Factors influencing the continuity of evidence-based practice in perioperative airway management for elderly patients with fractures:A qualitative study

BACKGROUND More and more evidence-based practices are emerging,but researchers mostly focus on short-term effects,resulting in evidence-based practices not being applied in the clinic in the long term.In this study,we took the evidence-based practice of perioperative airway management in elderly fracture patients as an example and adopted a descriptive phenomenological approach to understand the influencing factors of its sustainability to provide a reference basis for promoting the continuity of evidence-based practice in the clinic.AIM To explore factors influencing the persistence of evidence-based practice in perioperative airway management in elderly patients with fractures.METHODS This study was qualitative research.Nine nurses who implemented evidencebased practice in the orthopedic ward of a tertiary comprehensive hospital in Shanghai from September 2023 to October 2023 were selected using purposive sampling as research subjects.Semi-structured interviews were conducted with them,and the data were analyzed using the Colaizzi phenomenological analysis method based on the three dimensions and ten factors of the NHS sustainability model.RESULTS Three main themes and ten subthemes were identified:Process aspects(benefits to patients,benefits to nurses,lack of follow-up,complex processes);staff aspects(insufficient human resources,inadequate training and education,lack of leadership support);and organizational environment aspects(inadequate infrastructure,poor patient compliance,poor doctor cooperation).CONCLUSION Human resources,training and education,leadership support,infrastructure,and patient-physician collaboration are important factors influencing the sustainability of evidence-based practice for perioperative airway management in older patients with fractures.

Database Search Behaviors: Insight from a Survey of Information Retrieval Practices

This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.

A Deep-Learning and Transfer-Learning Hybrid Aerosol Retrieval Algorithm for FY4-AGRI:Development and Verification over Asia

The Advanced Geosynchronous Radiation Imager(AGRI)is a mission-critical instrument for the Fengyun series of satellites.AGRI acquires full-disk images every 15 min and views East Asia every 5 min through 14 spectral bands,enabling the detection of highly variable aerosol optical depth(AOD).Quantitative retrieval of AOD has hitherto been challenging,especially over land.In this study,an AOD retrieval algorithm is proposed that combines deep learning and transfer learning.The algorithm uses core concepts from both the Dark Target(DT)and Deep Blue(DB)algorithms to select features for the machinelearning(ML)algorithm,allowing for AOD retrieval at 550 nm over both dark and bright surfaces.The algorithm consists of two steps:①A baseline deep neural network(DNN)with skip connections is developed using 10 min Advanced Himawari Imager(AHI)AODs as the target variable,and②sunphotometer AODs from 89 ground-based stations are used to fine-tune the DNN parameters.Out-of-station validation shows that the retrieved AOD attains high accuracy,characterized by a coefficient of determination(R2)of 0.70,a mean bias error(MBE)of 0.03,and a percentage of data within the expected error(EE)of 70.7%.A sensitivity study reveals that the top-of-atmosphere reflectance at 650 and 470 nm,as well as the surface reflectance at 650 nm,are the two largest sources of uncertainty impacting the retrieval.In a case study of monitoring an extreme aerosol event,the AGRI AOD is found to be able to capture the detailed temporal evolution of the event.This work demonstrates the superiority of the transfer-learning technique in satellite AOD retrievals and the applicability of the retrieved AGRI AOD in monitoring extreme pollution events.

Evidence-based orthobiologic practice:Current evidence review and future directions

The field of orthopedic and regenerative medicine is rapidly evolving with the increasing utilization of orthobiologic.These biologically derived therapies,inc-luding platelet-rich plasma,mesenchymal stem cells,bone marrow aspirate con-centrate,stromal vascular fraction(SVF),and autologous chondrocyte implanta-tion,are gaining traction for their potential to enhance the body's natural healing processes.They offer a promising alternative to traditional surgical interventions for musculoskeletal injuries and degenerative conditions.Current evidence su-ggests significant benefits of orthobiologics in treating conditions like osteoarth-ritis,tendon injuries,and spinal disorders,yet inconsistencies in treatment pro-tocols and outcomes persist.The global market for orthobiologics is projected to grow substantially,driven by advancements in biologic therapies such as adipose-derived stem cells and SVF,and the demand for minimally invasive treatments.Despite their promise,regulatory and ethical challenges,as well as the need for high-quality,standardized research,remain significant obstacles.Future dire-ctions in the field include advancements in delivery systems,personalized medi-cine approaches,and the exploration of novel sources like induced pluripotent stem cells,aiming for more targeted and effective treatments.Collaborative efforts are crucial to overcoming these challenges and ensuring the safe and effective application of orthobiologics in clinical practice.

Effect of cetuximab plus FOLFOX4 regimen on clinical outcomes in advanced gastric carcinoma patients receiving evidence-based care

BACKGROUND Although chemotherapy is effective for treating advanced gastric carcinoma(aGC),it may lead to an adverse prognosis.Establishing a highly effective and low-toxicity chemotherapy regimen is necessary for improving efficacy and outcomes in aGC patients.AIM To determine the efficacy and safety of cetuximab(CET)combined with the FOLFOX4 regimen(infusional fluorouracil,folinic acid,and oxaliplatin)as firstline therapy for patients with aGC,who received evidence-based care(EBC).METHODS A total of 117 aGC patients who received EBC from March 2019 to March 2022 were enrolled.Of these,60 in the research group(RG)received CET+FOLFOX4 as first-line therapy,whereas 57 in the control group(CG)received FOLFOX4.The efficacy[clinical response rate(RR)and disease control rate(DCR)],safety(liver and kidney dysfunction,leukopenia,thrombocytopenia,rash,and diarrhea),serum tumor marker expression[STMs;carbohydrate antigen(CA)19-9,CA72-4,and carcinoembryonic antigen(CEA)],inflammatory indicators[interleukin(IL)-2 and IL-10],and quality of life(QOL)of the two groups were compared.RESULTS A markedly higher RR and DCR were observed in the RG compared with the CG,with an equivalent safety profile between the two groups.RG exhibited notably reduced CA19-9,CA72-4,CEA,and IL-2 levels following treatment,which were lower than the pre-treatment levels and those in the CG.Post-treatment IL-10 was statistically increased in RG,higher than the pre-treatment level and the CG.Moreover,a significantly improved QOL was evident in the RG.CONCLUSION The CET+FOLFOX4 regimen is highly effective as first-line treatment for aGC patients receiving EBC.It facilitates the suppression of STMs,ameliorates the serum inflammatory microenvironment,and enhances QOL,without increased adverse drug effects.

Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study

Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.

Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

A Survey of Crime Scene Investigation Image Retrieval Using Deep Learning

Crime scene investigation(CSI)image is key evidence carrier during criminal investiga-tion,in which CSI image retrieval can assist the public police to obtain criminal clues.Moreover,with the rapid development of deep learning,data-driven paradigm has become the mainstreammethod of CSI image feature extraction and representation,and in this process,datasets provideeffective support for CSI retrieval performance.However,there is a lack of systematic research onCSI image retrieval methods and datasets.Therefore,we present an overview of the existing worksabout one-class and multi-class CSI image retrieval based on deep learning.According to theresearch,based on their technical functionalities and implementation methods,CSI image retrievalis roughly classified into five categories:feature representation,metric learning,generative adversar-ial networks,autoencoder networks and attention networks.Furthermore,We analyzed the remain-ing challenges and discussed future work directions in this field.

Comparison between ozonesonde measurements and satellite retrievals over Beijing,China

从2013年开始,作者团队使用自主研发电化学原理臭氧探空仪在华北平原北京地区进行每周一次观测.本研究首次使用2013-2019年期间北京地区臭氧探空数据评估Aqua卫星搭载大气红外探测仪(AIRS)和Aura卫星搭载微波临边探测器(MLS)反演垂直臭氧廓线,并对比臭氧探空,AIRS和Aura卫星搭载臭氧监测仪(OMI)臭氧柱总量结果.尽管臭氧探空与卫星反演垂直臭氧廓线在局部高度处差异较大,但整体来说两者较为接近(相对偏差大多<10%).臭氧探空,AIRS和OMI三种仪器测量臭氧柱总量的年变化特征较为一致,其年均臭氧柱总量分别为351.8±18.4 DU,348.8±19.5 DU和336.9±14.2 DU.后续对国内多站点观测数据分析将有助于进一步理解臭氧探空与卫星反演臭氧资料在不同区域的一致性.

Region-Aware Fashion Contrastive Learning for Unified Attribute Recognition and Composed Retrieval

Clothing attribute recognition has become an essential technology,which enables users to automatically identify the characteristics of clothes and search for clothing images with similar attributes.However,existing methods cannot recognize newly added attributes and may fail to capture region-level visual features.To address the aforementioned issues,a region-aware fashion contrastive language-image pre-training(RaF-CLIP)model was proposed.This model aligned cropped and segmented images with category and multiple fine-grained attribute texts,achieving the matching of fashion region and corresponding texts through contrastive learning.Clothing retrieval found suitable clothing based on the user-specified clothing categories and attributes,and to further improve the accuracy of retrieval,an attribute-guided composed network(AGCN)as an additional component on RaF-CLIP was introduced,specifically designed for composed image retrieval.This task aimed to modify the reference image based on textual expressions to retrieve the expected target.By adopting a transformer-based bidirectional attention and gating mechanism,it realized the fusion and selection of image features and attribute text features.Experimental results show that the proposed model achieves a mean precision of 0.6633 for attribute recognition tasks and a recall@10(recall@k is defined as the percentage of correct samples appearing in the top k retrieval results)of 39.18 for composed image retrieval task,satisfying user needs for freely searching for clothing through images and texts.

Evidence-Based Nursing Practice of Reducing Immune-Related Skin Toxicity of Tumor Patients Guided by Sensitive Indicators

Purpose research on nursing sensitive indicators in tumor Patients application effect in immune-related skin toxicity management. Method select our hospital April to June, 202360 cases patients with immune therapy settings as the control group. August-October, 2023 60 cases the patients treated with immune therapy were the experimental group. The control group adopted regular nursing methods, while the experimental group sensitive Indicators, evidence-based give preventive care. The social situation, psychological state, physical function, quality of life score, incidence of skin toxicity caused by immune checkpoint inhibitors, moderate and above of the two groups of patients were compared. Incidence of skin toxicity. Result: experience group SAS score, SDS score higher than the control group, the difference was statistically significant (P < 0.05);The incidence of skin toxic reactions caused by immune checkpoint inhibitors and the incidence of moderate and above skin toxic reactions in the experimental group are lower than those in the control group, and the difference is statistically significant (P < 0.05). Conclusion: sensitive indicator guidance evidence-based preventive care can reduce the degree of immune-related skin toxicity, improve the psychological state and quality of life of tumor patients treated with immune therapy and reduce the incidence of adverse reactions, improve nursing quality and patient satisfaction.

Clinical Practice of Evidence-Based PDCA Cycle Management Model in Accelerated Recovery of Lung Cancer Patients

Objective: To explore the nursing effect of evidence-based PDCA cycle management mode in accelerated rehabilitation of patients undergoing thoracoscopic lung cancer radical surgery. Methods: 104 patients who underwent thoracoscopic lung cancer radical surgery in our hospital from June 2022 to February 2023 were randomly divided into control group and intervention group, with 52 cases in each group. The control group implemented evidence-based ERAS clinical pathway management, while the intervention group implemented evidence-based PDCA cycle quality management. The postoperative recovery of the two groups of patients was compared. Results: The postoperative recovery of the intervention group was significantly better than that of the control group. The first time to get out of bed, the first time to eat, the duration of chest drainage tube placement, and the length of hospital stay were significantly shorter than those of the control group. The incidence of postoperative chest complications and hospitalization costs were significantly lower than those of the control group, and patient satisfaction was significantly higher than that of the control group (P Conclusion: Evidence-based PDCA cycle quality management mode can effectively improve the implementation quality of accelerated rehabilitation nursing for patients undergoing thoracoscopic lung cancer radical surgery, and it is worthy of clinical promotion.

Evidence-based Clinical Chinese Medicine:What Has Changed Over the Past 20 Years

Chinese medicine has been used for centuries to treat a range of health conditions.This history has produced a wealth of classical literature,case studies and clinical research data detailing its use and effectiveness.However,high-quality and conclusive evidence that meets modern requirements for clinical decision support is lacking.This evidence gap limits the integration of Chinese medicine with contemporary medicine,which in turn limits global access and acceptance of Chinese medicine as a form of safe and effective health care.Over the past 20 years,researchers and organisations around the world,including the World Health Organization(WHO)and United Nations,have worked to support the integration of traditional medicines,such as Chinese medicine,with conventional medicines to improve global health care.This paper provides an overview of Chinese medicine studies published in the top four general medical journals(BMJ,JAMA,Lancet and New England Journal of Medicine)from February 2005 to February 2024 in the past 20 years to highlight the progress in the development of this evidence base.It also highlights key actions taken to promote evidence-based clinical Chinese medicine,including product and practitioner regulation,formalising education standards,and international collaborations.Research conducted at the China-Australia International Research Centre for Chinese Medicine demonstrates the benefits of such a collaboration.Through development of its unique and inclusive‘whole-evidence’approach,plus clinical studies and systematic reviews,the Centre has significantly contributed to the evidence base for clinical Chinese medicine.In addition,its high-impact papers and groundbreaking monographs have been cited in international conventional medicine guidelines.While progress has certainly been made during the past 20 years to build a stronger evidence base for clinical Chinese medicine,there is still a considerable gap that limits its integration with conventional medicine.Future funding and research are needed to continue this work and achieve to safe,effective and accessible traditional medicine as part of the WHO’s Universal Health Coverage strategy.

On the Nature of Online Retrieval of Electronic Data

With the development of information technology,the online retrieval of remote electronic data has become an important method for investigative agencies to collect evidence.In the current normative documents,the online retrieval of electronic data is positioned as a new type of arbitrary investigative measure.However,study of its actual operation has found that the online retrieval of electronic data does not fully comply with the characteristics of arbitrary investigative measures.The root cause is its inaccurately defined nature due to analogy errors,an emphasis on the authenticity of electronic data at the cost of rights protection,insufficient effectiveness of normative documents to break through the boundaries of law,and superficial inconsistency found in the mechanical comparison with the nature of existing investigative measures causes.The nature of electronic data retrieved online should be defined according to different circumstances.The retrieval of electronic data disclosed on the Internet is an arbitrary investigative measure,and following procedural specifications should be sufficient.When investigators conceal their true identities and enter the cyberspace of the suspected crime through a registered account to extract dynamic electronic data for criminal activities,it is essentially a covert investigation in cyberspace,and they should follow the normative requirements for covert investigations.The retrieval of dynamic electronic data from private spaces is a technical investigative measure and should be implemented in accordance with the technical investigative procedures.Retrieval of remote“non-public electronic data involving privacy”is a mandatory investigative measure,and is essentially a search in the virtual space.Therefore,procedural specifications should be set in accordance with the standards of searching.

A Visual Indoor Localization Method Based on Efficient Image Retrieval

The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor localization technologies generally used scene-specific 3D representations or were trained on specific datasets, making it challenging to balance accuracy and cost when applied to new scenes. Addressing this issue, this paper proposed a universal indoor visual localization method based on efficient image retrieval. Initially, a Multi-Layer Perceptron (MLP) was employed to aggregate features from intermediate layers of a convolutional neural network, obtaining a global representation of the image. This approach ensured accurate and rapid retrieval of reference images. Subsequently, a new mechanism using Random Sample Consensus (RANSAC) was designed to resolve relative pose ambiguity caused by the essential matrix decomposition based on the five-point method. Finally, the absolute pose of the queried user image was computed, thereby achieving indoor user pose estimation. The proposed indoor localization method was characterized by its simplicity, flexibility, and excellent cross-scene generalization. Experimental results demonstrated a positioning error of 0.09 m and 2.14° on the 7Scenes dataset, and 0.15 m and 6.37° on the 12Scenes dataset. These results convincingly illustrated the outstanding performance of the proposed indoor localization method.

Evidence-Based Design Application of Water Landscaping for Rehabilitation Gardens for Patients with Mental Disorders

The aim of the article is to explore the influence of the water landscape design of a rehabilitation garden for patients with mental disorders on the recovery effect of patients,intending to provide a better rehabilitation environment for patients with mental disorders.Based on literature research,this article reviews three aspects of evidence-based design theory,the concept of water landscape in rehabilitation gardens,and the types of water features in rehabilitation gardens.The results show that well-designed water features can significantly improve patients’psychological state and reduce anxiety and stress,and that water landscape design in rehabilitation gardens is an effective rehabilitation tool that can facilitate the recovery process of patients with mental disorders.Future designs should take into full consideration patients’needs and preferences,as well as best practices in waterscape design,to maximize its positive impact on patients’recovery.

Improving the Selection Model of Essential Medicines in China by Evidence-based Thinking

Objective To sort out the problems in the selection model of essential medicines in China,and to put forward some suggestions to optimize the selection model to ensure the rationality of the medicines in the essential medicines list.Methods The domestic and foreign literature on the selection of essential medicines was reviewed.Then,the opinions on the selection methods and results of essential medicines from foreign literature were investigated to make a comparison with the selection of essential medicines in China.Finally,the general and special laws of the selection process of the essential medicines were explored.Results and Conclusion It is recommended that the selection model of essential medicines in China should be further optimized,and the evidence-based thinking and methods should be utilized to enhance the scientific nature of the selection process.

A Study on the Application of Evidence-Based Nursing in The Care of Patients with Severe Acute Pancreatitis

Objective: To explore the application research of evidence-based nursing in the care of patients with severe acute pancreatitis. Methods: This study focuses on evidence-based nursing care of severe acute pancreatitis. Patients with severe acute pancreatitis who received treatment in our hospital were selected, from which 80 cases were chosen for detailed analysis. The patients were randomly grouped into a control group (conventional nursing care) and a study group (evidence-based nursing care), with 40 patients each. Relevant research data were recorded during the nursing process, analyzed, and used as research indicators. Results: The hospitalization time and morbidity and mortality rate of the research group were shorter than those of the control group, and the recovery rate was higher than that of the control group (P < 0.05). Patient satisfaction with nursing care in the observation group was higher than in the control group (P < 0.05). Conclusion: For patients with severe acute pancreatitis, the use of evidence-based nursing methods effectively reduced the patient’s mortality rate, improved its curative effect, and also shortened the patient’s hospitalization time.

Improving Statistical Literacy through Evidence-Based Strategies Among First-Year Education Students in a State University

Statistical literacy is crucial for cultivating well-rounded thinkers.The integration of evidence-based strategies in teaching and learning is pivotal for enhancing students’statistical literacy.This research specifically focuses on the utilization of Share and Model Concepts and Nurturing Metacognition as evidence-based strategies aimed at improving the statistical literacy of learners.The study employed a quasi-experimental design,specifically the nonequivalent control group,wherein students answered pre-test and post-test instruments and researcher-made questionnaires.The study included 50 first-year Bachelor in Secondary Education majors in Mathematics and Science for the academic year 2023-2024.The results of the study revealed a significant difference in the scores of student respondents,indicating that the use of evidence-based strategies helped students enhance their statistical literacy.This signifies a noteworthy increase in their performance,ranging from very low to very high proficiency in understanding statistical concepts,insights into the application of statistical concepts,numeracy,graph skills,interpretation capabilities,and visualization and communication skills.Furthermore,the study showed a significant difference in the post-test scores’performance of the two groups in understanding statistical concepts and visualization and communication skills.However,no significant difference was found in the post-test scores of the two groups concerning insights into the application of statistical concepts,numeracy and graph skills,and interpretation capabilities.Additionally,students acknowledged that the implementation of evidence-based strategies significantly contributed to the improvement of their statistical literacy.

Necessary prerequisites for evidence-based practice:results of investigating nurses'informatics competency and information literacy skills

This study aimed to evaluate the correlation between nursing informatics(NI)competency and information literacy skills for evidencebased practice(EBP)among intensive care nurses.This cross-sectional study was conducted on 184 nurses working in intensive care units(ICUs).The study data were collected through demographic information,Nursing Informatics Competency Assessment Tool(NICAT),and information literacy skills for EBP questionnaires.The intensive care nurses received competent and low-moderate levels for the total scores of NI competency and information literacy skills,respectively.They received a moderate score for the use of different information resources but a low score for information searching skills,different search features,and knowledge about search operators,and only 31.5%of the nurses selected the most appropriate statement.NI competency and related subscales had a significant direct bidirectional correlation with information literacy skills for EBP and its subscales(P<0.05).Nurses require a high level of NI competency and information literacy for EBP to obtain up-to-date information and provide better care and decision-making.Health planners and policymakers should develop interventions to enhance NI competency and information literacy skills among nurses and motivate them to use EBP in clinical settings.