搜索结果：Technology and health care : official journal of the European Society for Engineering and Medicine

BackgroundThe German congress for orthopedics and trauma surgery is the largest congress of this specialty in Europe. It reflects the latest scientific achievements and thus has a lasting impact on both, clinical practice and research. Understanding what is currently moving the specialist groups therefore helps to understand where orthopedics and trauma surgery is heading.MethodsContribution titles, topics, authors, and cities were extracted from the German Medical Science database (https://www.egms.de/) and using three distinct network analyses: an author network, a city network, and an entity network. Internal ratings were obtained from the congress committee for further elaboration.ResultsThe congress comprised 696 accepted papers, most of which were presented in German (72.41%) and in the form of lectures (57.61%), focusing on topics such as "spine," "basic research" and "polytrauma." The city network revealed geographical clusters, with Berlin, Munich and Dresden forming the most closely networked nodes. In the entity network, three major communities emerged, focusing on clinical care, fracture research and joint-related studies. Of the 1232 submissions, 85.80% received a majority favorable review, and 56.49% were accepted, with the acceptance rate increasing in proportion to the review score.ConclusionThe analysis of the DKOU 2021 revealed a broad scientific focus and research communities centered on clinical care, fracture studies and joint-related research. Transparent evaluation processes and global longitudinal comparisons are recommended to align research with the global burden of disease, taking into account the limitations of congress-based analyses and the influence of external factors such as the Covid-19 pandemic.

BackgroundAn accurate diagnosis of children's self-care problems significantly matters in the growth and development of children. However, various and extensive disorders make the self-care problems classification extremely complex and require much effort and time to solve.ObjectiveTo deal with the above challenge, a deep learning model is proposed to classify the children's self-care problems intelligently and precisely.MethodThe proposed deep learning model contains two sub-deep neural networks. The first sub-network employs a technology of representing learning named triplet loss. It aims to compress the dimensions of the feature of the children with self-care problems to extract the useful information and exclude the noise, in order to improve classification performance. The second sub-network utilizes a technology for handling the class imbalance problem called focal loss to further improve the classification accuracy.ResultThe experimental results show that the proposed deep learning model outperforms. The averages of accuracy, precision, recall, and F1 score can achieve 99.78%, 0.99, 0.99, and 0.99, respectively.ConclusionTo the best of our knowledge, the proposed method achieves state-of-the-art results. That can significantly support the rehabilitation and growth of children with self-care issues. Furthermore, this study also provides a demonstration and experience of the application of the deep learning model in the healthcare field.

BackgroundRecent research highlights the pivotal role of gut microbiota and bile acids as modulators of metabolic homeostasis in type 2 diabetes (T2D). The concomitant use of probiotics and ursodeoxycholic acid (UDCA) may potentiate glycemic and lipid control via complementary mechanisms.ObjectiveTo evaluate the metabolic effects of probiotic supplementation and its combination with UDCA in metformin-treated T2D patients.MethodsIn this monocentric, prospective, randomized, double-blind, controlled trial, 90 patients with T2D on metformin therapy were randomized into three groups: metformin-only (MG), metformin plus probiotic (MPG), and metformin plus probiotic plus UDCA (MPUG). The intervention lasted 4 weeks. Primary outcomes included changes in fasting glucose, postprandial glucose and HbA1c. Secondary outcomes included lipid profile, C-reactive protein (CRP), and fecal levels of probiotics and UDCA. Two visits were conducted during the study - at the beginning and at the end. Visits involved patient interviews, clinical data collection, anthropometric measurements, blood biochemical analyses, and stool sample analysis for the presence of probiotic culture and UDCA concentrations.ResultsAfter 4 weeks, the MPUG group showed a significant reduction in fasting glucose (-1.7 mmol/L; 95% CI: -2.2 to -1.2), postprandial glucose (-1.3 mmol/L; 95% CI: -1.8 to -0.7), and HbA1c (-0.49%; 95% CI: -0.66 to -0.31) compared to the MG group. Total cholesterol and LDL cholesterol were also significantly reduced, while HDL increased. The concentration of Lactobacillus rhamnosus GG was highest in the MPUG group. No serious adverse events were reported.ConclusionCo-administration of probiotics and UDCA for four weeks in metformin-treated T2D patients significantly improves short-term glycemic control and lipid profiles. These promising results warrant validation in larger, longer-term clinical trials.

BackgroundGestational weight gain (GWG) is a critical factor affecting maternal and fetal health. Excessive GWG increases the risk of complications and contributes to the prevalence of overweight and obesity among women of reproductive age. Despite existing guidelines, many pregnant individuals struggle to manage GWG effectively. Therefore, theory-based and evidence-informed interventions that provide continuous support are urgently needed. Mobile health (mHealth) applications have emerged as promising, cost-effective, and accessible tools for promoting healthy behaviors during pregnancy. This study describes the development of a theory-based mHealth application guided by Social Cognitive Theory (SCT) and the Information-Motivation-Behavioral Skills (IMB) model.ObjectiveThis study aims to present the design and development process of "Gebelikte Kilo Yönetimi" (Gestational Weight Management), a user-centered, evidence-based mHealth application intended to promote healthy nutrition, physical activity, and GWG in line with the Institute of Medicine (IOM) recommendations.MethodsA two-phase, parallel-group, single-blind randomized controlled trial was designed. In Phase 1, the mobile application was developed to support healthy GWG. In Phase 2, its effectiveness in improving adherence to IOM guidelines, promoting healthy eating, and increasing physical activity among pregnant women will be evaluated. The study is registered on ClinicalTrials.gov (NCT06542679).ConclusionsThis mHealth application may offer a scalable, accessible alternative to traditional face-to-face counseling, particularly in settings with limited healthcare access or during public health crises. It holds potential to improve GWG outcomes and support maternal health through digital innovation.

BackgroundHigh-intensity interval training (HIIT) is a time-efficient approach that improves cardiovascular and metabolic health, but it can acutely increase oxidative stress and delay recovery. With the growing availability of wearable sensors and point-of-care biochemical testing, recovery interventions can be evaluated with objective physiological monitoring.ObjectiveTo investigate whether a single session of manual lymphatic drainage (MLD) modulates post-HIIT oxidative stress and lactate responses measured using wearable and point-of-care monitoring tools in healthy adults.MethodsThirty healthy adults were randomized to an MLD group (n&#x2009;=&#x2009;15) or a passive-rest control group (n&#x2009;=&#x2009;15). Exercise intensity was controlled using a wearable heart-rate monitor during a standardized HIIT protocol. Capillary blood lactate, reactive oxygen species (ROS), and antioxidant capacity were assessed at baseline, immediately after HIIT, after 35&#x2005;min of MLD or rest, and at 24&#x2005;h using portable analyzers and photometric assays. Two-way repeated-measures ANOVA and within-group one-way repeated-measures ANOVA were applied.ResultsTime effects were observed in oxidative stress and lactate markers. Within the MLD group, ROS and antioxidant capacity changed significantly over time (p&#x2009;<&#x2009;.05). Antioxidant capacity increased immediately after exercise and declined at 24&#x2005;h. Lactate increased after HIIT and decreased after MLD and at 24&#x2005;h (p&#x2009;<&#x2009;.05). Between-group differences were not significant.ConclusionMLD appears to support post-HIIT physiological recovery, and its effects can be quantified using wearable heart-rate monitoring and point-of-care oxidative stress and lactate testing. This monitoring-based framework strengthens the clinical engineering relevance of MLD as an adjunct recovery strategy in rehabilitation and health-management settings.

Background: Osteoporosis and acute myocardial infarction (AMI) are major health challenges in the aging population. Osteoporosis increases bone fragility, while AMI, often due to atherosclerosis, causes myocardial ischemia and inflammation. Their co-morbidity and shared mechanisms remain unclear. Objective: To explore the causal relationship and shared molecular mechanisms between osteoporosis and AMI. Methods: GWAS data from the Risteys FinnGen R9 database (osteoporosis: 621 cases, 122,861 controls) and the IEU Open GWAS program (AMI: 20,917 cases, 461,823 controls) were analyzed using Mendelian Randomization (IVW, MR-Egger, weighted median). Gene expression datasets (GSE56815, GSE48060) were used to identify differentially expressed genes (DEGs). Functional enrichment, immune infiltration (MCPcounter), and weighted gene co-expression network analysis (WGCNA) were performed, and overlapping hub genes were identified. Results: MR analysis demonstrated a significant causal association between osteoporosis and AMI. Transcriptomic analysis revealed 2434 DEGs in osteoporosis and 2827 in AMI. Enrichment highlighted pathways including immune regulation, MAPK signaling, and cancer-related pathways. Immune infiltration showed altered monocytes and dendritic cells in osteoporosis, and cytotoxic lymphocytes and neutrophils in AMI. WGCNA identified 6 modules in osteoporosis and 11 in AMI, with 1423 common hub genes. Conclusion: Osteoporosis and AMI share genetic and molecular mechanisms, especially involving inflammation and calcium signaling. These findings provide new insights into their co-morbidity and suggest that targeting shared therapeutic pathways may support integrated strategies for improving bone and cardiovascular health.

ObjectiveTo explore the clinical and genetic characteristics of CNTNAP1 gene-related Lethal Congenital Contracture Syndrome Type 7 (LCCS7) and Congenital Hypomyelinating Neuropathy Type 3 (CHN3).MethodsThe clinical data and genetic test results of one patient were retrospectively analyzed. This patient had CNTNAP1 gene-related LCCS7 and admitted to hospital in 2013. A literature review was also conducted by searching for the CNTNAP1 gene or "Lethal Congenital Contracture Syndrome Type 7" or "Congenital Hypomyelinating Neuropathy Type 3" in databases such as CNKI, Wanfang database and PubMed. The clinical and genetic characteristics of CNTNAP1-related LCCS7 and CHN3 diseases were summarized.ResultsThe proband was a female. Prenatal ultrasound showed polyhydramnios, few swallowing and respiratory movements, and a fixed fetal posture. She was born at 33 weeks due to premature rupture of membranes. After birth, she exhibited no cry, respiratory distress, and low muscle tone. She received a series of treatments in the obstetrics department, and was ultimately transferred to neonatology of our hospital due to "respiratory distress in a premature infant." Since the fetus had abnormalities in utero, prenatal family exome sequencing was performed, which revealed two pathogenic mutations, c.1699G&#x2009;>&#x2009;T and c.789G&#x2009;>&#x2009;T, in the CNTNAP1 gene. c.1699G&#x2009;>&#x2009;T was inherited from the father, and c.789G&#x2009;>&#x2009;T was inherited from the mother, confirming compound heterozygosity. The infant died on the 13th day after premature birth. We retrieved 16 reports of CNTNAP1 gene-related LCCS7/CHN3 with 44 patients, and a total of 45 patients were analyzed combined with 1 case in this study. The main clinical manifestations included polyhydramnios (29 cases), fetal akinesia (12 cases), respiratory distress (35 cases), hypotonia (42 cases), hypomyelination (28 cases), and seizures (11 cases).Conclusionthe CNTNAP1 gene test can be considered for polyhydramnios, fetal akinesia, postnatal respiratory distress, hypotonia, and neurological abnormalities.

BackgroundThe knee is one of the most common areas to suffer injuries or be affected by surgery. Physiotherapy rehabilitation was shown to support recovery, but evidence guiding optimal rehabilitation practices is limited. To recommend appropriate exercises, it is essential to understand the musculoskeletal requirements involved in both physiotherapy and activities of daily living (ADLs).ObjectiveThis study aimed to evaluate and compare the knee joint kinematics, joint forces and muscle activity in knee flexors and extensors during selected rehabilitation exercises and ADLs.MethodsKinematic and kinetic data from 30 healthy participants were collected during 20 different tasks. Full-body musculoskeletal simulations were performed to estimate peak knee joint angles, angular velocities, joint reaction forces, and muscle activity of the knee flexors and extensors.ResultsComparatively high requirements were observed for lunges, squats, stair walking and gait. Medium requirements were observed for sitting down and rising from a chair. Low requirements were observed for balance shifts and variations of the single leg stand.ConclusionOverall, ADLs like gait and stair walking show surprisingly high requirements compared to many exercises employed in physiotherapy. These findings are a step towards biomechanically informed exercise selection and the development of personalized rehabilitation programs.

BackgroundThe cross-organ regulatory relationship between the lung and brain has been suggested. However, the causal associations between lung function and brain neuronal activity remain unclear.ObjectiveIn this study, we aimed to investigate this association using univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) analyses.MethodsWe utilized summary data from genome-wide association studies of European ancestry for three lung function indicators (n&#x2009;=&#x2009;400,102), including peak expiratory flow (PEF), forced expiratory volume in 1&#x2005;s (FEV1), and forced vital capacity, and 68 brain regional neuronal activity amplitude traits (NAATs) (n&#x2009;=&#x2009;34,691). The inverse-variance weighted method was employed to obtain main causal estimates. Sensitivity analyses were performed.ResultsIn the UVMR analysis, we showed 23 causal associations, including 21 associations with PEF and 2 with FEV1. The MVMR analysis revealed eight causal associations between PEF and NAATs. These associations were observed across multiple regions, mainly in the precuneus, middle and inferior frontal gyrus, superior and middle occipital gyrus, superior parietal gyrus, inferior parietal lobule, postcentral gyrus, and crus I and II of the cerebellar hemispheres. Among these, causal associations between PEF and the NAAT of the middle occipital gyrus and precuneus (&#x3b2;&#x2009;=&#x2009;-0.146, P&#x2009;=&#x2009;0.024) and the NAAT of the middle frontal gyrus and crus I and II of the cerebellar hemispheres (&#x3b2;&#x2009;=&#x2009;-0.139, P&#x2009;=&#x2009;0.024) were observed.ConclusionsWe demonstrated the genetically predicted causal effects of PEF on brain neuronal activity. Closely monitoring PEF reductions in patients with lung disease may be critical for promptly detecting abnormal brain function.

BackgroundOsteosarcoma (OS) has long presented a formidable challenge to human health and well-being. While traditional treatments, such as clinical chemotherapy and surgical intervention, have shown efficacy, they are frequently accompanied by adverse effects and often lead to a poor prognosis.ObjectiveThymoquinone (TQ) is recognized for its antitumor properties; however, the specific molecular mechanisms underlying its effects against OS remain inadequately understood. Emerging evidence suggests a strong correlation between p53 gene deletion and the onset and progression of various human cancers. This study aimed to elucidate the pharmacological targets and anti-OS mechanisms of TQ using systems bioinformatics approaches, including network pharmacology and molecular docking simulations.MethodsA comprehensive screening process identified 23 potential targets associated with the anti-OS effects of TQ. Subsequent bioinformatics analysis identified 8 core targets involved in TQ's anti-OS activity. Enrichment analysis indicated that these core targets modulate a range of biological processes and may influence multiple molecular pathways.ResultsPreliminary in vitro data indicated that TQ effectively reduces OS cell proliferation, induces apoptosis, and downregulates the expression of P53 and HMOX1 proteins.ConclusionOur findings elucidate the molecular mechanisms underlying TQ's effectiveness against OS, highlighting potential apoptosis-related therapeutic targets, such as P53 and CYCLIN D1, for the treatment of OS with TQ.

BackgroundConventional surgical instruments made from Stainless steel (SS), Titanium (Ti), and Tantalum (Ta) are widely utilized because of their excellent corrosion resistance and strength-to-weight ratio. However, these materials lack antibacterial properties, which could increase the risk of surgical site infections. Recent advancements in antimicrobial and biocompatible coatings, particularly Ag-Ta2O5 (Silver-Tantalum Pentoxide), present better solutions for new surgical instrument design. Despite numerous studies published on this topic, a comprehensive review specifically addressing Ag-Ta2O5 coatings remains absent, resulting in fragmented information across the literature. Systematizing this information and consolidating the developments in this field are beneficial, and this is the motivation behind this review.ObjectiveFor these reasons, this review examines the development and applications of these advanced coatings, with a focus on their antimicrobial and biocompatible properties.MethodsWe critically examine the technological challenges, innovative coating methodologies, and the comparative advantages of Ag-Ta2O5 over traditional and hybrid coatings.ResultsFurthermore, this review identifies future research directions and proposes strategic collaborations among clinicians, engineers, policymakers, and materials scientists to expedite the clinical adoption of these coatings.ConclusionIt is envisioned that this review paper will serve as a valuable source of information for engineers, researchers, and clinicians to stay current with the latest developments in this area and for new researchers to initiate their exploration of coating technology.

BackgroundEffective leadership is crucial for delivering high-quality healthcare, optimizing employee performance, and improving patient outcomes.ObjectiveThis study conducts a bibliometric analysis to examine leadership styles in the healthcare sector, identifying key research trends, influential works, and their impact on work outcomes.MethodsUsing Scopus-indexed publications (2010-2024), this study analyzes eighty-three relevant documents with VOSviewer.ResultsThe findings reveal that various leadership styles, such as transformational, transactional, authentic, collaborative, inclusive, servant, and paternalistic leadership, have a significant impact on both individual and organizational outcomes. Furthermore, transformational leadership is the most studied and influential style, promoting employee engagement, innovation, and better patient care. Transactional leadership ensures structure and efficiency but offers limited long-term benefits. Servant leadership fosters trust, collaboration, and ethical decision-making, while authentic leadership enhances transparency and psychological safety. Additionally, the study highlights a growing focus on healthcare leadership, with Medicine and Business, Management & Accounting as the dominant disciplines.ConclusionThis bibliometric study highlights the critical role of leadership styles in shaping work outcomes in the healthcare sector. Transformational leadership emerges as the most influential, fostering innovation, engagement, and improved patient care.

BackgroundDiabetic Retinopathy (DR) remains a leading cause of blindness among diabetic patients worldwide, necessitating early and accurate diagnostic interventions. While traditional screening methods rely heavily on manual ophthalmologic evaluations, recent advancements in machine learning (ML) and deep learning (DL) have opened new avenues for automated, scalable, and interpretable diagnostic tools. However, challenges persist in developing models that are not only high-performing but also transparent enough to gain clinical trust.ObjectiveThis study introduces a novel, standardized, and interpretable ML framework designed specifically to enhance diagnostic efficiency and accuracy for DR risk prediction. By prioritizing model interpretability alongside predictive performance, our approach aims to bridge the gap between cutting-edge AI technology and clinical applicability.MethodsWe evaluated eleven ML algorithms, optimizing hyperparameters via grid search and five-fold cross-validation to identify top-performing models. A key innovation lies in our dynamic weighted voting ensemble (Voting_soft), which integrates multiple classifiers based on model confidence, thereby leveraging the strengths of diverse algorithms. Model performance was rigorously assessed using accuracy, sensitivity, and area under the curve (AUC) metrics, with ROC and PR curves comparing performance across varying training dataset proportions. Crucially, we employed SHAP (SHapley Additive exPlanations) for interpretability analysis, providing clinicians with actionable insights into feature contributions.ResultsThrough LightGBM-based correlation analysis and AUC curve determination, fourteen clinical features were identified as optimal predictors. Notably, the CatBoost model achieved superior performance on a 20% test set, while the Extreme Random Tree model demonstrated robustness on a 30% test set. Our dynamic weighted voting ensemble (Voting_soft) outperformed individual models in terms of AUC across both datasets. SHAP analysis revealed that age, triglycerides, sex, and HDL-C were key predictors of DR prevalence, offering clinically meaningful explanations for model decisions.ConclusionsThis study presents a groundbreaking ML-based DR risk prediction system that excels in both accuracy and interpretability. The integration of SHAP analysis not only enhances model transparency but also empowers clinicians with a deeper understanding of diagnostic decision-making, ultimately improving the precision and efficiency of DR screening. Our dynamic voting ensemble approach sets a new benchmark for interpretable, multi-model integration in medical diagnostics.

BackgroundThe rapid advancement of digital technologies has transformed healthcare delivery, yet significant gaps remain in patient-centred research on digital healthcare services (DHCS).ObjectiveThis study aims to map the global research landscape of patient-centred DHCS, identify key themes and collaboration patterns, and highlight gaps to guide future research.MethodsFollowing a narrative review of DHCS evolution with China as a regional case study, a bibliometric analysis was conducted on 4163 publications retrieved from Scopus (2020-2025). VOSviewer and the Bibliometrix R package were used for visual mapping and trend analysis.ResultsPatient satisfaction with telemedicine has emerged as a key research focus, while on-site healthcare scenarios receive comparatively less attention. Additionally, the elderly population, as primary users of healthcare services, remains underrepresented in studies on the usability and experience of digital healthcare services. Research methodologies, including questionnaires, interviews, and randomised controlled trials, address diverse demographics and dimensions. International collaboration is dominated by the United States and European countries, reflecting their scientific influence.ConclusionCritical gaps identified include insufficient attention to on-site DHCS and elderly users, alongside disparities in global research influence. Future research should prioritise these areas and strengthen cross-continental collaboration to advance patient-centred digital healthcare delivery.

BackgroundGround reaction force (GRF) and ground reaction moment (GRM) are critical in gait analysis. While force plates provide accurate measurements, they are costly and spatially limiting.ObjectiveThis study aimed to evaluate the reliability and accuracy of GRF and GRM predictions using a feedforward neural network (FNN) integrating infrared camera-based positional data with accelerometer (ACC) data from wearable devices.MethodsEighty participants walked at their usual pace along a 10-meter walkway over force plates. Positional and ACC data of body segments were used to train the FNN to predict GRF and GRM. Prediction accuracy was assessed using multiple metrics, including root mean square error (RMSE) and normalized RMSE (NRMSE).ResultsCombining positional and ACC data improved GRF prediction in all directions (vertical, anterior-posterior, medial-lateral). The combined dataset achieved a correlation coefficient of 0.979 for medial-lateral GRF and an NRMSE of 6.07%. GRM predictions also benefited from ACC integration, especially in the sagittal plane, where R2 reached 0.939, outperforming other models. The vertical direction and transverse axis yielded the lowest RMSE and NRMSE.ConclusionsThese findings surpass many previously reported results, demonstrating the superior performance of the proposed model compared with current state-of-the-art methods. The approach offers a cost-effective, flexible alternative to traditional force plates for clinical and sports assessments.

BackgroundUpper extremity rehabilitation is critical for individuals with neurological disorders such as Parkinson's disease, where motor impairments significantly affect daily functionality.ObjectiveThis study presents the design and prototyping of a novel rehabilitation glove aimed at improving hand and wrist motor recovery through gamified therapy.MethodsThe proposed glove features wireless communication via a Wi-Fi network, adaptability to various hand sizes, and an integrated strength training mechanism using resistance bands and metal hooks. The glove consists of a lightweight forearm frame, a palm component, and a textile glove with embedded mechanical connectors, all designed based on anthropometric data. 3D printing techniques were employed using PLA and flexible TPU materials to create a modular, low-cost, and comfortable structure. The system interfaces with an interactive game, allowing users to control an avatar (bee) through hand movements, promoting motivation and active engagement.ResultsThe prototype effectively addresses key limitations of previous rehabilitation systems, including mobility, comfort, adaptability, and functionality.ConclusionThe proposed rehabilitation glove offers a promising solution for home-based neurorehabilitation.

BackgroundClinical fall risk prediction often relies on subjective observation or simplistic metrics, despite the high costs associated with falls in older adults.ObjectiveThis proof-of-concept study evaluated the validity and reliability of a consumer-grade depth camera system as an objective alternative for automated fall risk assessment.MethodsThirty-nine community-dwelling adults performed Timed Up and Go (TUG), Five Times Sit-to-Stand (FTSS), and Tandem Stance (TST) tests. Concurrent measurements were taken by an automated depth camera and blinded physical therapists. Validity (concurrent, convergent, discriminative) and reliability were assessed.ResultsAutomated FTSS and TUG tests demonstrated strong concurrent validity with therapist measurements (r&#x2009;=&#x2009;0.813 and 0.915) and high discriminative accuracy for fall history (AUC&#x2009;=&#x2009;0.941 and 0.864). Depth camera-based FTSS vertical velocity was significantly lower in participants with a fall history (p&#x2009;<&#x2009;0.001). TST sway metrics showed limited discriminative validity. The system showed good to excellent test-retest reliability. In an age-stratified analysis of older adults (&#x2265;65 years), AFTSS time and the AUC-weighted composite score demonstrated acceptable discrimination for retrospective fall history (AUC&#x2009;=&#x2009;0.892 and 0.867, respectively)ConclusionsThe&#xa0;depth camera system showed promise as a valid and reliable tool for objective quantification of performance on fall-risk-related functional tests, particularly FTSS and TUG, when benchmarked against therapist-administered measurements. Discriminative findings against retrospective fall history should be interpreted as exploratory, and larger prospective studies are required before clinical screening thresholds can be recommended.Trial RegistrationClinicalTrials.gov (NCT06519864).

ObjectiveTo improve gastrointestinal (GI) symptom clusters in colorectal cancer (CRC) patients undergoing chemotherapy by implementing a nursing program based on Knowledge, Attitudes, and Practice (KAP).MethodsThis retrospective study analyzed the medical records of 292 CRC patients who received chemotherapy from June 2023 to December 2024 in Bozhou Hospital Affiliated to Anhui Medical University. Patients were divided into a control group (CG, n&#x2009;=&#x2009;150) and an intervention group (IG, n&#x2009;=&#x2009;142) according to the GI symptom cluster nursing intervention program. GI symptoms, self-management efficacy, level of beliefs, psychological status, functional status, and quality of life were assessed in patients before the intervention (T1), after the fourth chemotherapy session (T2), and after the eighth chemotherapy session (T3).ResultsAt T1, there were no significant differences between the two groups in any of the assessed indices. At T2 and T3, the GI symptom clusters, the number of symptoms, the incidence of symptom clusters, and the nausea, loss of appetite, dry mouth, vomiting, diarrhea, change in appetite, and fullness in the patients of the IG were significantly lower than those of the CG. (P&#x2009;<&#x2009;0.05). In addition, patients in the IG showed significant improvements in self-management efficacy, belief level, psychological condition, functional status and quality of life (P&#x2009;<&#x2009;0.05).ConclusionThe KAP-based nursing program is both acceptable and feasible for managing GI symptom clusters in CRC patients undergoing chemotherapy. It effectively improves patients' GI symptoms and enhances their self-management efficacy, belief levels, psychological status, functional status, and quality of life.

BackgroundIn recent years, for patients with arterial stenosis up to 75% and poor medical control, stent implantation has become the mainstream choice.ObjectiveThe purpose of this work is to study the effects of stent implantation on hemodynamics in the stenotic artery considering microcirculation.MethodsA stent implantation model with microcirculation is constructed. Expansion simulations are carried out for the grid stent and the link stent respectively to analyze the changes in hemodynamic parameters and the mechanical responses of the plaque and the stent.ResultsCompared with the stent implantation study without microcirculation, the results show that the pressure gradient decreases, and the probability of high time averaged wall shear stress near the stent wires reduces after the grid stent is implanted and expanded. The link stent generates time averaged wall shear stress close to the normal physiological range, and no regions with high oscillatory shear index and high relative residence time are found near the stent wire upstream of the stent.ConclusionsThe link stent can not only better improve the hemodynamic environment, but also reduce the risk of intimal hyperplasia and atherosclerosis. These findings reflect the importance of microcirculation in the regulation of hemodynamics after different stent implantations, providing a new perspective for optimizing stent design.