.964,95%CI(-9.465~17.392),P=0.563]。治疗组能显著提高治疗有效率,差异具有统计学意义[RR=1.709,95%CI(1.361~2.145),P=0]。各项研究均未发现不良事件发生及与治疗有关的检验指标异常。GRADE证据质量分级结果为UPDRS Ⅰ、UPDRS Ⅲ、UPDRS Ⅳ及有效率方面均为中等级别,UPDRS Ⅱ为低等级,UPDRS总分为非常低。结论 乌梅丸加减的应用对PD的治疗有一定效果,且具有良好的安全性。