Association of Handgrip Strength and Cardiovascular Disease Risk Among Middle-Aged Postmenopausal Women: An Analysis of the Korea National Health and Nutrition Examination Survey 2014-2019.

Purpose: Handgrip strength is an indicator of overall muscle strength and has been associated with an increased risk of cardiovascular disease. Evidence suggests that menopause is a risk factor for cardiovascular disease in women, and muscle strength decreases progressively after menopause. Despite the prognostic importance of the decline in muscle strength and increased cardiovascular disease risk among postmenopausal women, evidence of their association is limited. This study aimed to investigate the relationship between handgrip strength and cardiovascular disease risk among postmenopausal, middle-aged Korean women. Patients and Methods: Using pooled cohort equations, we calculated the 10-year risk of atherosclerotic cardiovascular disease (ASCVD) among postmenopausal women (N = 2019) aged 50-64 years without cardiovascular disease history from the 2014-2019 Korea National Health and Nutrition Examination Survey. Relative grip strength was defined as measured grip strength divided by body mass index. Logistic regression analysis of a complex sampling design was performed to evaluate the association between relative grip strength and a predicted 10-year ASCVD risk ≥7.5%. Results: The average handgrip strength was 24.8 kg, and 5.2% of women were considered for sarcopenia (<18 kg). The quartile-stratified relative grip strength was negatively associated with 10-year ASCVD risk (p < 0.001). In the multiple logistic regression analysis, the adjusted odds ratio for the highest relative grip strength quartile was 0.53 (95% confidence interval [CI]: 0.36-0.78), and that of the group who breastfed for more than 12 months was 1.75 (95% CI: 1.36-2.25) for 10-year ASCVD risk. Conclusion: Increased handgrip strength may be associated with lower cardiovascular disease risk among middle-aged postmenopausal women in Korea. Our findings provide critical evidence regarding the importance of increasing handgrip strength among postmenopausal, middle-aged women to reduce cardiovascular disease risk. Handgrip strength measurement might be a valuable screening tool for cardiovascular disease prevention.

Combination of phytochemicals, including ginsenoside and curcumin, shows a synergistic effect on the recovery of radiation-induced toxicity.

Radiotherapy is commonly used to treat solid cancers located in the pelvis. A considerable number of patients experience proctitis of varying severity, even for a considerable period after radiotherapy. These side effects are often long-lasting or progressively worsen despite multiple therapeutic efforts and are a primary cause of an unexpectedly low quality of life, even after successful cancer treatment. Therefore, this study evaluated the individual and combined efficacy of ginsenoside, curcumin, butyric acid, and sucralfate compounds in treating radiation-induced proctitis. While the candidate compounds did not affect the proliferation and migration of cancer cells, they promoted the recovery of cell activity, including motility. They exhibited anti-inflammatory effects on human dermal fibroblasts or human umbilical vein endothelial cells within in vitro disease models. When each compound was tested, curcumin and ginsenoside were the most effective in cell recovery and promoted the migration of human dermal fibroblasts and cell restoration of human umbilical vein endothelial cells. The combination of ginsenoside and curcumin resulted in cell migration recovery of approximately 54%. In addition, there was a significant improvement in the length of the endothelial tube, with an increase of approximately 25%, suggesting that the ginsenoside-curcumin-containing combination was the most effective against radiation-induced damage. Furthermore, studies evaluating the effects of combined treatments on activated macrophages indicated that the compounds effectively reduced the secretion of inflammatory cytokines, including chemokines, and alleviated radiation-induced inflammation. In conclusion, our study provides valuable insights into using curcumin and ginsenoside as potential compounds for the effective treatment of radiation-induced injuries and highlights the promising therapeutic benefits of combining these two compounds.

Software-based interventions for low back pain management: A systematic review and meta-analysis.

INTRODUCTION: Using software for self-management interventions can improve health outcomes for individuals with low back pain, but there is a dearth of research to confirm its effectiveness. Additionally, no known research has evaluated the effective elements of software-based interventions for low back pain self-management components. This study aimed to synthesize the effectiveness of software-based interventions to promote self-management health outcomes among individuals with low back pain. DESIGN: A systematic review and meta-analysis was conducted. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement, relevant studies up to July 2022 were searched via four electronic databases: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, and Web of Science. RESULTS: 4908 adults with low back pain who participated in 23 studies were included. Software-based interventions were effective in reducing fear avoidance (mean difference [MD] = -0.95, 95% CI: -1.45 to -0.44), pain catastrophizing (MD = -1.31, 95% CI: -1.84 to -0.78), disability (MD = -8.21, 95% CI: -13.02 to -3.39), and pain intensity (MD = -0.86, 95% CI: -1.17 to -0.55). Specifically, interventions that included an exercise component were more effective in reducing pain and disability. Additionally, cognitive behavioral therapy (CBT) intervention significantly reduced fear avoidance and pain catastrophizing but had no noticeable impact on disability and pain compared to standard treatment. The certainty of the evidence in this review varied from very low to high across outcomes. The heterogeneity of the study results was significant, suggesting that future studies in this area could optimize the design, time points, measures, and outcomes to strengthen the evidence. CONCLUSIONS: Low back pain self-management interventions delivered through software-based programs effectively reduce pain intensity, disability, fear avoidance, and pain catastrophizing. CLINICAL RELEVANCE: Low back pain is among the most common reasons for seeking healthcare visits. Combining exercise and counseling through soft-based programs may effectively address this issue and its associated suffering and disability.

Pathways Through Which Experience in Treatment Decision-Making Affects Health-Related Quality of Life in People with Chronic Conditions.

Patient engagement in treatment decision-making is essential to improve the health-related quality of life (HRQoL) of patients affected by chronic diseases. However, research on how decision-making patterns influence HRQoL is limited. This study investigated the paths linking patient experience in decision-making to HRQoL through healthcare accessibility and physical activity among a representative sample of adults with chronic diseases. Using a cross-sectional design, the data of 4,071 individuals with chronic diseases from the 2015 Korea National Health and Nutrition Examination Survey were analyzed. We used R to account for the complex survey design and weights and conducted structural equation modeling. The EuroQoL 5 Dimensions were used to assess HRQoL. About half of the participants reported that providers always offered sufficient encounter time (48.8%), used lay terms (60.4%), provided opportunities for questions (57.8%), and reflected patient opinions on treatment plans (57.8%). Healthcare accessibility completely mediated the association between patient experience in decision-making and HRQoL, whereas decision-making experiences directly affected HRQoL, not via physical activity. Clinicians should provide solid and tailored advice that entails benefits and detriments to achieve evidence-based decision-making. Programs to enhance access to after-hour healthcare should be considered to improve patients' HRQoL.

Medication safety education in nursing research: Text network analysis and topic modeling.

OBJECTIVES: This study aimed to identify the knowledge structure of medication safety nursing education literature by developing schematic diagrams of the relationship between keywords from a macro perspective. This study also identifies the research topics and trends over time. DESIGN: This quantitative content study used text network analysis to explore keywords and research topics using topic modeling within the medication safety nursing education literature. DATA SOURCES: PubMed, EMBASE, and Cochrane databases were used to search for the medication safety nursing education literature published until December 2021. METHODS: Keywords from 2085 articles were examined using text network analysis and topic modeling with NetMiner 4.4.3. RESULTS: The keywords with the most frequency and the highest networking degree in centrality were "patient," "medication," "program," "nurse," and "care." The emerging keywords assessed by time periods were identified; the first phase ("heart failure," "insulin," "chemotherapy," and "infusion"), the second phase ("medication errors," "staff," and "information"), the third phase ("program," "management," and "data"). The results of topic modeling were as follows: safe medication administration, safe medication reconciliation process, medication education for patients, medication errors in nursing practice, and multidisciplinary teamwork for medication safety. CONCLUSION: These findings will help nursing researchers and educators to understand the trends and insights for medication safety education and educate future nurses to provide safer nursing care.

Identifying the Knowledge Structure and Trends of Nursing Informatics: A Text Network Analysis.

With the advent of the information age and technological development, the importance of digital health technologies has increased. Subsequently, nursing informatics has been developed to enhance the effectiveness of healthcare information management and communication. This study aimed to identify the nursing informatics knowledge structure and research trends through quantitative analysis using text network analysis. Here, we analyzed 14 225 studies published by 2020. The knowledge structure of nursing informatics and changes therein were clarified by identifying and analyzing the core keywords, topics, and changes in the topics of related studies over time. We identified "patient," "health," "system," and "information" as core keywords connecting other keywords. Over time, the networks between "information," "communication," and "technology" strengthened, and "patient safety" and "quality" have recently emerged as research keywords. This change indicates an increase in the importance of nursing education on technology. Similar changes appeared in the topic analysis, showing an increased proportion of research related to system and technology and nursing education. These results can broaden a systematic understanding of nursing informatics research. Furthermore, given these findings, the importance of nursing informatics on patient safety and nursing education-based on the development of systems and technology-can be expected to continue growing.

Privacy Attitudes and COVID Symptom Tracking Apps: Understanding Active Boundary Management by Users.

Multiple symptom tracking applications (apps) were created during the early phase of the COVID-19 pandemic. While they provided crowdsourced information about the state of the pandemic in a scalable manner, they also posed significant privacy risks for individuals. The present study investigates the interplay between individual privacy attitudes and the adoption of symptom tracking apps. Using the communication privacy theory as a framework, it studies how users' privacy attitudes changed during the public health emergency compared to the pre-COVID times. Based on focus-group interviews (N=21), this paper reports significant changes in users' privacy attitudes toward such apps. Research participants shared various reasons for both increased acceptability (e.g., disease uncertainty, public good) and decreased acceptability (e.g., reduced utility due to changed lifestyle) during COVID. The results of this study can assist health informatics researchers and policy designers in creating more socially acceptable health apps in the future.

Identifying the knowledge structure of electromagnetic fields and health research: Text network analysis and topic modeling.

BACKGROUND: With technological and scientific advancement, people are being increasingly exposed to electromagnetic fields, particularly from portable devices such as mobile phones. However, there is currently no consensus regarding the health effects of electromagnetic field exposure, despite the large amount of research conducted on this topic. This study aimed to understand the knowledge structure and trend of electromagnetic field and health research through text network analysis and topic modeling. METHODS: PubMed, Embase, and Cochrane were searched, and 3,880 articles published before June 2021 were identified. We explored the main keywords and research topics regarding electromagnetic fields and human health by constructing a network of keywords. A social network analysis program was used to analyze the data, visualize the network, and perform topic modeling. RESULTS: Four keywords, "exposure," "effect," "cell," and "cancer," were highly correlated to other keywords and formed each colony in the knowledge structure of research on electromagnetic fields and health. Five topics were derived from topic modeling: cell research, research on the adaption of MRI, health effects of mobile phones, pain therapy, and exposure measurement. Cell research has been continuously performed, and many studies have been conducted on the health effects of mobile phones since 2000. CONCLUSIONS: These findings will assist in gaining insights into and understanding changes in research on the health effects of electromagnetic fields, and suggest important areas and directions for future research.

Fairness in Mobile Phone-Based Mental Health Assessment Algorithms: Exploratory Study.

BACKGROUND: Approximately 1 in 5 American adults experience mental illness every year. Thus, mobile phone-based mental health prediction apps that use phone data and artificial intelligence techniques for mental health assessment have become increasingly important and are being rapidly developed. At the same time, multiple artificial intelligence-related technologies (eg, face recognition and search results) have recently been reported to be biased regarding age, gender, and race. This study moves this discussion to a new domain: phone-based mental health assessment algorithms. It is important to ensure that such algorithms do not contribute to gender disparities through biased predictions across gender groups. OBJECTIVE: This research aimed to analyze the susceptibility of multiple commonly used machine learning approaches for gender bias in mobile mental health assessment and explore the use of an algorithmic disparate impact remover (DIR) approach to reduce bias levels while maintaining high accuracy. METHODS: First, we performed preprocessing and model training using the data set (N=55) obtained from a previous study. Accuracy levels and differences in accuracy across genders were computed using 5 different machine learning models. We selected the random forest model, which yielded the highest accuracy, for a more detailed audit and computed multiple metrics that are commonly used for fairness in the machine learning literature. Finally, we applied the DIR approach to reduce bias in the mental health assessment algorithm. RESULTS: The highest observed accuracy for the mental health assessment was 78.57%. Although this accuracy level raises optimism, the audit based on gender revealed that the performance of the algorithm was statistically significantly different between the male and female groups (eg, difference in accuracy across genders was 15.85%; P<.001). Similar trends were obtained for other fairness metrics. This disparity in performance was found to reduce significantly after the application of the DIR approach by adapting the data used for modeling (eg, the difference in accuracy across genders was 1.66%, and the reduction is statistically significant with P<.001). CONCLUSIONS: This study grounds the need for algorithmic auditing in phone-based mental health assessment algorithms and the use of gender as a protected attribute to study fairness in such settings. Such audits and remedial steps are the building blocks for the widespread adoption of fair and accurate mental health assessment algorithms in the future.

Diagnostic Test Accuracy of the Beck Depression Inventory for Detecting Major Depression in Adolescents: A Systematic Review and Meta-Analysis.

Major depressive disorder in adolescents is closely linked to poor social, cognitive, and academic outcomes, including suicidality. The Beck Depression Inventory (BDI), a screening tool, is one of the most widely used instruments for detecting depression; however, its diagnostic test accuracy has not yet been thoroughly examined. This study, therefore, aimed to systematically review and perform a meta-analysis to evaluate the accuracy of the BDI for detecting depression in adolescents. In August 2020, a search was conducted in the EMBASE, MEDLINE, CINAHL, and PsycArticles databases, and following a review against predefined eligibility criteria, 22 studies were finally included. The quality of the included articles was evaluated, and a hierarchical regression model was used to calculate the pooled estimates of sensitivity and specificity; 73.0% (95% CI; 62.0%, 81.8%) and 80.3% (72.8%, 86.1%) in cutoff 16, respectively. The findings indicated the BDI is a reliable and useful tool to screen adolescents' depression.

Identifying the Knowledge Structure and Trends of Outreach in Public Health Care: A Text Network Analysis and Topic Modeling.

Outreach programs are considered a key strategy for providing services to underserved populations and play a central role in delivering health-care services. To address this challenge, knowledge relevant to global health outreach programs has recently been expanded. The aims of this study were to analyze the knowledge structure and understand the trends in aspects over time and across regions using text network analysis with NetMiner 4.0. Data analysis by frequency, time and region showed that the central keywords such as patient, care, service and community were found to be highly related to the area, target population, purpose and type of services within the knowledge structure of outreach. As a result of performing topic modeling, knowledge structure in this area consisted of five topics: patient-centered care, HIV care continuum, services related to a specific disease, community-based health-care services and research and education on health programs. Our results newly identified that patient-centered care, specific disease and population have been growing more crucial for all times and countries by the examination of major trends in health-care related outreach research. These findings help health professionals, researchers and policymakers in nursing and public health fields in understanding and developing health-care-related outreach practices and suggest future research direction.

Exposure to extremely low-frequency magnetic fields and childhood cancer: A systematic review and meta-analysis.

BACKGROUND: Extremely low frequency magnetic fields (ELF-MFs) are classified as a possible carcinogenic factor (Group 2B). This study assessed the association between ELF-MFs and childhood cancer through a systematic review and meta-analysis. METHODS: Three databases were searched in January 2020. We conducted a meta-analysis for the association between the ELF-MFs exposure level and childhood cancer. RESULTS: A total of 33 studies were identified. Thirty studies with 186,223 participants were included in the meta-analysis. Children exposed to 0.2-, 0.3-, and 0.4-µT ELF-MFs had a 1.26 (95% confidence interval [CI] 1.06-1.49), 1.22 (95% CI 0.93-1.61), and 1.72 (95% CI 1.25-2.35) times higher odds of childhood leukemia. In childhood brain tumors, children exposed to 0.2-µT had a 0.95 (95% CI 0.59-1.56) times higher odds, and those exposed to 0.4-µT ELF-MFs had a 1.25 (95% CI 0.93-1.61). Children exposed to 0.2- and 0.4-µT ELF-MFs had a 1.10 (95% CI 0.70-1.75) and 2.01 (95% CI 0.89-4.52) times higher odds of any childhood cancers. CONCLUSIONS: Significant associations were observed between exposure to ELF-MFs and childhood leukemia. Furthermore, a possible dose-response effect was also observed.

Design and Implementation of Intelligent Sports Training System for College Students' Mental Health Education.

In order to solve the problems of poor physical fitness of college students and low efficiency of college sport venues' management, an intelligent sports management system based on deep learning technology is designed by using information technology and human-computer interaction under artificial intelligence. Based on the Browser/Server (B/S) structure, the intelligent sports management system is constructed. The basic framework of Spring Cloud is used to integrate the framework and components of each part, and a distributed microservice system is built. The artificial intelligence recommendation algorithm is used to analyze the user's age, body mass index (BMI), and physical health status, and recommend sports programs suitable for students, thus realizing the intelligent sports program recommendation function. At the same time, the recommendation algorithm is used to complete the course recommendation according to the students' preferences, teaching distance, opening time, course evaluation, and other indexes, and the course registration system is constructed; after the analysis of the entity and the relationship between the entities of the intelligent sports system, the database relational model of the system is designed with the entity relationship (E-R) diagram. The results of the functional test show that the system can run well. In conclusion, the sports training environment instructional system based on artificial intelligence and deep learning technology can meet the teaching needs of colleges, improve the sports' quality for college students, and promote psychological education.

Recent Advances in Anti-Metastatic Approaches of Herbal Medicines in 5 Major Cancers: From Traditional Medicine to Modern Drug Discovery.

Metastasis is the main cause of cancer-related death. Despite its high fatality, a comprehensive study that covers anti-metastasis of herbal medicines has not yet been conducted. The aim of this study is to investigate and assess the anti-metastatic efficacies of herbal medicines in the five major cancers, including lung, colorectal, gastric, liver, and breast cancers. We collected articles published within five years using PubMed, Google Scholar, and Web of Science with "cancer metastasis" and "herbal medicine" as keywords. Correspondingly, 16 lung cancer, 23 colorectal cancer, 10 gastric cancer, 10 liver cancer, and 18 breast cancer studies were systematically reviewed. The herbal medicines attenuated metastatic potential targeting various mechanisms such as epithelial mesenchymal transition (EMT), reactive oxygen species (ROS), and angiogenesis. Specifically, the drugs regulated metastasis related factors such as matrix metalloproteinase (MMP), serine-threonine protein kinase/extracellular regulated protein kinase (AKT/ERK), angiogenic factors, and chemokines. Overall, the present study is the first review, comprehensively investigating the anti-metastasis effect of herbal medicines on five major cancers, providing the experimental models, doses and durations, and mechanisms. Herbal medicines could be a potent candidate for anti-metastatic drugs.

The Delirium Observation Screening Scale: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy.

Delirium is a reversible impairment of metabolism in the human brain. Early detection is important, and an effective screening tool for nurses is crucial. The Delirium Observation Screening (DOS) scale is one such screening tool; however, its diagnostic test accuracy has not yet been thoroughly examined. This study, therefore, aimed to evaluate the accuracy of the scale through a systematic review and meta-analysis. In July 2019, a search was conducted in the MEDLINE, CINAHL, Embase, and PsycARTICLES databases, and following a review against pre-defined eligibility criteria, eight studies were finally included. The quality assessment tool of diagnostic accuracy studies was applied to each study and a hierarchical regression model was used to calculate the pooled estimates of sensitivity (90%; 76%-97%, CI 95%) and specificity (92%; 88%-94%, CI 95%). The findings indicated a high diagnostic test accuracy for the DOS scale.

Development and Validation of the Medication Safety Competence Scale for Nurses.

Nurses are the most important health care personnel for medication safety. A scale to measure nurse medication competency, such as the Medication Safety Competence Scale (MSCS), would move research forward. Preliminary items were developed through a literature review and in-depth interviews. Content validity was established by ten experts. Nurses (n = 607) participated in a survey to evaluate the validity and reliability of the scale. Exploratory and confirmatory factor analyses and correlation analyses were conducted to assess construct, concurrent, and criterion validity. The 36 items and 6 factors were derived with the exploratory factor analysis, which accounted for 63.2% of the variance. The confirmatory factor analysis revealed that the hypothesized factor structure was a good fit. Criterion and discriminant validity were present. The internal consistency of the MSCS was .97, and the test-retest reliability was .78. The MSCS is a valid and reliable instrument to measure nurses' medication safety competence.

Alpha-beta transition induced by C18-conjugation of polyalanine and its implication in aqueous solution behavior of poly(ethylene glycol)-polyalanine block copolymers.

BACKGROUND: The aqueous solution behavior of thermosensitive PEG-PA block copolymers as well as secondary structure of PA is expected to significantly change through modification of the hydrophobic PA by long chain alkyl (C18) groups with different configurations. METHOD: Oleoyl and stearoyl (C18) groups were conjugated to poly(ethylene glycol)-poly(L-alanine) (PEG-PA; EG45A16) diblock copolymers to compare their conjugation effect on nano-assemblies and corresponding aqueous solution behavior of the polymers. RESULTS: Due to the nature of a hydrophilic PEG block and a hydrophobic PA or C18-modified PA, PEG-PA, oleoyl group-conjugated PEG-PA (PEG-PAO), and stearoyl group-conjugated PEG-PA (PEG-PAS) block copolymers form micelles in water. Compared with PEG-PA, the micelle size of PEG-PAO and PEG-PAS increased. Circular dichroism and FTIR spectra of aqueous polymer solutions showed that ß sheet content increased, whereas α helix content decreased by C18 modification of PEG-PA. PEG-PAS showed better performance in ice crystallization inhibition than PEG-PAO. The sol-to-gel transition temperatures of aqueous PEG-PAO solutions were 25-37 °C higher than those of aqueous PEG-PA solutions, whereas aqueous PEG-PAS solutions remained as gels in the temperature range of 0-80 °C. 1H-NMR spectra indicated that the oleoyl groups increased core mobility, whereas stearoyl groups decreased the core mobility of the micelles in water. The difference in micromobility between PAO and PAS interfered or promoted gelation of the aqueous polymer solutions, respectively. CONCLUSIONS: This study suggests that a hydrophobic C18-modification of polypeptide induces α helix-to-ß sheet transition of the polypeptide; however, aqueous solution behaviors including ice recrystallization inhibition and gelation are significantly affected by the nature of the hydrophobic molecule.

Development and Evaluation of Clinical Practice Guideline for Delirium in Long-Term Care.

Delirium is highly prevalent and leads to several bad outcomes for older long-term care (LTC) residents. For a more successful translation of delirium knowledge, Clinical Practice Guidelines (CPGs) tailored to LTC should be developed and applied based on the understanding of the barriers to implementation. This study was conducted to develop a CPG for delirium in LTC and to determine the barriers perceived by healthcare professionals related to the implementation of the CPG. We followed a structured, evidence- and theory-based procedure during the development process. After a systematic search, quality appraisal, and selection for eligible up-to-date CPGs for delirium, the recommendations applicable to the LTC were drafted, evaluated, and confirmed by an external group of experts. To evaluate the barriers to guideline uptake from the users' perspectives, semi-structured interviews were conducted which resulted in four major themes: (1) a lack of resources, (2) a tendency to follow mindlines rather than guidelines, (3) passive attitudes, and (4) misunderstanding delirium care in LTC. To minimize adverse prognoses through prompt delirium care, the implementation of a CPG with an approach that comprehensively considers various barriers at the system, practice, healthcare professional, and patients/family levels is necessary.

Regeneration of a full-thickness defect in rotator cuff tendon with umbilical cord-derived mesenchymal stem cells in a rat model.

Although rotator cuff disease is a common cause of shoulder pain, there is still no treatment method that could halt or reveres its development and progression. The purpose of this study was to investigate the efficacy of umbilical cord-derived mesenchymal stem cells (UC MSCs) on the regeneration of a full-thickness rotator cuff defect (FTD) in a rat model. We injected either UC MSCs or saline to the FTD and investigated macroscopic, histological and biomechanical results and cell trafficking. Treatment with UC MSCs improved macroscopic appearance in terms of tendon thickness at two weeks, and inflammation, defect size, swelling/redness and connection surrounding tissue and slidability at four weeks compared to the saline group. Histologically, UC MSCs induced the tendon matrix formation recovering collagen organization, nuclear aspect ratio and orientation angle of fibroblast as well as suppressing cartilage-related glycosaminoglycan compared to saline group at four weeks. The UC MSCs group also improved ultimate failure load by 25.0% and 19.0% and ultimate stress by 27.3% and 26.8% at two and four weeks compared to saline group. UC MSCs labeled with PKH26 exhibited 5.3% survival at four weeks compared to three hours after injection. This study demonstrated that UC MSCs regenerated the FTD with tendon tissue similar properties to the normal tendon in terms of macroscopic, histological and biomechanical characteristics in a rat model.

Diagnostic Test Accuracy of the 4AT for Delirium Detection: A Systematic Review and Meta-Analysis.

Under-recognition of delirium is an international problem. For the early detection of delirium, a feasible and valid screening tool for healthcare professionals is needed. This study aimed to present a scientific reason for using the 4 'A's Test (4AT) through a systematic review and meta-analysis of studies on the diagnostic test accuracy. We systematically searched articles in the EMBASE, MEDLINE, CINAHL, and PsycINFO databases and selected relevant articles on the basis of the predefined inclusion criteria. The quality of the included articles was evaluated using the Quality Assessment of the Diagnostic Accuracy Studies-2 tool. We estimated the pooled values of diagnostic test accuracy by employing the bivariate model and the hierarchical summary receiver operating characteristic (HSROC) model in data synthesis. A total of 3729 patients of 13 studies were included in the analysis. The pooled estimates of sensitivity and specificity of the 4AT were 81.5% (95% confidence interval: 70.7%, 89.0%) and 87.5% (79.5%, 92.7%), respectively. Given the 4AT's evidence of accuracy and practicality, we suggest healthcare professionals to utilize this tool for routine screening of delirium. However, for detecting delirium in the dementia population, further work is required to evaluate the 4AT with other cut-off points or scoring methods in order for it to be more sensitive and specific.