METHODS: We investigated the existing body of evidence and applied Preferred Reporting Items for Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to search records in IEEE, Google scholar, and PubMed databases. We identified 65 papers that were published from 2013 to 2022 and these papers cover 67 different studies. The review process was structured according to the medical data that was used for disease detection. We identified six main categories, namely air flow, genetic, imaging, signals, and miscellaneous. For each of these categories, we report both disease detection methods and their performance.
RESULTS: We found that medical imaging was used in 14 of the reviewed studies as data for automated obstructive airway disease detection. Genetics and physiological signals were used in 13 studies. Medical records and air flow were used in 9 and 7 studies, respectively. Most papers were published in 2020 and we found three times more work on Machine Learning (ML) when compared to Deep Learning (DL). Statistical analysis shows that DL techniques achieve higher Accuracy (ACC) when compared to ML. Convolutional Neural Network (CNN) is the most common DL classifier and Support Vector Machine (SVM) is the most widely used ML classifier. During our review, we discovered only two publicly available asthma and COPD datasets. Most studies used private clinical datasets, so data size and data composition are inconsistent.
CONCLUSIONS: Our review results indicate that Artificial Intelligence (AI) can improve both decision quality and efficiency of health professionals during COPD and asthma diagnosis. However, we found several limitations in this review, such as a lack of dataset consistency, a limited dataset and remote monitoring was not sufficiently explored. We appeal to society to accept and trust computer aided airflow obstructive diseases diagnosis and we encourage health professionals to work closely with AI scientists to promote automated detection in clinical practice and hospital settings.
METHODS: we searched six electronic databases, which include PubMed, Embase, PsycINFO, SciELO, ERIC and AgeLine, between January 2000 and April 2022. Reference lists of the included papers were also manually searched. The COSMIN (CONsensus-based Standards for the selection of health Measurement Instruments) guidelines were used to evaluate the measurement properties and the quality of evidence for each instrument.
RESULTS: 13 instruments from 29 studies were included for evaluation of their measurement properties. Of the 13 reviewed, 6 were on the ability to learn, 3 were on the ability to grow and 4 were on the ability to make decisions. The review found no single instrument that measured all three constructs in unidimensional or multidimensional scales. Many of the instruments were found to have sufficient overall rating on content validity, structural validity, internal consistency and cross-cultural validity. The quality of evidence was rated as low due to a limited number of related validation studies.
CONCLUSION: a few existing instruments to assess the ability to learn, grow and make decisions of older people can be identified in the literature. Further research is needed in validating them against functional, real-world outcomes.
METHODS: Extensive research was conducted using the Scopus database, which is the most authoritative database of research publications and citations, to focus on CKD research between 2003 and 2022, as indicated by title and author keywords. Then, within this vast collection of academic publications, a notable subset of articles was exclusively dedicated to investigating the relationship between CKD and malnutrition. Finally, we performed bibliometric analysis and visualization using VOSviewer 1.6.19 and Microsoft Excel 2013.
RESULTS: Large global research between 2003 and 2022 resulted in 50,588 documents focused on CKD, as indicated by title and author keywords. In this extensive collection of scientific publications, a staggering portion of 823 articles is devoted exclusively to investigating the link between CKD and malnutrition. Further analysis reveals that this body of work consists of 565 articles (68.65%), 221 reviews (26.85%), and 37 miscellaneous entries (4.50%), which encompass letters and editorials. The USA was found to be the most productive country (n = 173; 21.02%), followed by Italy (n = 83; 10.09%), Sweden (n = 56; 6.80%), Brazil (n = 54; 6.56%) and China (n = 51; 6.20%). The most common terms on the map include those related to the topic of (a) malnutrition in hemodialysis patients and predicting factors; terms associated with the (b) impact of malnutrition on cardiovascular risk and complications in CKD patients; and terms related to the (c) dietary protein intake and malnutrition in CKD.
CONCLUSIONS: This study is the first of its kind to analyze CKD and malnutrition research using data from Scopus for visualization and network mapping. Recent trends indicate an increasing focus on protein-energy wasting/malnutrition in hemodialysis patients and predicting factors, dietary protein intake, and malnutrition in CKD. These topics have gained significant attention and reflect the latest scientific advances. Intervention studies are crucial to examining diet therapy's impact on patients with stages 1 to 5 CKD. We hope this study will offer researchers, dietitians and nephrologists valuable information.
METHODS: The study included 382 participants (252 normal voices and 130 dysphonic voices) in the proposed database MVPD. Complete data were obtained for both groups, including voice samples, laryngostroboscopy videos, and acoustic analysis. The diagnoses of patients with dysphonia were obtained. Each voice sample was anonymized using a code that was specific to each individual and stored in the MVPD. These voice samples were used to train and test the proposed OSELM algorithm. The performance of OSELM was evaluated and compared with other classifiers in terms of the accuracy, sensitivity, and specificity of detecting and differentiating dysphonic voices.
RESULTS: The accuracy, sensitivity, and specificity of OSELM in detecting normal and dysphonic voices were 90%, 98%, and 73%, respectively. The classifier differentiated between structural and non-structural vocal fold pathology with accuracy, sensitivity, and specificity of 84%, 89%, and 88%, respectively, while it differentiated between malignant and benign lesions with an accuracy, sensitivity, and specificity of 92%, 100%, and 58%, respectively. Compared to other classifiers, OSELM showed superior accuracy and sensitivity in detecting dysphonic voices, differentiating structural versus non-structural vocal fold pathology, and between malignant and benign voice pathology.
CONCLUSION: The OSELM algorithm exhibited the highest accuracy and sensitivity compared to other classifiers in detecting voice pathology, classifying between malignant and benign lesions, and differentiating between structural and non-structural vocal pathology. Hence, it is a promising artificial intelligence that supports an online application to be used as a screening tool to encourage people to seek medical consultation early for a definitive diagnosis of voice pathology.
METHODOLOGY: Records of patients diagnosed with tuberculosis from 1st January 2018 to 30th September 2019 were retrieved. Sociodemographic and clinical data were extracted. Treatment outcomes and all-cause mortality were recorded at 1 year after diagnosis. Univariate, multivariate, and stepwise regression were used to determine the factors associated with all-cause mortality.
RESULTS: Four-hundred and seventy-one patients were reviewed. The mean age was 46.6 ± 19.7 years. The all-cause mortality rate at one year of diagnosis was 15.3%. Factors identified were age [aOR 1.026 (95% CI: 1.004-1.049)], chronic kidney disease [aOR 3.269 (1.508-7.088)], HIV positive status [aOR 4.743 (1.505-14.953)], active cancer [aOR 5.758 (1.605-20.652)], liver disease [aOR 6.220 (1.028-37.621)], and moderate to advanced chest X-ray findings [aOR 3.851 (1.033-14.354)].
CONCLUSIONS: On average, one in seven patients diagnosed with TB died within a year in a Malaysian tertiary hospital. Identification of this vulnerable group using the associated factors found in this study may help to reduce the risk of mortality through early intervention strategies.
MATERIALS AND METHODS: A systematic search for existing guidelines on TDI was performed on PubMed, EMBASE, CINAHL, Cochrane Library, ProQuest, National Institute for Health Care Excellence, BMJ Best Practice, Trip database, Guideline International Network, Scottish Intercollegiate Guidelines Network, World Health Organisation, Web of Science and 'Ministry of Health worldwide' databases. Four appraisers independently appraised the included CPGs. The AGREE II tool was applied to assess the methodological quality, while AGREE REX assessed the quality of recommendations of the included guidelines.
RESULTS: Of the 7736 titles screened, three guidelines, namely the International Association of Dental Traumatology Guidelines (IADT), and the Italian and Malaysian guidelines, were included for the final analysis. These guidelines were published between 2019 and 2020. The AGREE II analysis demonstrated scores above 80% for the IADT and Italian guidelines for the scope and purpose domain. Overall, the Malaysian guidelines achieved the highest score for all domains. The AGREE REX analysis indicated variability in implementation across the nine items, with five that scored above the midpoint of 4.0 on the response scale. Both the Italian and the IADT guidelines had a similar score for the values and preference domains (36.36%).
CONCLUSIONS: Several deficiencies exist in the methodological quality of existing CPGs on TDI. Future guidelines should consider improvements for domains such as 'rigour of development', 'stakeholder involvement' and 'applicability' to overcome the existing limitations.
MATERIALS AND METHODS: PubMed and Semantic Scholar databases were scoured for articles using 10 search terms. In vitro studies satisfying the inclusion criteria were probed which were meticulously screened and scrutinized for eligibility adhering to the 11 exclusion criteria. The quality assessment tool for in vitro studies (QUIN Tool) containing 12 criteria was employed to assess the risk of bias (RoB).
RESULTS: A total of 48 studies assessing shear bond strength (SBS) and 15 studies evaluating tensile bond strength (TBS) were included in the qualitative synthesis. Concerning SBS, 33.4% moderate and 66.6% high RoB was observed. Concerning TBS, 26.8% moderate and 73.2% high RoB was discerned. Seventeen and two studies assessing SBS and TBS, respectively, were included in meta-analyses.
CONCLUSIONS: Shear bond strength and TBS increased for the primed alloys. Cyclic disulfide primer is best-suited for noble alloys when compared with thiol/thione primers. Phosphoric acid- and phosphonic acid ester-based primers are opportune for base alloys.
CLINICAL SIGNIFICANCE: The alloy-resin interface (ARI) would fail if an inappropriate primer was selected. Therefore, the selection of an appropriate alloy adhesive primer for an alloy plays a crucial role in prosthetic success. This systematic review would help in the identification and selection of a congruous primer for a selected alloy.
OBJECTIVE: The objective of the study is to identify the factors that have had a significant impact on mobility in recent years and currently, and to identify gaps in our understanding of these factors. The study aims to highlight areas where further research is needed and where new and effective solutions are required.
METHODS: The PRISMA methodology was used to conduct a scoping review in the Scopus and Web of Science databases. Papers published from 2007 to 2021 were searched in November 2021. Of these, 52 papers were selected from the initial 788 outputs for the final analysis.
RESULTS: The final selected papers were analyzed, and the key determinants were found to be environmental, physical, cognitive, and psychosocial, which confirms the findings of previous studies. One new determinant is technological. New and effective solutions lie in understanding the interactions between different determinants of mobility, addressing environmental factors, and exploring opportunities in the context of emerging technologies, such as the integration of smart home technologies, design of accessible and age-friendly public spaces, development of policies and regulations, and exploration of innovative financing models to support the integration of assistive technologies into the lives of seniors.
CONCLUSION: For an effective and comprehensive solution to support senior mobility, the determinants cannot be solved separately. Physical, cognitive, psychosocial, and technological determinants can often be perceived as the cause/motivation for mobility. Further research on these determinants can help to arrive at solutions for environmental determinants, which, in turn, will help improve mobility. Future studies should investigate financial aspects, especially since many technological solutions are expensive and not commonly available, which limits their use.
METHODS: Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) were used to report the data for this review. To gather research from the literature, we used recognized academic and scientific databases such SportsDiscus with Full Text, PsycINFO, Cochrane, Scopus, PubMed, and Web of Science. The systematic review only included 22 studies out of the 1,463 that matched all inclusion criteria. The PEDro scale was used to rate each study's quality. 22 research received scores between 3 and 7.
RESULTS: Latin dance has been demonstrated to promote physical health by helping people lose weight, improve cardiovascular health, increase muscle strength and tone, and improve flexibility and balance. Furthermore, Latin dance can benefit mental health by reducing stress, improving mood, social connection, and cognitive function.
CONCLUSIONS: Finding from this systematic review provide substantial evidence that Latin dance has effect on physical and mental health. Latin dance has the potential to be a powerful and pleasurable public health intervention.
SYSTEMATIC REVIEW REGISTRATION: CRD42023387851, https://www.crd.york.ac.uk/prospero .
METHODOLOGY: Several databases, including PubMed (Medline), Cumulative Index to Nursing and Allied Health Literature (CINAHL), BioMed Central, and Google Scholar, were used to review the literature. Information was retrieved using Medical Subject Headings (MeSH) and documents were selected according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). To assess the quality of the selected articles, the Newcastle-Ottawa Scale (NOS) technique was utilized.
RESULTS: A total of 29 papers were selected for final review based on PRISMA guidelines and the NOS quality assessment. Studies have shown that many forms of SimEx commonly used in disaster management including tabletop exercises, functional exercises, and full-scale exercises have their benefits and limitations. There is no doubt that SimEx is an excellent tool for improving disaster planning and response. It is still necessary to give SimEx programs a more rigorous evaluation and to standardize the processes more thoroughly.
CONCLUSIONS: Drills and training can be improved for disaster management, which will enable medical professionals to face the challenges of disaster management in the 21st century.