Journal of Multidisciplinary Healthcare最新文献

Tuberculosis remains a common and clinically significant infectious disease in elderly Homo sapiens aged 60 and above, characterized by atypical manifestations and complex treatment. This review provides a comprehensive analysis of tuberculosis-related pulmonary damage in elderly Homo sapiens, evaluates current care practices, and discusses associated challenges. Key areas of discussion include early detection and diagnosis, optimized management of medication regimens, provision of adequate nutritional support, rehabilitation-focused care, and psychosocial support. The necessity of regular follow-up and long-term management is emphasized to prevent complications and promote functional recovery. Future research and clinical practice directions should focus on developing personalized, technology-integrated care strategies to enhance care quality, improve clinical outcomes, and support the overall health of this Homo sapiens population.

Objective: Fire needle therapy has shown promise in treating acne vulgaris (AV), improving facial lesions and patient quality of life. This study aims to investigate the effects of combining fire needle therapy with doxycycline hydrochloride tablets (DHT) on the Global Acne Grading System (GAGS), the échelle d'évaluation clinique des cicatrices d'acné (ECCA) grading scale, the Dermatology Life Quality Index (DLQI), and the serum levels of inflammatory factors interleukin-17 (IL-17), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) in patients with moderate-to-severe AV.

Methods: 70 patients with moderate-to-severe AV were randomly assigned to the control group (n=35) to receive oral DHT treatment once a day and the intervention group (n=35) to be treated with fire needle therapy on the basis of DHT once a week. The total treatment duration for both groups was 8 weeks. Therapeutic efficacy was evaluated at the 4-week and 8-week marks. The primary outcome measure evaluated was the GAGS score. The secondary outcome measures included the ECCA score, the DLQI score, and the serum levels of the inflammatory factors IL-17, TNF-α, and IL-6.

Results: Compared to baseline data, both groups exhibited marked improvements in skin lesions at both the 4-week and 8-week treatment marks. Significant reductions were observed in the GAGS, ECCA, and DLQI scores, as well as in the serum levels of the inflammatory factors IL-17, TNF-α, and IL-6. Notably, the intervention group demonstrated significantly greater improvements than the control group at both the 4-week and 8-week assessments.

Conclusion: An 8-week regimen of fire needle therapy combined with DHT improved lesion severity, scar symptoms, quality of life, and serum inflammatory cytokine levels in patients with moderate-to-severe AV compared to DHT monotherapy.

Purpose: To analyze and summarize research hotspots and development trends in the health-related quality of life (HRQoL) of patients undergoing extracorporeal membrane oxygenation (ECMO), providing a reference for future studies on survivor outcomes.

Methods: Articles published between 2013 and 2024 were retrieved from the Web of Science Core Collection. VOS viewer was used to assess contributions by countries, institutions, and authors in ECMO-related research. Collaboration networks, trending topics, and keyword patterns were analyzed using VOS viewer and Pajek.

Results: A total of 164 publications from 22 countries were included, accumulating 2870 citations overall. Research on ECMO patients' health-related quality of life demonstrated an annual growth rate of approximately 15% over the past decade. The United States, Germany, and Australia were the primary contributors. High-frequency keywords included outcomes, survivors, and ARDS, with COVID-19 emerging prominently from 2020 to 2024.

Conclusion: This bibliometric analysis, the first to focus specifically on ECMO survivors' HRQoL, demonstrates steady progress in the field. The analysis highlights three major research hotspots: survivor outcomes, rehabilitation strategies, and the impact of COVID-19, offering concrete insights into evolving directions and areas requiring future investigation.

Objective: To provide an overview of the current state of mixed reality (MR) technology's application in medical education and to review a research scope of the area.

Methods: According to the Joanna Briggs Institute's scope-based review procedures, searches were conducted in the following databases: PubMed, Embase, Web of Science Core Collection, Cochrane Library, CNKI, WanFang Database, and VIP Database. The included literatures were compiled and examined, and the search period was limited to the period from the database's creation to April 20, 2025.

Results: In all, 4118 records were found. After eligibility assessment, 28 studies in English or Chinese that examine the use of MR in education for medical students were included. Data extraction focused on theoretical/skills test scores, students' satisfaction, testing and evaluation of the system operation as well as students' learning interest of MR. The majority of studies indicated MR technology effectively enhances students' theoretical knowledge and skill proficiency. Eighteen studies consistently reported a high students' satisfaction level with MR-assisted instruction; MR systems demonstrated favorable usability due to its high consistency. Ten studies showed students in the MR-assisted learning groups exhibit heightened learning interest.

Conclusion: MR Technology has demonstrated excellent performance in enhancing students' mastery of theories/skills, improving students' satisfaction, and increasing students' interest. However, it has not yet been widely adopted due to the high costs associated with teacher training and the purchase and maintenance of equipment. The future should prioritize continuously developing the immersive experience and engagement of MR technology, integrating ecological instantaneous evaluation methodologies and artificial intelligence technology, and combining economic benefit analysis and feasibility testing to perform higher-quality original research.

Objective: Using network analysis, this study examined the interactions between positive psychological capital (PsyCap) and quality of life (QoL) in patients after percutaneous coronary intervention (PCI), identifying core psychological dimensions and cross-domain bridging symptoms to inform targeted psychological interventions.

Methods: In this cross-sectional study, 186 post-PCI patients were enrolled. PsyCap dimensions (resilience, optimism, hope, self-efficacy) were measured with the Positive Psychological Capital Scale (PPC), and QoL domains (physical strength, illness, medical conditions, daily activities, social psychology, work status) were assessed using the Chinese Quality of Life Questionnaire for Cardiovascular Patients (CQQC). Gaussian graphical models combined with LASSO regularization were employed to construct network structures. Centrality and bridge strength analyses identified key nodes, and bootstrap resampling was used to evaluate network stability.

Results: PsyCap demonstrated a dual-core structure comprising "self-efficacy-hope" and "resilience-optimism." Among QoL dimensions, the strongest interaction was observed between "daily activities" and "social psychology." "hope" emerged as the central hub within the PsyCap network and a critical bridge node, forming a robust link with the "daily function" domain of QoL. Stability analyses confirmed high network reliability, with statistically significant differences in edge weights and node strength.

Conclusion: As the first application of network analysis in this population, this study elucidates the multilevel psychological rehabilitation mechanisms post-PCI and reveals that "hope" is associated with synergistic improvements in both PsyCap and QoL through the integration of goal-directed cognitive and behavioral activation. These findings transcend conventional unidimensional intervention approaches and provide actionable network-based targets for implementing integrated psychological-functional rehabilitation models.

Purpose: This scoping review aimed to explore the application of mobile health (mHealth) in prostate cancer (PC) care, focusing on how these interventions have been applied to promote self-management and patient empowerment.

Methods: A comprehensive search was performed across multiple databases, including CNKI, PubMed, Embase, Web of Science, and Cochrane Library. Studies were included if they involved mHealth interventions for prostate cancer patients and assessed self-management or empowerment outcomes. Data were extracted from randomized controlled trials, quasi-experimental studies, and mixed-methods studies.

Results: Among the 30 studies included, mHealth interventions were reported to support improvements in self-management and patient empowerment. Interventions ranged from remote monitoring systems and mobile apps to social media platforms, with generally high feasibility and patient satisfaction. However, the evidence remains heterogeneous, and challenges persist regarding data privacy, platform customization for older adults, and integration of theoretical frameworks.

Conclusion: mHealth interventions show promise in enhancing prostate cancer management by supporting patient empowerment and self-management. Nevertheless, evidence is still limited, and future research should prioritize personalized approaches and address privacy concerns to better establish their role and optimize impact.

Objective: As a non-invasive, convenient and real-time imaging tool, ultrasound has provided new imaging evidence for rehabilitation and scientific research in recent years. As the volume and scope of studies grow, analyzing the innovative applications and research trends of ultrasound in rehabilitation is essential. This study employs bibliometric methods to map global research collaboration networks in ultrasound for rehabilitation, explore research dynamics, and predict future research themes based on emerging trends.

Methods: We performed a bibliometric analysis of 8346 articles from the Web of Science (WoS) Core Collection (1990-2024) using CiteSpace and VOSviewer.

Results: A total of 8346 articles were included. Annual publication volumes have a surge in the past five years. Western countries dominate research output, while institutions in China are emerging as significant contributors. Levent Ozcakar and Paul W. Hodges lead in publication volume and citation impact, respectively. Musculoskeletal ultrasound, intelligent algorithms, and skill education are key citation clusters and emergent topics. High-frequency keywords include ultrasound examination, exercise and efficacy validation emerging recently.

Conclusion: Ongoing research is likely to continue focusing on the reliability of ultrasound for diagnosing various diseases, musculoskeletal quantification through novel ultrasound technologies in physical therapy, and ultrasound monitoring and biofeedback in respiratory and postpartum rehabilitation. Additionally, musculoskeletal examination evidence, real-time training monitoring, and systematic review evaluation are gaining increasing attention. These emerging areas may serve as guiding themes for future research, providing a foundation for continued innovation in the application of ultrasound in rehabilitation.

Background: Abnormal liver function has often been associated with epilepsy, but there is a lack of large-scale clinical evidence to support the potential correlation between liver function and post-stroke epilepsy.

Objective: We aimed to explore a real correlation between liver function and secondary epilepsy after stroke.

Methods: From the Dryad database, we retrospectively identified 21,459 patients who had experienced acute ischemic stroke. Multivariate regression was used to clarify the correlation between liver function and secondary epilepsy post-stroke via cross-sectional analysis.

Results: Our multivariate nonlinear analysis, adjusted for age and gender, suggested that a significant correlation exists between liver function (alanine aminotransferase [ALT] and aspartate aminotransferase [AST]) and the risk of secondary epilepsy post-stroke. Saturation effect analysis showed that a fold point (K) of blood AST level of 39.3 U/L was related to an epilepsy event. An increased AST level was related to a higher rate of epilepsy (1.2 [1.2-1.3], <0.001) among patients with AST levels of less than 39.3 U/L. Significance was weaker among patients with AST levels of more than 39.3 U/L. As for ALT, the fold point of blood ALT level revealed an association with epilepsy at 23.3 U/L. Similarly, elevated AST levels were related to a significantly higher risk of secondary epilepsy post-stroke (1.2 [1.1-1.2], <0.001) when they were less than 23.3 U/L. The significant correlation was weaker when blood AST levels were higher than 23.3 U/L. Importantly, ROC curve analysis displayed a high AUC value (0.8101) of blood AST in terms of detecting epilepsy risk, with a sensitivity of 0.7254 and specificity of 0.7997, respectively.

Conclusion: Our study provided potential evidence for the correlation between liver function and secondary epilepsy after acute stroke, indicating that early protection and management of liver dysfunction among post-stroke patients might be beneficial for reducing epileptic seizures. More studies with a high level of evidence are needed to confirm this finding, however.

Objective: This study aimed to examine the association between different obesity-related metabolic phenotypes, transitions in metabolic status over time, and cognitive function improvement among middle-aged and older adults in China.

Methods: Data were derived from the China Health and Retirement Longitudinal Study, a nationally representative longitudinal cohort involving urban and rural residents aged 45 years and older. Baseline data were collected in 2011, with follow-up assessments extending to 2020. Participants were classified into four body mass index (BMI)-metabolic phenotypes: Metabolically Healthy Normal Weight (MHNW), Metabolically Unhealthy Normal Weight (MUNW), Metabolically Healthy Overweight/Obesity (MHOO), and Metabolically Unhealthy Overweight/Obesity (MUOO). Cognitive function was evaluated through assessments of episodic memory, mental status, and overall cognitive performance. Statistical analyses were performed using R Studio 4.3.1. Cox regression analysis models were employed to estimate associations between metabolic phenotypes, their longitudinal transitions, and changes in cognitive function.

Results: In both the 2011 and 2015 surveys, MHOO demonstrated significantly higher scores in episodic memory, mental status, and overall cognitive function compared to other groups, while MUNW demonstrated significantly lower scores across all domains. In addition, cognitive outcomes varied by BMI-metabolic phenotypes: MHOO was positively associated with cognitive improvement, MUNW was usually associated with poorer cognitive outcomes, and MUOO had no significant association with cognitive changes. Moreover, individuals with stable MUNW status exhibited a lower likelihood of cognitive improvement relative to those with stable MHNW status. In contrast, individuals with stable MHOO status demonstrated a significantly greater likelihood of cognitive improvement. Furthermore, transitioning from MHNW to MUNW was associated with decreased likelihood of favorable cognitive outcomes.

Conclusion: Regardless of weight classification, metabolic health was associated with superior baseline cognitive function and a slower rate of cognitive decline. These findings underscore the significance of metabolic health in predicting cognitive aging trajectories among middle-aged and older individuals.

Background: The rising prevalence of mental disorders, coupled with limited access to mental health services, underscores the urgent need for innovative solutions. Artificial Intelligence (AI) offers transformative potential in managing mental health conditions through multimodal data analysis.

Objective: This study explores emerging applications of AI in early detection, personalized treatment, and the prevention of symptom escalation in mental disorders.

Methods: A narrative review was conducted using comprehensive searches of PubMed, Scopus, and IEEE Xplore databases (2015-2025). Selected sources included studies on natural language processing (NLP), deep learning, and the analysis of multimodal data (eg, voice, text, and biosensor inputs). A qualitative synthesis was employed to identify key patterns, challenges, and innovations.

Findings: AI enhances early detection through concepts such as a "psychological digital signature" and reports high performance in some studies (reported accuracies vary widely, eg, up to ~91% in selected cohorts). However, many high-accuracy reports derive from single-site or limited datasets with variable external validation; therefore, these figures should be interpreted cautiously. We discuss study-specific limitations (sample size, validation methods, and population diversity) in the Methods and Critical Appraisal sections.

Conclusion: AI provides a patient-centered, preventive framework for reimagining mental health care. However, its effective integration requires robust ethical standards and digital infrastructure. Ethical considerations are critically linked to clinical implementation, particularly regarding privacy, fairness, and transparency in AI-assisted decision-making.