Predicting intensive care unit-acquired weakness:A multilayer perceptron neural network approach

In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.

Observation of the effect of one-to-one education on high-risk cases of diabetic foot

BACKGROUND Diabetes is a common chronic disease,and its global incidence is on the rise.The disease is directly attributed to insufficient insulin efficacy/secretion,and patients are often accompanied by multiple complications.Diabetic foot is one of the most common complications of diabetes.Diabetic feet have ulcers and infections,which can eventually lead to amputation.Basic nursing care,such as lowering blood pressure and preventing foot skin infections in clinical nursing work,has positive significance for the prevention and control of diabetic feet.AIM To explore the positive significance of one-to-one education in high-risk cases of diabetic foot.METHODS This observation included 98 high-risk cases of diabetic foot in our hospital during the period from August 2017 to October 2019,and these patients were randomly divided into the basic nursing group and the one-to-one education group with 49 patients per group.The basic nursing group only received routine basic nursing,while the one-to-one education group gave patients one-to-one education on the basis of basic nursing.After nursing,the self-care ability and compliance behavior of the two groups were evaluated and compared between these two groups.The knowledge mastery of the patient and the satisfaction of nursing were accounted.RESULTS The assessment results of patients(self-care responsibility,self-care skills,selfconcept and self-care knowledge)were significantly higher in the one-to-one education group than in the basic nursing group.The scores of compliance behaviors(foot bathing,shoes and socks selection,sports health care)in the oneto-one education group were significantly higher than those in the basic nursing group.Patients in the one-to-one education group had a significantly higher level of knowledge mastery and satisfaction of nursing than the basic nursing group.CONCLUSION One-to-one education for high-risk cases of diabetic foot is helpful to improve the cognition and self-care ability of patients with diabetic foot,to ensure that patients follow the doctor’s advice of self-care and to improve their nursing satisfaction.

Unveiling significant risk factors for intensive care unit-acquired weakness:Advancing preventive care

In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.

Pioneering role of machine learning in unveiling intensive care unitacquired weakness

In the research published in the World Journal of Clinical Cases,Wang and Long conducted a quantitative analysis to delineate the risk factors for intensive care unit-acquired weakness(ICU-AW)utilizing advanced machine learning methodologies.The study employed a multilayer perceptron neural network to accurately predict the incidence of ICU-AW,focusing on critical variables such as ICU stay duration and mechanical ventilation.This research marks a significant advancement in applying machine learning to clinical diagnostics,offering a new paradigm for predictive medicine in critical care.It underscores the importance of integrating artificial intelligence technologies in clinical practice to enhance patient management strategies and calls for interdisciplinary collaboration to drive innovation in healthcare.

Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

Sensor Networking: Concepts, Applications, and Challenges

Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless networking methodologies. In this overview paper, we first provide some rationales for the growth of sensor networking. Then we discuss various basic concepts and hardware issues. Four basic application cases in the US. National Science Foundation funded Ceneter for Embedded Networked Sensing program at UCLA are presented. Finally, six challenging issues in sensor networks are discussed. Numerous references including relevant papers, books, and conferences that have appeared in recent years are given.

Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care

Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.

New avenues for reducing intensive care needs in patients with chronic spinal cord injury

Relatively soon after their accident, patients suffering a spinal cord injury(SCI) begin generally experiencing the development of significant, often life-threatening secondary complications. Many of which are associated with chronic physical inactivity-related immune function problems and increasing susceptibility to infection that repeatedly requires intensive care treatment. Therapies capable of repairing the spinal cord or restoring ambulation would normally prevent many of these problems but, as of now, there is no cure for SCI. Thus, management strategies and antibiotics remain the standard of care although antimicrobial resistance constitutes a significant challenge for patients with chronic SCI facing recurrent infections of the urinary tract and respiratory systems. Identifying alternative therapies capable of safe and potent actions upon these serious health concerns should therefore be considered a priority. This editorial presents some of the novel approaches currently in development for the prevention of specific infections after SCI. Among them, brain-permeable small molecule therapeutics acting centrally on spinal cord circuits that can augment respiratory capabilities or bladder functions. If eventually approved by regulatory authorities, some of these new avenues may potentially become clinically-relevant therapies capable of indirectly preventing the occurrence and/or severity of these lifethreatening complications in people with paraplegic or tetraplegic injuries.

Virtual Nursing Using Deep Belief Networks for Elderly People (DBN-EP)

The demand for better health services has resulted in the advancementof remote monitoring health, i.e., virtual nursing systems, to watch and supportthe elderly with innovative concepts such as being patient-centric, easier to use,and having smarter interactions and more accurate conclusions. While virtual nursing services attempt to provide consumers and medical practitioners with continuous medical and health monitoring services, access to allied healthcare expertssuch as nurses remains a challenge. In this research, we present Virtual NursingUsing Deep Belief Networks for Elderly People (DBN-EP), a new framework thatprovides a virtual nurse agent deployed on a senior citizen’s home, workplace, orcare centre to help manage their health condition on a continuous basis. Using thismethod, healthcare providers can assign various jobs to nurses by utilizing a general task definition mechanism, in which a task is defined as a combination ofmedical workflow, operational guidelines, and data gathered from a remotelymonitored virtual nursing system. Practitioners are in charge of DBN-EP andmake treatment decisions for patients. This allows a DBN-EP to act as a personalized full-time nurse for a client by carrying out practitioner support activitiesbased on information gathered about the client’s health. An electronic PersonalHealth Record (ePHR) system, such as a specialized web portal and mobile apps,could provide such patient information to elderly person family members and carecentres. We created a prototype system using a DBN-EP system that allows traditional client applications and healthcare provider systems to collaborate. Finally,we demonstrate how this system may benefit the elderly through a result anddebate.

The Management of Mental Health, and Service Networks in Italy

Madness has attracted and frightened for centuries,and talking about this means discussing how this diversity was built and managed in different social contexts and historical periods.Not all societies have had,and still have,the same relationship with madness.It is only with the affirmation of the Modern State,and of Capitalism,that the idea of“normality”indispensable to be able to conceive diversity as something dangerously distant and different from the norm takes over.In our post-modern society,people with mental illness in Italy can resort to specialists and social-health services.But the heterogeneous answers given after the approval of law 180 appear to be increasingly diversified.In this research,much attention will be paid to how the social and health services,located in different areas of Italy(Messina,Rome,Trento)face the current growing risk of social,housing and economic isolation of these fragile subjects.The aim of the research is to explore the possibility of a new relationship between the social-health service and the local community.On the one hand,research investigates what the contribution of the services could be.On the other what the spaces of protagonism and participation of the community could be in inclusion process account.In order to better understand the differences between these two dimensions,a qualitative research approach was chosen through the conduct of in-depth interviews.In this way it was possible to investigate:(1)the partial representations characteristic of the single individual,family members,operators and stackholders in general;(2)the services around the topic dealt with is articulated.From the first results of the research it emerges that the territory can no longer be considered as an abstract entity,but becomes the social space within which the construction of a new community welfare can and must take place.

User Profile in Smart Elderly Care Community:Findings from Community in Western China

With the increase in the aging population,the need for elderly care services has diversified,and smart elderly care has become an effective measure to cope with this increasing aging population.Based on the data from the platform“Guan Hu Tong”of RQ Company in the community of Shaanxi Province in western China,this study mined the data of smart elderly care services through the recency,frequency and monetary value(RFM)model and the backpropagation(BP)neural network model,constructed the user profile of the elderly,and predicted users’practical demands.The following conclusions were drawn:The oldest users are important target users of smart elderly care service platforms;Elderly women living alone rely more on smart elderly care services;Meal delivery and health follow-up services are the most popular among elderly users.

Challenges and Possibilities for the Household Medicine Lease （HML） System Viewed in Light of CRM： HML-Based Everyday Self-Medication in Ubiquitous Network Society

Household medicine lease （HML） industry originated way back in the Edo period （17C-19C）, when it was promoted by the local fiefdom government to revitalize the economy. Accumulations of wealth, acquired thereafter from everywhere outside the region, have culminated in the formation of the present-day industrial cluster in Toyama, the largest in the whole area facing the Sea of Japan. Today an adaptation of the quasi-CRM （customer relationship management） business model of the HML system has proved to be a success in Mongolia. This fact seems to offer the authors some clues for dealing with those problems that healthcare and medical services in Japan and elsewhere are riddled with. In this paper, focusing on the common critical success factors （CSFs） behind the success of the authors＇ prototype HML system and its recent successful application in Mongolia, the authors will analyze these factors from the perspective of CRM. The authors will then clarify the following： （1） the usefulness of the business model for ensuring primary healthcare for people in developing countries; （2） the usefulness in our ubiquitous network society of applying ICT to the HML system; （3） possible contributions that the use of the system can make toward improving the quality of our everyday healthcare and medical services in our prominently aging society; and the authors will also suggest （4） the importance of elevating ＂individual self-medication＂ to ＂community-based self-medication＂.

The development of patient education: Experiences of collaborative work between special and primary care in Finland

Evaluating care pathways, strengthening patient education, developing staff’s patient education skills, and improving collaboration between primary and special healthcare workers are all topical challenges. Successful patient education requires seamless cooperation across organizational boundaries throughout the whole nursing process. The aim of this study is to describe participants’ experiences of development work between primary and special health care units on patient education. In this qualitative descriptive study twenty four health care workers who took part in development work in a collaborative project of special and primary health care service in northern Finland were interviewed when they had nine months’ experience of the development work. The material was analysed using content analysis. Experiences of the nature of development work were described using the following categories: attachment to development work, delight in participation, factors supporting success and challenges of development work. Improvement of co-operation between special and primary health service is a topical challenge. Participation in development work offers occupational learning opportunities. Evaluation and development of own work strengthens staff members’ occupational know-how. The results of this research may be utilized in the planning and execution of development work in the field of health care.

农村医养结合型养老服务政策的演进逻辑

伴随着健康中国战略的稳步推进,我国农村医养结合型养老服务体系经历了从供给不足到供需相对均衡的发展过程,逐步形成了与经济社会持续健康发展相协调的高质量社会养老服务体系,在满足公众需求、缓解社会矛盾、促进社会公平、增进老年福祉等方面发挥了重要作用。深入挖掘其在政策目标、政策内容、价值取向等方面的阶段性特征和变化趋势,通过社会网络分析发现,我国农村医疗卫生与养老服务相结合由点到面逐步拓展,二者由彼此独立走向有机融合,其结合、融合与整合的体制机制逐渐成熟,二者相结合由逐步成熟向深度融合阶段迈进。为了促进医养结合政策的有效衔接,我国应加快推进农村医养结合型养老服务体系建设,以县域医共体为核心发展农村医养结合型养老服务,探究不同类型政策工具之间的合理匹配,全方位提高农村医养结合型养老服务质量,不断提升老年人健康保障水平。

社会网络对中青年群体养老责任认同的影响研究——基于CGSS 2018年数据的检验

从人口代际更迭的角度看,我国目前的中青年群体步入老年阶段后将面临重度老龄化和高龄老龄化并存的养老困境,亟须通过前瞻性制度规划和资源准备避免养老压力的代际叠加。由于认知是意愿形成和行为选择的前提与基础,中青年群体对养老责任归属的态度直接关系未来规模庞大的老年人口的养老方式,厘清其对养老责任主体的倾向与偏好可以在一定程度上预判未来潜在的养老需求,从而在养老资源总量不足、结构不均的情况下实现“有备而老”的积极老龄化目标。同时,我国是典型的人情关系社会,人们往往会借助血缘、亲缘、地缘等社会关系网络及相应资源降低养老活动的运行成本,尤其在家庭养老功能日趋萎缩的背景下,社会网络正在成为个体应对养老风险的重要支持力量,以互联网为代表的新型社交形式日益普及,也为保障老年福祉提供了新的可能。但目前学界相关研究对中青年群体和社会网络因素关注不足,仍然存在研究内容和研究维度上的缺位。基于此,本研究使用中国综合社会调查(CGSS)数据,分析我国中青年养老责任认同的变迁趋势,采用无序多分类Logistic回归模型探究社会网络各因素对中青年养老责任认同的作用机制,并以倾向得分匹配法(PSM)对结果进行稳健性检验。研究发现:在家庭赡养功能持续弱化的宏观背景下,传统的代际责任伦理在我国中青年群体中仍具有相当强的生命力,同时其对社会养老机制和自我养老机制的接受度逐渐提高。而社会关系网络能够发挥非正式保险的效用,对正式养老制度形成补充,进而降低社会风险对家庭的冲击。其中,以朋友交往为代表的强关系对子女养老发挥强有力的替代作用,弱关系网络主要具有补充功能,说明群体信任更强的强关系网络具备弱关系无法比拟的养老资源优势。而互联网作为社会网络中交往行为和互动关系的新表征形态,通过信息传递与政策普及,增强互助养老意识,社会信任则代表个体获取社会关系网络中信息与资源的能力,通过建构社会资本,弱化人们对子女和家庭养老的依赖。因此,以社会支持网络对现有养老实践作出补充,或将在有限养老资源的约束下缓解我国持续加剧的养老压力。

算法推荐背景下网络服务平台过滤义务负担研究

算法推荐技术使得传统版权法体系受到冲击,“通知删除”规则在算法推荐背景下逐渐失灵,无法有效平衡版权人与传播者之间的利益关系,由此所形成的价值差将有损版权人的创作积极性进而严重阻碍互联网文化产业的发展。过滤义务既不是注意义务也不是普遍审查义务,而是一种特殊的版权审查义务,引入网络服务平台的版权过滤义务既有利于缓解现实矛盾,也符合法经济学、公共政策学及知识产权基本原则的基本理论。为了有效平衡版权人与传播者等相关主体的利益,过滤义务负担的标准不宜过高,应根据网络服务平台提供的不同服务类型,对版权人上传的作品类型及网络服务平台的预见能力进行综合设定,网络服务平台对于侵权行为的判断难度越高则其负担的过滤义务越低,反之亦然。

复杂网络视角下政府购买居家养老服务质量影响机理研究

为实现对政府购买居家养老服务质量的科学管控,将直觉模糊二元语义模型及复杂网络分析法引入到对其服务质量影响机理的研究中,从系统的角度探究影响服务质量的关键因素,并提出相应的对策建议。首先,以政府购买居家养老服务链为载体,挖掘政府购买居家养老服务质量影响因素,并运用直觉模糊二元语义模型测度因素间的影响强度;其次,构建政府购买居家养老服务质量影响因素网络,采用优化的加权LR算法评估网络中各因素节点的重要度;最后,结合实证分析验证解决方案的有效性和可行性。研究结果表明,政府监管力度、财政投入以及专业护工比例对政府购买居家养老服务质量的影响最为显著。这为地方政府部门的质量管控决策提供了有益参考。

运用PCNE分类系统对呼吸道疾病患者进行药学监护的应用研究

目的 运用欧洲医药保健网(PCNE)分类系统对呼吸道疾病患者进行药学监护,探索呼吸科的有效药学监护模式,促进临床合理用药。方法 选取安徽理工大学第一附属医院2022年诊断为慢性阻塞性肺疾病(COPD)和肺部感染的住院患者,分为简单组和干预组;根据PCNE分类系统,对药物相关问题(DRPs)的类型、原因、干预、干预的接受情况及解决状态等方面进行分析。结果 共纳入病例120例,简单组60例,干预组60例。DRPs发生人数方面,简单组15例,干预组45例,两组差异有统计学意义(P <0.05)。DRPs共82个,主要涉及治疗效果(51.22%)和安全性(46.34%),原因为患者药物使用方法不正确、用法用量不适宜和未定期安全监测等。药师干预中,药物层面75个(91.46%),医生层面38个(46.34%),患者层面43个(52.44%);药师干预后,接受率为97.56%,74.39%的DRPs得到解决。结论 应用PCNE分类系统进行药学监护能够增强临床药师发现和处理DRPs的能力,减少临床发生不良事件的风险,促进患者的合理、安全用药;同时还有助于药学监护实施记录的标准化和规范化,可为呼吸科患者的药学服务模式提供参考。

药物治疗管理结合PCNE分类系统对乙型肝炎肝硬化患者的药学服务效果评价

目的应用药物治疗管理(MTM)结合欧洲医药保健网(PCNE)的模式对乙型肝炎(乙肝)肝硬化患者进行药学服务,从临床疗效、安全性、人文效果以及药物相关问题等方面分析药学服务成效。方法将乙肝肝硬化患者随机分为药学组(50例)和仅接受传统治疗的对照组(48例),临床药师运用MTM结合PCNE分类系统对药学组进行药学服务,分别从经济效果、临床疗效和安全性、人文结果进行比较,并分析药学组药物相关问题(DRPs)。结果药学组日均用药费用及药占比以及临床指标转归优于对照组,前者药品不良反应相较后者在随访3个月时差异有统计学意义,用药依从性和生活质量在干预后和随访期间均差异有统计学意义(P<0.05)。药学组DRPs共计52个,类别主要为治疗效果不佳,原因主要有药物选择不合理和用法用量不合理,干预接受共计46个,共计解决45个。结论MTM结合PCNE分类系统的药学服务模式对乙肝肝硬化患者的治疗和后续随访具有积极作用。

经皮冠状动脉介入术后病人多维症状网络分析

目的:了解经皮冠状动脉介入术(PCI)病人多维症状体验,构建PCI术后病人症状网络,探索症状网络中的核心症状,为个性化干预提供证据支持。方法:2021年12月—2022年12月选取广西某医院行PCI术的748例病人。采用一般资料调查表、疾病症状严重程度调查表及9条目健康人抑郁量表等,调查PCI术后相关症状的发生率与严重程度;通过高斯模型进行网络分析其核心症状,并基于相关、回归分析联合混合症状网络模型,探索PCI术后各症状与人口学、生活方式及疾病因素间的关系。结果:PCI术后发生率最高的症状是术后切口压迫点疼痛(90.5%);严重程度最高的是疲乏,其次是下肢肿胀以及压迫点疼痛;在高斯网络中,压迫点疼痛在整个网络中起桥梁作用;混合网络中,支架个数与消化道症状、睡眠障碍症状、心慌症状、下肢麻木症状及恐动症状有较强的直接关联,抑郁与疲乏症状有直接关联,生活态度与睡眠障碍症状有直接关联。结论:PCI术后病人压迫点疼痛症状须首要关注,安装支架个数与消化道、焦虑情绪及睡眠障碍等症状往往相互影响,未来的研究有必要建立动态症状网络和中心性指数的轨迹,以探索上述症状和疾病之间的因果关系。