Are case reports valuable?Exploring their role in evidence based medicine and patient care

Case reports,often overlooked in evidence-based medicine(EBM),play a pivotal role in healthcare research.They provide unique insights into rare conditions,novel treatments,and adverse effects,serving as valuable educational tools and generating new hypothesis.Despite their limitations in generalizability,case reports contribute significantly to evidence-based practice by offering detailed clinical information and fostering critical thinking among healthcare professionals.By acknowledging their limitations and adhering to reporting guidelines,case reports can contribute significantly to medical knowledge and patient care within the evolving landscape of EBM.This editorial explores the intrinsic value of case reports in EBM and patient care.

Preceptors'experiences in guiding nursing students to use research findings and to implement evidence-based practice

Objective:Evidence-based practices(EBPs)have been taught to students by identifying the best evidence/evidence from research results.However,the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly.This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.Methods:This study used interpretive phenomenology analysis that involves 9 nurse preceptors from hospitals in West Kalimantan,Indonesia.Semi-structured in-depth interviews were recorded and then transcribed verbatim.Results:Three themes were generated during the analysis:“types of student supervision,”“issues during supervision,”and“the need for research literacy and supervision.”Conclusions:Nurse preceptors need support to supervise the nursing students to use research findings.In addition to upgrading nursing skills,nurse preceptors must receive training in research and its utilization.Developing an appropriate strategy to assist students in using research findings will enhance the promotion of evidence-based nursing practices on a daily basis.

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.

Research on the Application of Evidence-Based Quality Control Circle to Improve the Implementation Rate of Airway Management Measures in Adult Critically Ill Patients

Objective: To explore the effect of evidence-based quality control circle (QCC) in improving the implementation rate of airway management measures in adult critically ill patients. Methods: Based on the Joanna Briggs Institute (JBI) evidence-based health care model, the best evidence of airway management in adult critically ill patients was obtained and applied to the clinic. Results: The total implementation rate of airway management measures in adult critically ill patients increased from 23.62% before the implementation of quality control circle to 88.82%, and the pulmonary infection rate in critically ill patients decreased from 42.31% to 21.74%, with statistical significance between the two groups (P 0.05). Conclusion: Evidence-based quality control circle activities can standardize the practice standards of airway management in critically ill patients, reduce the occurrence of patients’ airway related complications, and improve clinical outcomes.

Intelligent Evidence-Based Management for Data Collection and Decision-Making Using Algorithmic Randomness and Active Learning

We describe here a comprehensive framework for intelligent information management (IIM) of data collection and decision-making actions for reliable and robust event processing and recognition. This is driven by algorithmic information theory (AIT), in general, and algorithmic randomness and Kolmogorov complexity (KC), in particular. The processing and recognition tasks addressed include data discrimination and multilayer open set data categorization, change detection, data aggregation, clustering and data segmentation, data selection and link analysis, data cleaning and data revision, and prediction and identification of critical states. The unifying theme throughout the paper is that of “compression entails comprehension”, which is realized using the interrelated concepts of randomness vs. regularity and Kolmogorov complexity. The constructive and all encompassing active learning (AL) methodology, which mediates and supports the above theme, is context-driven and takes advantage of statistical learning, in general, and semi-supervised learning and transduction, in particular. Active learning employs explore and exploit actions characteristic of closed-loop control for evidence accumulation in order to revise its prediction models and to reduce uncertainty. The set-based similarity scores, driven by algorithmic randomness and Kolmogorov complexity, employ strangeness / typicality and p-values. We propose the application of the IIM framework to critical states prediction for complex physical systems;in particular, the prediction of cyclone genesis and intensification.

循证医学(Evidence-based Medicine)——临床研究与实践的新时代

80年代以来的大规模、随机、双盲、多中心、安慰剂对照临床试验证明,以经验和推论,如以一些临床化验指标为依据的传统临床试验不能反映病人的长期预后。为了对新药和已上市药物作出恰当的评价,应当从所谓“众说纷坛”转向注重和评价病人预后,包括总死亡率、重要心脑血管事件、生活质量、卫生经济学等的“循证医学”。反过来,“循证医学”和临床治疗指南的发展将对新药的研究与开发、医生的临床实践、药物经济学、医疗保健服务决策等带来积极和正面的影响。

A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating SHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new SHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)are also higher than the baseline models.The results of the proposed model help us identify the dominant feature sets that impact thyroid cancer classification and prediction.The features{calcification}and{shape}consistently emerged as the top-ranked features associated with thyroid malignancy,in both association-rule based interestingnessmetric values and SHAPmethods.The paper highlights the potential of the rule-based integrated models with SHAP in bridging the gap between the machine learning predictions and the interpretability of this prediction which is required for real-world medical applications.

Landscape Design Elements in Rehabilitation Environment Founded on Evidence-based Design

The concept and development history of rehabilitation environment were summarized in this study,principles and techniques of applying evidence-based design in the design of rehabilitation environment were analyzed,classification and functions of landscape elements in rehabilitation environment were particularly discussed.

Extension of Paraconsistent Many-Valued Similarity Method to Group Decision

The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.

Application of Clustering-based Decision Tree in the Screening of Maize Germplasm

[Objective] This paper aims to construct an improved fuzzy decision tree which is based on clustering,and researches into its application in the screening of maize germplasm.[Method] A new decision tree algorithm based upon clustering is adopted in this paper,which is improved against the defect that traditional decision tree algorithm fails to handle samples of no classes.Meanwhile,the improved algorithm is also applied to the screening of maize varieties.Through the indices as leaf area,plant height,dry weight,potassium（K） utilization and others,maize seeds with strong tolerance of hypokalemic are filtered out.[Result] The algorithm in the screening of maize germplasm has great applicability and good performance.[Conclusion] In the future more efforts should be made to compare improved the performance of fuzzy decision tree based upon clustering with the performance of traditional fuzzy one,and it should be applied into more realistic problems.

Corticosteroid-free immunosuppression in liver transplantation: An evidence-based review

Thirty-six randomized controlled trials and two metaanalyses were reviewed. With respect to adult patients undergoing first orthotopic liver transplantation(OLT), steroid replacement resulted in fewer cases of overall acute rejection in the corticosteroid free-immunosuppression arm. Initial steroid administration for two weeks and early tacrolimus monotherapy is a feasible immunosuppression regimen without steroid replacement, although further investigations are needed in view of chronic rejections. No significant differences were noted between the treatment groups in terms of patient and graft survival independently of steroid replacement. Renal insufficiency, de novo hypertension, neurological disorders and infectious complications did not differ significantly among steroid and steroidfree groups. Diabetes mellitus, cholesterol levels and cytomegalovirus infection are more frequent in patients within the steroid group. With respect to diabetes mellitus and hypercholesterolemia, the difference was independent of steroid replacement. In relation to transplanted hepatitis C virus patients, mycophenolate mofetil does not appear to have a significant antiviral effect despite early reports. Male gender of donors and recipients, living donors, cold ischemia times, acute rejection, and early histological recurrence were related to the development of advanced hepatitis. There is sufficient scientific clinical evidence advocating avoidance of the ab initio use of steroids in OLT.

A long-term-based handover decision algorithm for dense macro-femto coexistence networks

For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tostay（TTS） to reduce the unnecessary handover numbers.First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations（CBSs） scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.

Innovative Artificial Neural Networks-Based Decision Support System for Heart Diseases Diagnosis

Heart diagnosis is not always possible at every medical center, especially in the rural areas where less support and care, due to lack of advanced heart diagnosis equipment. Also, physician intuition and experience are not always sufficient to achieve high quality medical procedures results. Therefore, medical errors and undesirable results are reasons for a need for unconventional computer-based diagnosis systems, which in turns reduce medical fatal errors, increasing the patient safety and save lives. The proposed solution, which is based on an Artificial Neural Networks (ANNs), provides a decision support system to identify three main heart diseases: mitral stenosis, aortic stenosis and ventricular septal defect. Furthermore, the system deals with an encouraging opportunity to develop an operational screening and testing device for heart disease diagnosis and can deliver great assistance for clinicians to make advanced heart diagnosis. Using real medical data, series of experiments have been conducted to examine the performance and accuracy of the proposed solution. Compared results revealed that the system performance and accuracy are acceptable, with a heart diseases classification accuracy of 92%.

Hepatocellular carcinoma: From clinical practice to evidence-based treatment protocols

Hepatocellular carcinoma(HCC) is one of the major malignant diseases in many healthcare systems. The growing number of new cases diagnosed each year is nearly equal to the number of deaths from this cancer. Worldwide, HCC is a leading cause of cancerrelated deaths, as it is the fifth most common cancer and the third most important cause of cancer related death in men. Among various risk factors the two are prevailing: viral hepatitis, namely chronic hepatitis C virus is a well-established risk factor contributing to the rising incidence of HCC. The epidemic of obesity and the metabolic syndrome, not only in the United States but also in Asia, tend to become the leading cause of the long-term rise in the HCC incidence. Today, the diagnosis of HCC is established within the national surveillance programs in developed countries while the diagnosis of symptomatic, advanced stage disease still remains the characteristic of underdeveloped countries. Although many different staging systems have been developed and evaluated the BarcelonaClinic Liver Cancer staging system has emerged as the most useful to guide HCC treatment. Treatment allocation should be decided by a multidisciplinary board involving hepatologists, pathologists, radiologists, liver surgeons and oncologists guided by personalized-based medicine. This approach is important not only to balance between different oncologic treatments strategies but also due to the complexity of the disease(chronic liver disease and the cancer) and due to the large number of potentially efficient therapies. Careful patient selection and a tailored treatment modality for every patient, either potentially curative(surgical treatment and tumor ablation) or palliative(transarterial therapy, radioembolization and medical treatment, i.e., sorafenib) is mandatory to achieve the best treatment outcome.

Analysis of Telephone Call Detail Records based on Fuzzy Decision Tree

Digital evidences can be obtained from computers and various kinds of digital devices, such as telephones, mp3/mp4 players, printers, cameras, etc. Telephone Call Detail Records （CDRs） are one important source of digital evidences that can identify suspects and their partners. Law enforcement authorities may intercept and record specific conversations with a court order and CDRs can be obtained from telephone service providers. However, the CDRs of a suspect for a period of time are often fairly large in volume. To obtain useful information and make appropriate decisions automatically from such large amount of CDRs become more and more difficult. Current analysis tools are designed to present only numerical results rather than help us make useful decisions. In this paper, an algorithm based on Fuzzy Decision Tree （FDT） for analyzing CDRs is proposed. We conducted experimental evaluation to verify the proposed algorithm and the result is very promising.

Traditional Chinese Medicine as a Treatment for Rheumatoid Arthritis:From Empirical Practice to Evidence-Based Therapy

Rheumatoid arthritis(RA)is a common autoimmune condition with an elusive etiology.Conventional and biological disease-modifying drugs sometimes fail or produce only partial responses.Traditional Chinese medicine(TCM)has long been used in China as a treatment for RA and is achieving everincreasing acceptance worldwide.TCM treatments are traditionally guided by the theory of treatment based on TCM syndrome differentiation;however,they remain a matter of empirical practice relying on TCM theories and doctors’own experience,which places severe restrictions on worldwide TCM application.Nevertheless,TCM is a treasure trove for drug discovery,particularly as a treatment for complicated human conditions.The discoveries of artemisinin as a treatment for malaria and of TCM–arsenic trioxide(As2O3)combination therapy as a treatment for acute promyelocytic leukemia(APL)are excellent examples of the great value of TCM.Regarding RA treatments,many Chinese medicinal herbs and their formulas,extracts,ingredients,and even single compounds have been used in clinical applications.Several Chinese proprietary medicines(CPMs)derived from TCM formulas or herbal bioactive components,such as the controlled-release ZhengQingFengTongNing(ZQFTN)Tablets,Tripterygium Glycoside Tablets,and Total Glucosides of Peony(TGP)Capsules,have been included in the National Health Insurance Directory of China,and show comparable therapeutic efficacies to those of western chemical drugs with fewer side effects.As TCM research has advanced,particularly in the use of multidisciplinary technologies,the scientific foundations and characteristics of the use of TCM to treat RA have been revealed,and the quality of TCM treatments have been increasingly enhanced.However,TCM generally lacks sufficient clinical and laboratory data to be consistent with international standards for quality,safety,and efficacy in order to support its application worldwide.Therefore,intensive basic and clinical studies on TCM are required.In particular,investigations that use cutting-edge technologies in analytical chemistry,biology,and biomedical sciences,and the development of randomized clinical trials(RCTs)and personalized pragmatic randomized controlled trials(PPRCTs)are necessary.Researchers should also collaborate to advance TCM from empirical practice to evidence-based therapy,thus consistently promoting TCM development and globalization in a vital,beneficial,and contributable manner.

New Concepts and Evidence Based Practice in Physiotherapy：Examples from Stroke Rehabilitation

Objective:The purpose of this paper is to give an overview of new concepts and evidence based physiotherapy practice in stroke rehabilitation in the acute,post acute and chronic stage of stroke. Background:Historically physiotherapy has developed through the years from a focus on health,beauty,and equilibrium between spiritual,moral and physical powers,to a client centered service to people and populations to develop,to maintain and to restore maximum movement and functional ability throughout the lifespan. Still the health perspective is strong and divided into first,second and third prophylaxis. New concepts like Evidence Based Medicine,Evidence Based Practice,International Classification of Function and research within neurophysiology have had a deep impact on physiotherapy services,practice and education. The highest levels of documentation are Meta analyses and Randomised Controlled Trials,and today many of the physiotherapy methods used in rehabilitation of neurological conditions are tried out in different trials,bringing up-to date knowledge into practice. This paper focuses on rehabilitation of persons with stroke and physiotherapy methods in particular. Result:Physiotherapy in the acute stage improves motor function and enhances mobility. Rehabilitative efforts within the first few weeks as opposed to later favors better recovery. Type of physiotherapy in the acute stage is task oriented training with a focus on intensity and variability. Post acute therapy-based rehabilitation services targeted towards stroke patients living at home appear to improve independence in personal activities of daily living. In the chronic stage there is good evidence that aerobic exercise is beneficial for improving aerobic capacity in people with mild and moderate stroke. Progressive resistance strength training programmes reduce musculoskeletal impairment after stroke,without increasing tone or spasticity.

EVIDENCE-BASED MEDICINE AND THE CLINICAL STUDY ON ACUPUNCTURE AND MOXIBUSTION

In this article, the authors hold that the evidence based medicine(EBM) is a new medical action produced at the historic moment in clinical practice, which is promoting development of the medicine and even the whole life science in a fully new train of thought and method. Further the briefly introduced contents are the effect of EBM, the difficulty of utilizing in the acupuncture clinical practice and how to resolve them. It is highly recommended that the doctors of the acupuncture science field should study EBM and its effect and difficulties in practice as earlier as possible, insistently assimilate new knowledge and keep abreast of the times’ progress to facilitate the further development of acupunctology.

Condition-Based Maintenance Decision-Making for Equipment

At present, condition monitoring and fault diagnosis technology and their application in engineering have been widely studied. Relatively little attention has been paid to condition-based maintenance decision-making for equipment. In this paper,based on the decision-making policy in traditional condition-based maintenance,the connotation of condition-based maintenance for equipment was defined, and its characteristics were analyzed.Working contents of condition-based maintenance for equipment were provided,which were divided into three stages. The influence factors in condition-based maintenance for equipment were analyzed. The key links of equipment maintenance contents and decision-making process were proposed. The condition-based maintenance decision-making policy presented in this paper can provide a practical reference for equipment maintenance.