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International Journal of Nursing... Dec 2022Nurse-surgeons have been performing surgeries for decades. Yet, their impact on perioperative clinical outcomes has not been explored in detail. (Review)
Review
BACKGROUND
Nurse-surgeons have been performing surgeries for decades. Yet, their impact on perioperative clinical outcomes has not been explored in detail.
OBJECTIVE
To investigate the impact of nurse-surgeons on patient-centred outcomes.
DESIGN
Systematic review.
METHOD
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram and checklist for systematic reviews were used as the screening and reporting guideline. CINAHL, Cochrane Library, MEDLINE, and PubMed databases were searched for articles that fit the review's eligibility criteria. A combination of Medical Subject Headings, keywords and filters for each database were used. Following screening and full text review, the Mixed Methods Appraisal Tool was used for quality assessment and the Grading of Recommendations, Assessment, Development and Evaluations framework for certainty and confidence assessment. Narrative synthesis was used to report the findings due to the design heterogeneity of the included studies.
RESULTS
Forty-eight ( = 48) patient-centred outcomes were identified from 25 included studies. These outcomes were grouped into four categories: patient satisfaction and experience; waiting list; perioperative complications; and quality of surgical care. Patient satisfaction and experience was rated high to very high in 16 studies; none reported patient dissatisfaction. Waiting lists improved in eight studies. Perioperative complications were none to very low in nine studies. Mortality rates in the nurse-surgeon group were better than the physician group in three studies. The quality of care in the performance of surgeries by nurse-surgeons was either similar or better than physicians in ten studies.
CONCLUSIONS
Nurse-surgeons performed safe, satisfactory, and high-quality surgeries with minimal perioperative complications similar to physicians. The use of nurse-surgeons has significantly reduced waiting lists regardless of surgical speciality. Policies around nurse-surgeon practice needs to be developed at national and international levels to streamline the delivery of much needed surgical services amidst the coronavirus pandemic in the areas of cancer diagnostic surgeries, emergency surgeries, minor surgeries, and remote and rural health.
PubMed: 38745634
DOI: 10.1016/j.ijnsa.2022.100086 -
Social Network Analysis and Mining 2022Emerging of social media creates inconsistencies in online news, which causes confusion and uncertainty for consumers while making decisions regarding purchases. On the...
Emerging of social media creates inconsistencies in online news, which causes confusion and uncertainty for consumers while making decisions regarding purchases. On the other hand, in existing studies, there is a lack of empirical and systematic examination observed in terms of inconsistency regarding reviews. The spreading of fake news and disinformation on social media platforms has adverse effects on stability and social harmony. Fake news is often emerging and spreading on social media day by day. It results in influencing or annoying and also misleading nations or societies. Several studies aim to recognize fake news from real news on online social media platforms. Accurate and timely detection of fake news prevents the propagation of fake news. This paper aims to conduct a review on fake news detection models that is contributed by a variety of machine learning and deep learning algorithms. The fundamental and well-performing approaches that existed in the past years are reviewed and categorized and described in different datasets. Further, the dataset utilized, simulation platforms, and recorded performance metrics are evaluated as an extended review model. Finally, the survey expedites the research findings and challenges that could have significant implications for the upcoming researchers and professionals to improve the trust worthiness of automated fake news detection models.
PubMed: 36407554
DOI: 10.1007/s13278-022-00995-5 -
F1000Research 2023A systematic literature review was conducted to summarize the overall thermal performance of different gasified cooking stoves from the available literature. For this...
A systematic literature review was conducted to summarize the overall thermal performance of different gasified cooking stoves from the available literature. For this purpose, available studies from the last 14 years (2008 to 2022) were searched using different search strings. After screening, a total of 28 articles were selected for this literature review. Scopus, Google Scholar, and Web of Science databases were used as search strings by applying "Gasifier cooking stove" AND "producer gas cooking stove" AND "thermal performance" keywords. This review uncovers different gasified cooking stoves, cooking fuels, and fabrication materials besides overall thermal performances. The result shows that the overall thermal performance of different gasified cooking stoves was 5.88% to 91% depending on the design and burning fuels. The premixed producer gas burner with a swirl vane stove provided the highest overall thermal performance range, which was 84% to 91%, and the updraft gasified stove provided the lowest performance, which was 5.88% to 8.79%. The result also demonstrates that the wood pellets cooking fuel provided the highest thermal performance and corn straw briquette fuel provided the lowest for gasified cooking stoves. The overall thermal performance of wood pellets was 38.5% and corn straw briquette was 10.86%.
Topics: Air Pollution, Indoor; Cooking; Household Articles; Particulate Matter
PubMed: 37484517
DOI: 10.12688/f1000research.126890.2 -
International Journal of Medical... Sep 2023Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity... (Review)
Review
BACKGROUND
Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid developments the last few years that there's currently no overview of it. Moreover, it is unclear how these models and tools have been translated into clinical practice. We aim to synthesize and review these developments.
METHODS
We reviewed literature from 2010 to date, searching PubMed, Scopus, the Association of Computational Linguistics (ACL), and Association of Computer Machinery (ACM) libraries for studies of NLP systems performing general-purpose (i.e., not disease- or treatment-specific) information extraction and relation extraction tasks in unstructured clinical text (e.g., discharge summaries).
RESULTS
We included in the review 94 studies with 30 studies published in the last three years. Machine learning methods were used in 68 studies, rule-based in 5 studies, and both in 22 studies. 63 studies focused on Named Entity Recognition, 13 on Relation Extraction and 18 performed both. The most frequently extracted entities were "problem", "test" and "treatment". 72 studies used public datasets and 22 studies used proprietary datasets alone. Only 14 studies defined clearly a clinical or information task to be addressed by the system and just three studies reported its use outside the experimental setting. Only 7 studies shared a pre-trained model and only 8 an available software tool.
DISCUSSION
Machine learning-based methods have dominated the NLP field on information extraction tasks. More recently, Transformer-based language models are taking the lead and showing the strongest performance. However, these developments are mostly based on a few datasets and generic annotations, with very few real-world use cases. This may raise questions about the generalizability of findings, translation into practice and highlights the need for robust clinical evaluation.
Topics: Humans; Natural Language Processing; Machine Learning; Language; Information Storage and Retrieval; PubMed
PubMed: 37295138
DOI: 10.1016/j.ijmedinf.2023.105122 -
Cell and Tissue Banking Dec 2016For successful transplantation, allografts should be free of microorganisms that may cause harm to the allograft recipient. Before or during recovery and subsequent... (Review)
Review
For successful transplantation, allografts should be free of microorganisms that may cause harm to the allograft recipient. Before or during recovery and subsequent processing, tissues can become contaminated. Effective tissue recovery methods, such as minimizing recovery times (<24 h after death) and the number of experienced personnel performing recovery, are examples of factors that can affect the rate of tissue contamination at recovery. Additional factors, such as minimizing the time after asystole to recovery and the total time it takes to perform recovery, the type of recovery site, the efficacy of the skin prep performed immediately prior to recovery of tissue, and certain technical recovery procedures may also result in control of the rate of contamination. Due to the heterogeneity of reported recovery practices and experiences, it cannot be concluded if the use of other barriers and/or hygienic precautions to avoid contamination have had an effect on bioburden detected after tissue recovery. Qualified studies are lacking which indicates a need exists for evidence-based data to support methods that reduce or control bioburden.
Topics: Allografts; Cell Culture Techniques; Decontamination; Humans; Specimen Handling; Sterilization; Tissue Banks; Transplantation, Homologous
PubMed: 27761677
DOI: 10.1007/s10561-016-9590-5 -
Jornal de Pediatria 2016This systematic review aimed to verify the available scientific evidence on the clinical performance and diagnostic accuracy of nutritional screening tools in... (Review)
Review
OBJECTIVE
This systematic review aimed to verify the available scientific evidence on the clinical performance and diagnostic accuracy of nutritional screening tools in hospitalized pediatric patients.
DATA SOURCE
A search was performed in the Medline (National Library of Medicine United States), LILACS (Latin American and Caribbean Health Sciences), PubMed (US National Library of Medicine National Institutes of Health), in the SCIELO (Scientific Electronic Library Online), through CAPES portal (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), bases Scopus e Web of Science. The descriptors used in accordance with the Descriptors in Health Sciences (DeCS)/Medical Subject Headings (MeSH) list were "malnutrition", "screening", and "pediatrics", as well as the equivalent words in Portuguese.
SUMMARY OF THE FINDINGS
The authors identified 270 articles published between 2004 and 2014. After applying the selection criteria, 35 were analyzed in full and eight articles were included in the systematic review. We evaluated the methodological quality of the studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS). Five nutritional screening tools in pediatrics were identified. Among these, the Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP) showed high sensitivity, almost perfect inter-rater agreement and between the screening and the reference standard; the Screening Tool Risk on Nutritional Status and Growth (STRONGkids) showed high sensitivity, lower percentage of specificity, substantial intra-rater agreement, and ease of use in clinical practice.
CONCLUSIONS
The studies included in this systematic review showed good performance of the nutritional screening tools in pediatrics, especially STRONGkids and STAMP. The authors emphasize the need to perform for more studies in this area. Only one tool was translated and adapted to the Brazilian pediatric population, and it is essential to carry out studies of tool adaptation and validation for this population.
Topics: Adolescent; Child; Child, Hospitalized; Child, Preschool; Female; Humans; Infant; Male; Malnutrition; Nutrition Surveys; Nutritional Status; Reproducibility of Results; Risk Assessment; Risk Factors; Sensitivity and Specificity
PubMed: 26859247
DOI: 10.1016/j.jped.2015.08.011 -
Biology of Sport Sep 2022Since the analysis of worst-case scenarios (WCS) has been increasing knowledge about match demands and possible impacts for the training process, it seems important to... (Review)
Review
Since the analysis of worst-case scenarios (WCS) has been increasing knowledge about match demands and possible impacts for the training process, it seems important to summarize the evidence to provide useful information for the soccer community. Thus, the purpose of this systematic review was to summarize the evidence about WCS in professional soccer. A systematic review of PubMed, SPORTDiscus, and FECYT (Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO) was performed according to the guidelines for performing systematic reviews in sport science. From the 85 studies initially identified, 12 were fully reviewed, and their outcome measures were extracted and analyzed. There was an inverse relationship between the duration of WCS windows and running output during match play. Occurrences of WCS during soccer matches were also position-dependent across studies, at least, when analyzing performance with the total distance covered variable, although different outputs were identified between women and men players. Future research should consider analyzing the impact of contextual variables (match status, team formation, and match location) on peak match values and the weight of these moderators.
PubMed: 35959320
DOI: 10.5114/biolsport.2022.107022 -
Frontiers in Physiology 2021The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus...
The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms "fatigue," "drowsiness," "vigilance," or "alertness" in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (T), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.
PubMed: 34975541
DOI: 10.3389/fphys.2021.790292 -
Diagnostic and Interventional Imaging 2024The purpose of this study was to systematically review the reported performances of ChatGPT, identify potential limitations, and explore future directions for its... (Review)
Review
PURPOSE
The purpose of this study was to systematically review the reported performances of ChatGPT, identify potential limitations, and explore future directions for its integration, optimization, and ethical considerations in radiology applications.
MATERIALS AND METHODS
After a comprehensive review of PubMed, Web of Science, Embase, and Google Scholar databases, a cohort of published studies was identified up to January 1, 2024, utilizing ChatGPT for clinical radiology applications.
RESULTS
Out of 861 studies derived, 44 studies evaluated the performance of ChatGPT; among these, 37 (37/44; 84.1%) demonstrated high performance, and seven (7/44; 15.9%) indicated it had a lower performance in providing information on diagnosis and clinical decision support (6/44; 13.6%) and patient communication and educational content (1/44; 2.3%). Twenty-four (24/44; 54.5%) studies reported the proportion of ChatGPT's performance. Among these, 19 (19/24; 79.2%) studies recorded a median accuracy of 70.5%, and in five (5/24; 20.8%) studies, there was a median agreement of 83.6% between ChatGPT outcomes and reference standards [radiologists' decision or guidelines], generally confirming ChatGPT's high accuracy in these studies. Eleven studies compared two recent ChatGPT versions, and in ten (10/11; 90.9%), ChatGPTv4 outperformed v3.5, showing notable enhancements in addressing higher-order thinking questions, better comprehension of radiology terms, and improved accuracy in describing images. Risks and concerns about using ChatGPT included biased responses, limited originality, and the potential for inaccurate information leading to misinformation, hallucinations, improper citations and fake references, cybersecurity vulnerabilities, and patient privacy risks.
CONCLUSION
Although ChatGPT's effectiveness has been shown in 84.1% of radiology studies, there are still multiple pitfalls and limitations to address. It is too soon to confirm its complete proficiency and accuracy, and more extensive multicenter studies utilizing diverse datasets and pre-training techniques are required to verify ChatGPT's role in radiology.
Topics: Humans; Radiology; Forecasting
PubMed: 38679540
DOI: 10.1016/j.diii.2024.04.003 -
Frontiers in Behavioral Neuroscience 2021According to the neural efficiency hypothesis (NEH), professionals have more effective cortical functions in cognitive tasks. This study is focusing on providing a...
According to the neural efficiency hypothesis (NEH), professionals have more effective cortical functions in cognitive tasks. This study is focusing on providing a systematic review of sport-related NEH studies with functional neuroimaging or brain stimulation while performing a sport-specific task, with the aim to answer the question: How does long-term specialized training change an athlete's brain and improve efficiency? A total of 28 studies ( = 829, Experimental Group = 430) from 2001 to 2020 (Median = 2014, = 5.43) were analyzed and results were organized into four different sections: expert-novice samples, perceptual-cognitive tasks and neuroimaging technologies, efficiency paradox, and the cluster analysis. Researchers examined a wide range of sport-specific videos and multiple object tracking (MOT) specific to 18 different sports and utilized blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), and electroencephalogram (EEG). Expert-novice comparisons were often adopted into investigations about the variations in general about optimal-controlled performance, neurophysiology, and behavioral brain research. Experts tended to perform at faster speeds, more accurate motor behavior, and with greater efficiency than novices. Experts report lower activity levels in the sensory and motor cortex with less energy expenditure, experts will possibly be more productive. These findings generally supported the NEH across the studies reviewed. However, an efficiency paradox and proficient brain functioning were revealed as the complementary hypothesis of the NEH. The discussion concentrates on strengths and key limitations. The conclusion highlights additional concerns and recommendations for prospective researchers aiming to investigate a broader range of populations and sports.
PubMed: 34421553
DOI: 10.3389/fnbeh.2021.698555