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Errata regarding missing Ethical Statements in previously published articles:Part 2
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《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期736-736,共1页
Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are inc... Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are included below. 展开更多
关键词 statements ETHICAL missING
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Errata regarding missing Ethical Statements in previously published articles:Part 5
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《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期739-739,共1页
Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are inc... Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are included below. 展开更多
关键词 statements ETHICAL missING
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Errata regarding missing Ethical Statements in previously published articles:Part 3
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《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期737-737,共1页
Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are inc... Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are included below. 展开更多
关键词 statements ETHICAL missING
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Errata regarding missing Ethical Statements in previously published articles:Part 1
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《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期735-735,共1页
Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are inc... Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are included below. 展开更多
关键词 statements ETHICAL missING
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Errata regarding missing Ethical Statements in previously published articles:Part 4
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《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期738-738,共1页
Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are inc... Ethical statements were not included in the published version of the following articles that appeared in previous issues of Journal of Integrative Agriculture.The appropriate statements provided by the Authors are included below. 展开更多
关键词 statements ETHICAL missING
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A Practical Approach for Missing Wireless Sensor Networks Data Recovery
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作者 Song Xiaoxiang Guo Yan +1 位作者 Li Ning Ren Bing 《China Communications》 SCIE CSCD 2024年第5期202-217,共16页
In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data collected.Unfortunately,missing data is almost inevitable in the process of data acquisition and tra... In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data collected.Unfortunately,missing data is almost inevitable in the process of data acquisition and transmission.Existing methods often rely on prior information such as low-rank characteristics or spatiotemporal correlation when recovering missing WSNs data.However,in realistic application scenarios,it is very difficult to obtain these prior information from incomplete data sets.Therefore,we aim to recover the missing WSNs data effectively while getting rid of the perplexity of prior information.By designing the corresponding measurement matrix that can capture the position of missing data and sparse representation matrix,a compressive sensing(CS)based missing data recovery model is established.Then,we design a comparison standard to select the best sparse representation basis and introduce average cross-correlation to examine the rationality of the established model.Furthermore,an improved fast matching pursuit algorithm is proposed to solve the model.Simulation results show that the proposed method can effectively recover the missing WSNs data. 展开更多
关键词 average cross correlation matching pursuit missing data wireless sensor networks
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Optimal Estimation of High-Dimensional Covariance Matrices with Missing and Noisy Data
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作者 Meiyin Wang Wanzhou Ye 《Advances in Pure Mathematics》 2024年第4期214-227,共14页
The estimation of covariance matrices is very important in many fields, such as statistics. In real applications, data are frequently influenced by high dimensions and noise. However, most relevant studies are based o... The estimation of covariance matrices is very important in many fields, such as statistics. In real applications, data are frequently influenced by high dimensions and noise. However, most relevant studies are based on complete data. This paper studies the optimal estimation of high-dimensional covariance matrices based on missing and noisy sample under the norm. First, the model with sub-Gaussian additive noise is presented. The generalized sample covariance is then modified to define a hard thresholding estimator , and the minimax upper bound is derived. After that, the minimax lower bound is derived, and it is concluded that the estimator presented in this article is rate-optimal. Finally, numerical simulation analysis is performed. The result shows that for missing samples with sub-Gaussian noise, if the true covariance matrix is sparse, the hard thresholding estimator outperforms the traditional estimate method. 展开更多
关键词 High-Dimensional Covariance Matrix missing Data Sub-Gaussian Noise Optimal Estimation
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Missing Value Imputation for Radar-Derived Time-Series Tracks of Aerial Targets Based on Improved Self-Attention-Based Network
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作者 Zihao Song Yan Zhou +2 位作者 Wei Cheng Futai Liang Chenhao Zhang 《Computers, Materials & Continua》 SCIE EI 2024年第3期3349-3376,共28页
The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random mis... The frequent missing values in radar-derived time-series tracks of aerial targets(RTT-AT)lead to significant challenges in subsequent data-driven tasks.However,the majority of imputation research focuses on random missing(RM)that differs significantly from common missing patterns of RTT-AT.The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation.Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss.In this paper,a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed.Our model consists of two probabilistic sparse diagonal masking self-attention(PSDMSA)units and a weight fusion unit.It learns missing values by combining the representations outputted by the two units,aiming to minimize the difference between the missing values and their actual values.The PSDMSA units effectively capture temporal dependencies and attribute correlations between time steps,improving imputation quality.The weight fusion unit automatically updates the weights of the output representations from the two units to obtain a more accurate final representation.The experimental results indicate that,despite varying missing rates in the two missing patterns,our model consistently outperforms other methods in imputation performance and exhibits a low frequency of deviations in estimates for specific missing entries.Compared to the state-of-the-art autoregressive deep learning imputation model Bidirectional Recurrent Imputation for Time Series(BRITS),our proposed model reduces mean absolute error(MAE)by 31%~50%.Additionally,the model attains a training speed that is 4 to 8 times faster when compared to both BRITS and a standard Transformer model when trained on the same dataset.Finally,the findings from the ablation experiments demonstrate that the PSDMSA,the weight fusion unit,cascade network design,and imputation loss enhance imputation performance and confirm the efficacy of our design. 展开更多
关键词 missing value imputation time-series tracks probabilistic sparsity diagonal masking self-attention weight fusion
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Cross Validation Based Model Averaging for Varying-Coefficient Models with Response Missing at Random
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作者 Huixin Li Xiuli Wang 《Journal of Applied Mathematics and Physics》 2024年第3期764-777,共14页
In this paper, a model averaging method is proposed for varying-coefficient models with response missing at random by establishing a weight selection criterion based on cross-validation. Under certain regularity condi... In this paper, a model averaging method is proposed for varying-coefficient models with response missing at random by establishing a weight selection criterion based on cross-validation. Under certain regularity conditions, it is proved that the proposed method is asymptotically optimal in the sense of achieving the minimum squared error. 展开更多
关键词 Response missing at Random Model Averaging Asymptotic Optimality B-Spline Approximation
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Comparison of two statistical methods for handling missing values of quantitative data in Bayesian N-of-1 trials: a simulation study
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作者 Jing-Bo Zhai Tian-Ci Guo Wei-Jie Yu 《Medical Data Mining》 2024年第1期10-15,共6页
Background:Missing data are frequently occurred in clinical studies.Due to the development of precision medicine,there is an increased interest in N-of-1 trial.Bayesian models are one of main statistical methods for a... Background:Missing data are frequently occurred in clinical studies.Due to the development of precision medicine,there is an increased interest in N-of-1 trial.Bayesian models are one of main statistical methods for analyzing the data of N-of-1 trials.This simulation study aimed to compare two statistical methods for handling missing values of quantitative data in Bayesian N-of-1 trials.Methods:The simulated data of N-of-1 trials with different coefficients of autocorrelation,effect sizes and missing ratios are obtained by SAS 9.1 system.The missing values are filled with mean filling and regression filling respectively in the condition of different coefficients of autocorrelation,effect sizes and missing ratios by SPSS 25.0 software.Bayesian models are built to estimate the posterior means by Winbugs 14 software.Results:When the missing ratio is relatively small,e.g.5%,missing values have relatively little effect on the results.Therapeutic effects may be underestimated when the coefficient of autocorrelation increases and no filling is used.However,it may be overestimated when mean or regression filling is used,and the results after mean filling are closer to the actual effect than regression filling.In the case of moderate missing ratio,the estimated effect after mean filling is closer to the actual effect compared to regression filling.When a large missing ratio(20%)occurs,data missing can lead to significantly underestimate the effect.In this case,the estimated effect after regression filling is closer to the actual effect compared to mean filling.Conclusion:Data missing can affect the estimated therapeutic effects using Bayesian models in N-of-1 trials.The present study suggests that mean filling can be used under situation of missing ratio≤10%.Otherwise,regression filling may be preferable. 展开更多
关键词 N-of-1 trial BAYESIAN missing data simulation study
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Efficient and robust missing key tag identification for large-scale RFID systems
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作者 Chu Chu Guangjun Wen Jianyu Niu 《Digital Communications and Networks》 SCIE CSCD 2023年第6期1421-1433,共13页
Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize t... Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions. 展开更多
关键词 RFID missing key tag identification Time efficiency ROBUST
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Ultra-High Dimensional Feature Selection and Mean Estimation under Missing at Random
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作者 Wanhui Li Guangming Deng Dong Pan 《Open Journal of Statistics》 2023年第6期850-871,共22页
Next Generation Sequencing (NGS) provides an effective basis for estimating the survival time of cancer patients, but it also poses the problem of high data dimensionality, in addition to the fact that some patients d... Next Generation Sequencing (NGS) provides an effective basis for estimating the survival time of cancer patients, but it also poses the problem of high data dimensionality, in addition to the fact that some patients drop out of the study, making the data missing, so a method for estimating the mean of the response variable with missing values for the ultra-high dimensional datasets is needed. In this paper, we propose a two-stage ultra-high dimensional variable screening method, RF-SIS, based on random forest regression, which effectively solves the problem of estimating missing values due to excessive data dimension. After the dimension reduction process by applying RF-SIS, mean interpolation is executed on the missing responses. The results of the simulated data show that compared with the estimation method of directly deleting missing observations, the estimation results of RF-SIS-MI have significant advantages in terms of the proportion of intervals covered, the average length of intervals, and the average absolute deviation. 展开更多
关键词 Ultrahigh-Dimensional Data missing Data Sure Independent Screening Mean Estimation
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Missing Value Imputation Model Based on Adversarial Autoencoder Using Spatiotemporal Feature Extraction
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作者 Dong-Hoon Shin Seo-El Lee +1 位作者 Byeong-Uk Jeon Kyungyong Chung 《Intelligent Automation & Soft Computing》 SCIE 2023年第8期1925-1940,共16页
Recently,the importance of data analysis has increased significantly due to the rapid data increase.In particular,vehicle communication data,considered a significant challenge in Intelligent Transportation Systems(ITS... Recently,the importance of data analysis has increased significantly due to the rapid data increase.In particular,vehicle communication data,considered a significant challenge in Intelligent Transportation Systems(ITS),has spatiotemporal characteristics and many missing values.High missing values in data lead to the decreased predictive performance of models.Existing missing value imputation models ignore the topology of transportation net-works due to the structural connection of road networks,although physical distances are close in spatiotemporal image data.Additionally,the learning process of missing value imputation models requires complete data,but there are limitations in securing complete vehicle communication data.This study proposes a missing value imputation model based on adversarial autoencoder using spatiotemporal feature extraction to address these issues.The proposed method replaces missing values by reflecting spatiotemporal characteristics of transportation data using temporal convolution and spatial convolution.Experimental results show that the proposed model has the lowest error rate of 5.92%,demonstrating excellent predictive accuracy.Through this,it is possible to solve the data sparsity problem and improve traffic safety by showing superior predictive performance. 展开更多
关键词 missing value adversarial autoencoder spatiotemporal feature extraction
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Missed Opportunities for Diagnosing Bacilliferous Pulmonary Tuberculosis by Optical Microscopy versus GeneXpert MTB/RIF in Endemic Areas
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作者 Aba Yapo Thomas Nassoué Dobré Olivia +3 位作者 Yéo Liomehin Monemo Pacome Yapo Matine Tatiana Achi Hoboueu Vincent 《Advances in Infectious Diseases》 2023年第4期652-659,共8页
Objective: To assess the missed opportunities from the diagnosis of bacilliferous pulmonary tuberculosis by optical microscopy compared to GeneXpert MTB/RIF between 2015 and 2019. Methods: This is a retrospective anal... Objective: To assess the missed opportunities from the diagnosis of bacilliferous pulmonary tuberculosis by optical microscopy compared to GeneXpert MTB/RIF between 2015 and 2019. Methods: This is a retrospective analysis of the diagnostic results of bacilliferous pulmonary tuberculosis in patients suspected of pulmonary tuberculosis at their first episode during the period. GeneXpert MTB/RIF (GeneXpert) and optical microscopy (OM) after Ziehl-Neelsen stained smear were performed on each patient’s sputum or gastric tubing fluid sample. Results: Among 341 patients suspected of pulmonary tuberculosis, 229 patients were declared bacilliferous tuberculosis by the two tests (67%), 220 patients by GeneXpert and 95 patients by OM, i.e. 64.5% versus 28% (p i.e. 58.5% of the positive cases detected by the two tests (134/229 patients) and 39.3% of the patients suspected of tuberculosis (134/341 patients). On the other hand, among 95 patients declared positive by OM, the GeneXpert ignored 9 (9.5%), i.e. 4% of all the positive cases detected by the two diagnostic tests (9/229 patients) and 3% of the patients suspected of tuberculosis (9/341 patients). The differences observed between the results of the two tests were statistically significant at the 5% threshold (p Conclusion: This study reveals missed diagnostic opportunities for bacilliferous pulmonary mycobacteriosis, statistically significant with optical microscopy than GeneXpert. The GeneXpert/optical microscopy couple could be a good contribution to the strategies for the elimination of pulmonary tuberculosis in sub-Saharan Africa. 展开更多
关键词 Bacilliferous Pulmonary Tuberculosis missed Opportunity GeneXpert MTB/RIF Optical Microscopy
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Smoothed Empirical Likelihood Inference for Nonlinear Quantile Regression Models with Missing Response
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作者 Honghua Dong Xiuli Wang 《Open Journal of Applied Sciences》 2023年第6期921-933,共13页
In this paper, three smoothed empirical log-likelihood ratio functions for the parameters of nonlinear models with missing response are suggested. Under some regular conditions, the corresponding Wilks phenomena are o... In this paper, three smoothed empirical log-likelihood ratio functions for the parameters of nonlinear models with missing response are suggested. Under some regular conditions, the corresponding Wilks phenomena are obtained and the confidence regions for the parameter can be constructed easily. 展开更多
关键词 Nonlinear Model Quantile Regression Smoothed Empirical Likelihood missing at Random
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蔬菜穴盘育苗播种漏播检测及智能补种装置设计与试验 被引量:1
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作者 马旭 杨传艺 +5 位作者 谭穗妍 曹秀龙 秦亦娟 陈嘉盈 余杰 王曦成 《农业工程学报》 EI CAS CSCD 北大核心 2024年第6期168-180,共13页
为保证植物工厂蔬菜穴盘育苗高质量作业要求,该研究在气吸滚筒式蔬菜穴盘育苗精密播种器的基础上,优化设计了在线漏播检测与智能补种装置,以可编程逻辑控制器(programmable logic controller,PLC)为控制核心,实时进行播种器吸孔漏吸检... 为保证植物工厂蔬菜穴盘育苗高质量作业要求,该研究在气吸滚筒式蔬菜穴盘育苗精密播种器的基础上,优化设计了在线漏播检测与智能补种装置,以可编程逻辑控制器(programmable logic controller,PLC)为控制核心,实时进行播种器吸孔漏吸检测及穴盘穴孔漏播位置预报,并完成漏播穴孔的定点定穴补种。采用光电检测技术检测播种器吸孔漏吸位置,构建漏吸吸孔与育苗穴盘穴孔的对应动态补种矩阵,实现穴盘穴孔漏播位置精准预报;优化设计了智能补种装置,根据预报的穴盘穴孔漏播位置实现定点定穴精准补种。以中双11号菜心种子为对象,开展播种器吸孔漏吸检测与穴孔漏播位置预报试验,得到吸孔漏吸平均检测准确率为98.82%,穴孔漏播位置预报准确率为100%。采用BoxBehnken试验设计方法,对智能补种装置开展作业性能试验,构建主要性能指标(单粒合格指数、重播指数和漏播指数)与主要影响因素(吸针负压、吸针孔径和种室振动压力)的关系,并进行多目标优化,确定智能补种装置最优工作参数组合为吸针负压10.19 kPa、吸针孔径0.67 mm、种室振动压力0.07 MPa,此时补种装置播种的平均单粒合格指数为94.80%、重播指数为2.94%、漏播指数为2.26%。开展整机性能试验,在生产率为100盘/h条件下,整机的单粒合格指数由补种前的93.96%提高到98.18%;在生产率为300盘/h条件下,单粒合格指数由补种前的93.18%提高到97.89%。试验结果满足植物工厂和大田蔬菜穴盘育苗播种装置高精密播种作业要求,可提高蔬菜穴盘育苗的播种性能。 展开更多
关键词 农业机械 自动化 蔬菜穴盘育苗 漏播检测 补种
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普通话特殊型语言障碍儿童辖域指派的研究 被引量:1
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作者 何晓炜 邢雪明 《山东外语教学》 北大核心 2024年第3期45-58,共14页
有关正常儿童辖域指派的研究已取得不少成果,但到目前为止尚无研究关注特殊型语言障碍(SLI)儿童的辖域知识。本研究采用真值判断任务考察学龄前普通话SLI儿童处理全称量词和否定词的辖域关系的能力。结果表明,与正常发展儿童不同,SLI儿... 有关正常儿童辖域指派的研究已取得不少成果,但到目前为止尚无研究关注特殊型语言障碍(SLI)儿童的辖域知识。本研究采用真值判断任务考察学龄前普通话SLI儿童处理全称量词和否定词的辖域关系的能力。结果表明,与正常发展儿童不同,SLI儿童偏好全部否定解读,全称量词和否定词在句子表层结构的位置关系并不会对SLI儿童的辖域指派产生明显影响。本研究验证了“语义子集原则”同样适用于SLI儿童,并提出SLI儿童在句子层面也存在“部分量化缺失”的问题。研究发现可为普通话SLI儿童的鉴定和干预提供重要参考。 展开更多
关键词 特殊型语言障碍 辖域 语义子集原则 部分量化缺失
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术前雌激素、孕激素水平与稽留流产清宫术后宫腔粘连发生的关系及其预测价值
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作者 王军 宋晓霞 +5 位作者 王佳佳 张占薪 苏倩倩 张博慧 吴启文 郭伟平 《检验医学与临床》 CAS 2024年第2期174-177,182,共5页
目的探讨雌激素、孕激素水平与稽留流产(MA)患者清宫术后发生宫腔粘连(IUA)的关系及其预测价值。方法选取2019年1月至2022年1月在该院妇科就诊行清宫术的128例MA患者作为研究对象,根据术后6个月内宫腔检查情况分为未发生IUA组(MA组,97例... 目的探讨雌激素、孕激素水平与稽留流产(MA)患者清宫术后发生宫腔粘连(IUA)的关系及其预测价值。方法选取2019年1月至2022年1月在该院妇科就诊行清宫术的128例MA患者作为研究对象,根据术后6个月内宫腔检查情况分为未发生IUA组(MA组,97例)和IUA组(31例),并根据严重程度将IUA组分为轻、中和重度IUA组。比较IUA组和MA组,以及不同严重程度IUA组术前雌二醇(E 2)和孕酮(P)水平,采用多因素Logistic回归分析发生IUA的独立影响因素;分析E 2、P与IUA病情的相关性,采用受试者工作特征(ROC)曲线分析E 2、P水平对发生IUA及其病情严重程度的预测价值。结果IUA组E 2、P水平均明显低于MA组,差异均有统计学意义(P<0.05);多因素Logistic回归分析结果显示,E 2为MA清宫术后发生IUA的独立影响因素(P<0.05);术前E 2和P水平预测MA清宫术后发生IUA的曲线下面积分别为0.714和0.702。重度IUA组E 2、P水平均明显低于轻、中度IUA组,差异均有统计学意义(P<0.05),且E 2、P水平与IUA严重程度均呈负相关(P<0.05);术前E 2、P水平预测IUA轻/中度和重度的曲线下面积分别为0.845和0.923。结论E 2、P水平与MA清宫术后IUA的发生及严重程度均相关,对临床预测MA清宫术后IUA的发生及病情进展具有一定的参考价值。 展开更多
关键词 稽留流产 清宫术 宫腔粘连 雌激素 孕激素
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儿科护理缺失量表的汉化及信效度检验
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作者 陈晨 吴艳芳 +3 位作者 王亚喜 张玲慧 许文丽 庞旭峰 《中国卫生质量管理》 2024年第9期62-67,共6页
目的对意大利儿科护理缺失量表(MISSCARE Survey-Pediatric Version)进行汉化,并检验信效度。方法采用Brislin翻译模型对原量表进行翻译,并通过文化调适和预调查进行修订,形成中文版儿科护理缺失量表。采用便利抽样法选取青岛市4家三级... 目的对意大利儿科护理缺失量表(MISSCARE Survey-Pediatric Version)进行汉化,并检验信效度。方法采用Brislin翻译模型对原量表进行翻译,并通过文化调适和预调查进行修订,形成中文版儿科护理缺失量表。采用便利抽样法选取青岛市4家三级甲等医院367名儿科护士进行量表信效度检验。结果中文版儿科护理缺失量表包括两个分量表。分量表A为单维度量表,共28个条目,Cronbach'sα系数为0.944,内容效度指数为0.971。分量表B包括3个维度共17个条目,总Cronbach'sα系数为0.888,重测信度为0.849,内容效度指数为0.984,探索性因子分析共提取3个公因子,累计方差贡献率为60.966%。结论中文版儿科护理缺失量表具有良好的信度和效度,可作为我国儿科护理缺失现状及原因的评估工具。 展开更多
关键词 儿科 护理缺失 量表 汉化 信度 效度 护理质量
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北京市海淀区危重孕产妇救治网络运行现况分析
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作者 邵瑜 梁英智 +4 位作者 杨雪梅 李丹丹 石蕊 孟超 蒋红清 《中国计划生育学杂志》 2024年第5期1201-1206,共6页
目的:探讨北京市海淀区危重孕产妇救治网络建设及运行现状。方法:对北京市海淀区危重孕产妇救治中心2020-2022年填报的《海淀区危重孕产妇转会诊指定医院接诊高危孕产妇和危重孕产妇个案登记表》等报表进行汇总分析。结果:2020-2022年... 目的:探讨北京市海淀区危重孕产妇救治网络建设及运行现状。方法:对北京市海淀区危重孕产妇救治中心2020-2022年填报的《海淀区危重孕产妇转会诊指定医院接诊高危孕产妇和危重孕产妇个案登记表》等报表进行汇总分析。结果:2020-2022年海淀区高危孕产妇占比从16.16%升至27.34%(χ^(2)_(趋势)=923.56,P<0.001),危重救治网络高危双向转诊率由47.02%上升至59.21%(χ^(2)_(趋势)=26.03,P<0.001),危重孕产妇救治中心的月床位平均周转次数高于下级助产机构,产科医护人员配置相对紧张,下级助产机构危重孕产妇发生率由3.23‰降至1.45‰(χ^(2)_(趋势)=8.81,P=0.003),孕产妇死亡率也呈现下降趋势(χ^(2)_(趋势)=4.25,P=0.039)。结论:北京市海淀区危重孕产妇救治网络运行效果较为理想,降低了危重孕产妇发生率和孕产妇死亡率,下一步应加强区域资源配置,依托“云上妇幼”,加强信息反馈和人员能力提升。 展开更多
关键词 危重孕产妇 救治网络 资源配置
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