Factors Affecting Cotrimoxazole Prophylactic Therapy Compliance in HIV Patients Attending a Care and Treatment Clinic at Bugando Medical Centre in Mwanza, Tanzania

Introduction: Cotrimoxazole Prophylactic Therapy (CPT) compliance lowers the risk of opportunistic infections and other Acquired Immune Deficiency Syndrome (AIDS)-related diseases. The aim of this study was to examine factors that influence compliance with CPT among HIV patients in the Care and Treatment Clinic (CTC) at Bugando Medical Centre (BMC) in Mwanza, Tanzania. Methods: A descriptive cross-sectional study was conducted at the BMC between April 1, 2021, and June 30, 2021. Data were collected using face-to-face interviews and a semi-structured questionnaire. Data are presented in frequency, percentages, and cross-tabulation tables. A P-value of less than 0.05 was considered statistically significant. Results: The prevalence of compliance with CPT by self-reported measurement was 158 (63.7%). Most CPT-compliant participants were more likely to have a spouse who is familiar with CPT, have a family member who is aware of their HIV status, and be aware of the benefits of CPT. The majority of participants who complied with CPT were more likely to have experienced counseling during refill, felt that the length of time spent seeing doctors for treatment was reasonable, and received accurate information from them. Conclusion: Most adult HIV patients attending CTC at BMC were reported to be in compliance with CPT. These findings suggest that improving social support and patient-provider communication may be effective strategies for improving compliance with CPT among HIV patients.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

Critical Analysis of Increasingly Mathematical Economics in the Modern Society

This paper critically examines the escalating trend of mathematization in economics,highlighting its implications and controversies in contemporary economic research.While the application of sophisticated mathematical models and statistical techniques has enhanced the precision,rigor,and status of economics within academia and practical application,concerns arise regarding the potential oversimplification and detachment from real-world complexities.The adoption of mathematical tools has arguably led to a focus on theoretically tractable problems at the expense of those more relevant to practical economic and social issues.This paper explores both the benefits and limitations of this trend,discussing how the reliance on quantitative methods affects the innovation,comprehensibility,and application of economic theories.We argue for a balanced approach that fosters innovation by integrating qualitative insights and embracing interdisciplinary methods to ensure economics remains both rigorous and relevant to societal needs.

Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.

Ultrasound in Ti-Rads Classification of Thyroid Nodules at the Marie Curie Medical Clinic

Introduction: A thyroid nodule is a localized hypertrophy within the thyroid parenchyma. The aim of our study was to study the benefit of ultrasound in the Ti-rads classification of thyroid nodules. Methodology: This was a prospective study with a descriptive aim, with prospective collection, which took place over a period of 17 months at the “Marie Curie” medical clinic. The ultrasound machine used was a Voluson E8 from 2011 and the examinations were carried out by two radiologists and two experienced sonographers. The parameters studied were sociodemographic data;clinical data and ultrasound aspects of the Ti-rads classification in the management of nodules. Results: We collected 235 patients out of 738 patients referred to the service for a cervical ultrasound, i.e. a frequency of 31.84% of cases. There was a female predominance with 95.7% of cases and a sex ratio of 0.04. The average age of our patients was 50 years. We found on cervical ultrasound: Isthmo-lobar glandular hyperplasia in 99 patients, i.e. a frequency of 42.1%. The Ti-rads 3 classification was the most represented in 69.4% of cases. The benignity criterion represented 85.6% of cases in our patients and the malignancy criterion represented 14.4% of cases. Conclusion: The precise description of a thyroid nodule provided by ultrasound (Ti-rads) is essential in the management of nodules.

Teaching Reform and Practice of Functional Experiment Based on the Cultivation of Excellent Medical Talents

In order to cultivate excellent clinical medical talents with a solid foundation, strong literacy, refined skills, excellent communication abilities, innovative thinking, and a strong focus on practicality, functional experiments have undergone a series of reforms in areas such as constructing new curriculum systems, improving teaching content, updating teaching equipment, introducing new teaching models, and enhancing teaching evaluation systems.

A Study on the Impact of Psychological Counseling for Minor Medical Students in Clinical Teaching and Learning

Objective:To explore the impact of psychological counseling for underage medical students in clinical teaching.Methods:24 of the 48 underage medical students who were interned in our hospital from March 2023 to February 2024 were randomly selected to adopt the teaching management method of one-on-one psychological guidance as the observation group;the remaining 24 adopted the traditional teaching management method as the control group.The observation of the effects of psychological detachment on various aspects of underage medical students allows the determination of whether psychological detachment impacts clinical teaching.Results:The observation group’s theoretical examination scores,skill assessment scores,and departmental performance evaluation scale score excellence rate were higher than the control group’s,with P<0.05 being statistically significant.At the same time,the clinical teaching and teaching management ability of the hospital was also improved.Conclusion:Psychological guidance for underage medical students can not only improve the comprehensive quality of medical students but also improve the teaching level,which is conducive to improving the teaching effect,and it is a clinical teaching mode worth promoting.

Adapter Based on Pre-Trained Language Models for Classification of Medical Text

We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.

Meta-Analysis of Efficacy and Safety of Mongolian Medical Warm Acupuncture in the Treatment of Lumbar Disc Herniation

Objective:To systematically evaluate the safety and efficacy of Mongolian medical warm acupuncture in the treatment of lumbar disc herniation(LDH).Methods:CNKI,Wanfang,VIP,Pubmed,Embase,Cochrane Library,and other databases were searched.The randomized controlled trials(RCTs)on the treatment of LDH with Mongolian medical warm acupuncture were manually searched in the Chinese Journal of Ethnic Medicine,Chinese Journal of Mongolian Medicine,Journal of Inner Mongolia University for Nationalities,and Journal of Inner Mongolia Medical University.The search time limit was from January 2000 to October 2023.RevMan5.4 software was used to analyze the included and excluded literature.Results:A total of 8 RCTs involving 1,042 patients with LDH were included,with 551 patients in the observation group and 491 patients in the control group.The results of the meta-analysis showed that a total of 8 randomized controlled trials were included in the treatment of LDH with Mongolian medical warm acupuncture compared with simple acupuncture(RR=1.18,95%CI=[1.12,1.23],P<0.00001).Conclusion:The total effective rate of Mongolian medical warm acupuncture for LDH is higher than that of simple acupuncture.However,due to the low quality of the literature included in this study,multi-dimensional,large sample size,and more rigorous clinical randomized trials are needed for further verification in the future.

Evaluation of Attending Medical Teams and Their Impact on the DRG Components of Cholecystectomy

Objective:This study assessed the role of the attending medical team in the cost control of the cholecystectomy DRG components.Methods:The association between team structure,workflow,and treatment outcomes was analyzed using a mixed-methods approach combining quantitative data and qualitative interviews from 628 patients.Results:Inter-professional teamwork significantly affected length of stay,treatment costs,and recurrence rates,with experienced teams performing better in terms of emergency response and collaborative efficiency.Patient satisfaction was generally high,indicating that good teamwork enhances treatment outcomes.Significance:The study highlights the importance of optimizing team configuration to improve the quality,efficiency,and cost control of healthcare.

Analysis of the Effect of Extended Rehabilitation Care at Home on the Psychological Condition and Adherence to Medical Compliance Behavior of Patients with Coronary Heart Disease Combined with Heart Failure

Objective:To analyze the effects of providing extended rehabilitation nursing services at home to patients with coronary heart disease(CHD)combined with heart failure(CHF)on psychological improvement and adherence to medical compliance behavior.Methods:79 patients with CHD with CHF admitted to Sijia Town Central Health Hospital,Haimen District,Nantong City,Jiangsu Province,between June 2021 and June 2023 were selected and grouped according to the randomized numerical table method.The control group(39 cases)was provided with conventional nursing care and extended rehabilitation nursing care at home was provided to the observation group(40 cases).The psychological status,adherence to medical behaviors,cardiac function,and complications between both groups were compared.Results:The scores of anxieties and depression self-assessment scales(SAS,SDS)of patients in the observation group were lower than those of the control group(t=2.954,3.212;P<0.05);the compliance of patients in the observation group was higher than that of the control group(P<0.05).The levels of left ventricular ejection fraction,end-systolic and end-diastolic internal diameters(LVEF,LVESD,LVEDD)of patients in the observation group at 58.02±5.34%,44.49±5.16 mm,and 49.16±5.76 mm respectively were better than those of the control group after nursing care(t=3.205,3.288,2.633;P<0.05);the complication rate of the observation group was lower than that of the control group(P<0.05).Conclusion:Extended rehabilitation nursing at home exhibited a psychological regulation effect on CHD with CHF patients,improved their medical compliance,improved cardiac function,reduced the incidence of complications,and had significant application value.

Research on the Construction Status of the Beijing-Tianjin-Hebei Medical Talent Community and the Countermeasures for Its Realization

In April 2015,the Political Bureau of the CPC Central Committee adopted the“Outline of the Plan for the Coordinated Development of Beijing,Tianjin,and Hebei.”In July 2017,the“Plan for the Integrated Development of Beijing,Tianjin,and Hebei Talents(2017–2030),”jointly prepared by the leading groups of the three regions,was officially released.The core of the coordinated development of these three regions is the orderly removal of non-capital functions from Beijing.Talents,especially medical talents,are integral to this transition.The construction of a medical talent community across these three regions promotes the further development of a healthier China,meets the growing needs of the people for a better life,and embodies the concept of putting people first.This paper begins by examining the current situation of the construction of the Beijing-Tianjin-Hebei medical talent community,reviewing the progress made,analyzing existing problems,and proposing targeted countermeasures and suggestions.

Advancements in medical treatment for pancreatic neuroendocrine tumors:A beacon of hope

This editorial highlights the remarkable advancements in medical treatment strategies for pancreatic neuroendocrine tumors(pan-NETs),emphasizing tailored approaches for specific subtypes.Cytoreductive surgery and somatostatin analogs(SSAs)play pivotal roles in managing tumors,while palliative options such as molecular targeted therapy,peptide receptor radionuclide therapy,and chemotherapy are reserved for SSA-refractory patients.Gastrinomas,insul-inomas,glucagonomas,carcinoid tumors and VIPomas necessitate distinct thera-peutic strategies.Understanding the genetic basis of pan-NETs and exploring immunotherapies could lead to promising avenues for future research.This review underscores the evolving landscape of pan-NET treatment,offering renewed hope and improved outcomes for patients facing this complex disease.

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.

Mindfulness training in medical education as a means to improve resilience,empathy,and mental health in the medical profession

The high rates of depression,burnout,and increased risk of suicide among medical students,residents,and physicians in comparison with other careers signal a mental health crisis within our profession.We contend that this crisis coupled with the inadequate acquisition of interpersonal skills during medical education results from the interaction between a challenging environment and the mental capital of individuals.Additionally,we posit that mindfulness-based practices are instrumental for the development of major components of mental capital,such as resilience,flexibility of mind,and learning skills,while also serving as a pathway to enhance empathy,compassion,self-awareness,conflict resolution,and relational abilities.Importantly,the evidence base supporting the effectiveness of mindfulness-based interventions has been increasing over the years,and a growing number of medical schools have already integrated mindfulness into their curricula.While we acknowledge that mindfulness is not a panacea for all educational and mental health problems in this field,we argue that there is currently an unprecedented opportunity to gather momentum,spread and study mindfulness-based programs in medical schools around the world as a way to address some longstanding shortcomings of the medical profession and the health and educational systems upon which it is rooted.

EDSUCh:A robust ensemble data summarization method for effective medical diagnosis

Identifying rare patterns for medical diagnosis is a challenging task due to heterogeneity and the volume of data.Data summarization can create a concise version of the original data that can be used for effective diagnosis.In this paper,we propose an ensemble summarization method that combines clustering and sampling to create a summary of the original data to ensure the inclusion of rare patterns.To the best of our knowledge,there has been no such technique available to augment the performance of anomaly detection techniques and simultaneously increase the efficiency of medical diagnosis.The performance of popular anomaly detection algorithms increases significantly in terms of accuracy and computational complexity when the summaries are used.Therefore,the medical diagnosis becomes more effective,and our experimental results reflect that the combination of the proposed summarization scheme and all underlying algorithms used in this paper outperforms the most popular anomaly detection techniques.

Special Issue: The Global Cross-cultural Integration of TCM in the Mainstream Healthcare, Medical Education and the Practice of Medicine

Ioannis Solos Ph.D.,M.D.(China),L.Ac.currently serves as President and CEO at the Saint George Clinic and Research Institute,Scottsdale,AZ.,and Associate Editor for Chinese Medicine and Culture.Professor Solos has earned his Master of Medicine in Traditional Diagnosis at the Beijing University of Chinese Medicine,and his Medical Ph.D.in Chinese and Western Integrative Medicine at the Jinan University in Guangzhou.He practices and teaches integrative clinical medicine,Jing Fang(经方TCM formulas),martial lineage acupuncture,and his personalized style of“tendon and fascia reconditioning manipulations for bone and joint disease”.

Investigation on the Knowledge, Attitude and Practice of Oral Health among Medical College and University Undergraduate

Objectives: This study aims to investigate the status of knowledge, attitude and practice (KAP) of oral health among medical undergraduate students, and provide reference for implementing oral health interventions. Methods: A total of 528 undergraduate students enrolled in Fuzhou Medical College from February 2023 to September 2023 were selected as the research subjects. Their oral health KAP were investigated, and the oral health behavior habits of different types of medical students were compared, and possible influencing factors were analyzed. Results: The total awareness rate of oral health knowledge among medical students is 77.0%, with an average score of 3.85 ± 1.16 points. The overall positive rate of oral health attitudes among medical students is 80.0%, with an average score of 3.19 ± 0.72 points. The total qualified rate of oral health behavior is 65.9%, with an average score of 4.61 ± 1.23 points. The scores of oral health knowledge, attitudes, and behaviors among medical students are related to gender, major, smoking status, and oral health status. The frequency of brushing teeth in the female group was higher than that in the male group, while the habit of brushing teeth before bedtime and the frequency of timely replacement of toothbrushes when deformed were lower, with statistical significance (p 0.05). The frequency of timely replacement of toothbrushes varies among medical students from different majors, and the difference is statistically significant (p 0.05). People who have a habit of eating hot and cold food have a higher frequency of brushing their teeth every day, and the difference is statistically significant (p 0.05). Non smokers have a better habit of brushing their teeth before bedtime and a higher frequency of timely replacement when their toothbrush deforms, with a statistically significant difference (p 0.05). The frequency of using fluoride toothpaste or medicated toothpaste, having a habit of unilateral chewing, and timely replacement of toothbrushes when deformed in patients with existing oral problems is higher than that of those without oral problems, and the difference is statistically significant (p 0.05). Conclusion: The knowledge, attitude, and behavior of oral health among medical students in this school are above average. Students with different genders, dietary and smoking habits, and oral health status have different oral health behavioral habits. It is recommended to include oral health education in mandatory courses for various medical majors.

Knowledge of Hospital Acquired Infections (HAIs) among Medical Students in a Tertiary Hospital in Jos North Local Government Area, Plateau State, Nigeria

Background: Hospital Acquired Infections (HAIs) remain a common cause of death, functional disability, emotional suffering and economic burden among hospitalized patients. Knowledge of HAIs is important in its prevention and control. This study seeks to assess the knowledge of Hospital Acquired Infections (HAIs) among medical students in a Tertiary Hospital in Jos North Local Government Area, Plateau State, Nigeria. Methods: This was a descriptive cross-sectional study done in October 2019 among clinical medical students using a Multistage sampling technique. Data was collected using a self-administered structured questionnaire and analyzed using the IBM SPSS 20 (Statistical Package for the Social Sciences). Ethical approval was granted by Bingham University Teaching Hospital, Ethics Committee, Jos, Plateau State. Results: A total of 219 students in the clinical arm of the College of Medicine and Health Sciences were selected. A higher proportion (97.7%) of respondents knew about Hospital Acquired Infections and 85.4% knew that Hospital Acquired infections occur in the hospital, and (86.3%) considered patients contagious with half (58.9%) considered patients as the most important source of HAIs, followed by care givers (13.2%), then doctors including medical students and interns (10.0%) and lastly nurses (8.7%). The majority of respondents (70.8%) considered Surgical Wound Infections to be the most commonly occurring HAI, followed by UTIs (69.9%), RTIs (61.2%), BSIs (37.0%) and others (0.9%). The clinical thermometer was the instrument that most commonly transmits HAIs (82.6%), then followed by stethoscope (62.1%), white coats (53.9%), and blood pressure cuff (51.1%). Most respondents knew the infectious substances, like blood (96.3%), nasal discharge (82.6%), saliva (85.3%), and faeces (79.4%) transmitted HAIs, 72.6% of the respondents said that they were aware of the recommended hand washing techniques by WHO. Conclusion: The majority of students 91.3% had good knowledge while 8.7% had poor knowledge of HAIs. Lower classes had more respondents with poor knowledge. This finding was statistically significant (p = 0.002, Chi-square 12.819). Students are encouraged to keep up the level of knowledge they have about HAIs. These students can help improve the knowledge of those whose knowledge level is low. Government and NGOs should support sponsorship for capacity-building events targeted at HAIs for healthcare workers and medical students.