Journal of evaluation in clinical practice
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College students represent a unique demographic group as they are adults no longer under direct parental care, yet often lack the institutional health support available to more established members of society, which can lead to their health needs being neglected, despite their substantial contributions to blood donation. The objective of this study is to shed light on the health status of college students in Hefei, with a specific focus on transfusion-transmitted diseases. Based on the detailed data analysis, the implementation of some constructive strategies will play a good warning role in improving clinical blood safety and promoting better health monitoring of this population in the future. ⋯ The overall group had prevalence rates of 0.44% for hepatitis B, 0.15% for hepatitis C, 0.02% for HIV, and 0.42% for Treponema pallidum. When focusing on the student cohort, the prevalence rates were 0.17% for hepatitis B, 0.04% for hepatitis C, 0.02% for HIV, and 0.23% for Treponema pallidum. Transmissibility through blood transfusion All donors (%) Students (%) Non-students (%) Any infection 1.23 0.48 1.51 HbsAg 0.44 0.17 0.54 Anti-HCV 0.15 0.04 0.19 HIV Ag/Ab 0.02 0.02 0.02 Anti-TP 0.42 0.23 0.49 Individuals with two or more infectious agents occur more than once in all categories. While it leads to numerical over-representation, such overlap is minimal and statistically insignificant.
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Observational Study
The Effect of Lean Hospital Practices on Nurses' Direct Care Activities: Time and Motion Study.
This study investigates the effects of lean management practices on nurses' direct patient care activities and the interruptions they encounter in healthcare settings. The literature indicates that lean management enhances efficiency and improves patient care. Increased nursing time per patient correlates with better outcomes; however, rising patient loads and frequent interruptions hinder nurses' ability to deliver effective care, jeopardising patient safety. Addressing these inefficiencies is essential, given nurses' critical role in ensuring quality care. ⋯ Lean management effectively reduces waste and improves direct patient care time, enhancing patient safety and care quality. Continuous improvement initiatives in nursing practices are essential for success.
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This study aims to assess the performance of machine learning (ML) techniques in optimising nurse staffing and evaluating the appropriateness of nursing care delivery models in hospital wards. The primary outcome measures include the adequacy of nurse staffing and the appropriateness of the nursing care delivery system. ⋯ While the study lacked direct patient involvement, its goal was to enhance patient care and healthcare efficiency. Future research will aim to incorporate patient and public insights more directly.
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The positive effects of vaccination status on the course of Long COVID symptoms have not been fully elucidated. Our aim is to determine the most common Long COVID symptoms in patients monitored in the COVID-19 follow-up clinic and to examine whether there is a difference between the recovery rates of those who are vaccinated and those who are not vaccinated. ⋯ This study showed that receiving vaccination may be effective in improving Long COVID symptoms. Although there were no statistically significant differences between the inactive vaccine CoronaVac, the mRNA vaccine BNT162b2, and the heterologous (CoronaVac+ BNT162b2) vaccine in terms of reducing Long COVID symptoms, higher recovery rates were detected in those who received the mRNA vaccine BNT162b2.
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3D Magnetic Resonance Imaging (3D-MRI) analysis of brain tumours is an important tool for gathering information needed for diagnosis and disease therapy planning. However, during the brain tumor segmentation process existing techniques have segmentation error while identifying tumor location and extended tumor regions due to improper extraction of initial contour points and overlapping tissue intensity distributions. ⋯ The results obtained for the BraTS2020 and Brain Tumor Detection 2020 data sets showed that the proposed model outperforms existing techniques with excellent precision of 97%, 97.5%, recall of 99%, 97.8%, and accuracy of 95.7%, 98.4%, respectively.