Patient Safety Culture, Infection Prevention, and Patient Safety in the Operating Room: Health Workers' Perspective.

Introduction: A hospital's patient safety culture affects surgical outcomes. Operating room safety culture has been overlooked despite the importance of patient safety. The AHRQ's Hospital Survey on Patient Safety Culture (HSOPSC) has been used worldwide to assess and enhance patient safety culture. This study examined how patient safety culture and infection prevention effect patient safety in the Operating Room (OR). Methods: This observational study used an online survey and included 143 OR workers. Descriptive statistics and multilinear regression were used to examine how patient safety culture and infection prevention affects level of patient safety. Results: Most responders worked in excellent-accredited general hospitals. Most responders were male, aged between 26 to 40 years old, and had bachelor's degrees. Most were hospital-experienced nurses. Less than half had worked in units for over ten years. Organizational Learning - Continuous Improvement; Teamwork and Handoffs; and Information Exchange had the most positive responses in the OR. However, Staffing, Work Pace, and Patient Safety ranked lowest. Organizational Learning - Continuous Improvement and Hospital Management Support for Infection Prevention Efforts were found to affect OR patient safety level perceptions. Conclusion: According to the findings of our study, the overall patient safety culture in the operating room remains weak which highlights the importance of continuing efforts to improve patient safety in the OR. Further study could be directed to identify organizational learning in infection prevention to enhance the patient safety in the OR.

A Novel Classification Model Using Optimal Long Short-Term Memory for Classification of COVID-19 from CT Images.

The human respiratory system is affected when an individual is infected with COVID-19, which became a global pandemic in 2020 and affected millions of people worldwide. However, accurate diagnosis of COVID-19 can be challenging due to small variations in typical and COVID-19 pneumonia, as well as the complexities involved in classifying infection regions. Currently, various deep learning (DL)-based methods are being introduced for the automatic detection of COVID-19 using computerized tomography (CT) scan images. In this paper, we propose the pelican optimization algorithm-based long short-term memory (POA-LSTM) method for classifying coronavirus using CT scan images. The data preprocessing technique is used to convert raw image data into a suitable format for subsequent steps. Here, we develop a general framework called no new U-Net (nnU-Net) for region of interest (ROI) segmentation in medical images. We apply a set of heuristic guidelines derived from the domain to systematically optimize the ROI segmentation task, which represents the dataset's key properties. Furthermore, high-resolution net (HRNet) is a standard neural network design developed for feature extraction. HRNet chooses the top-down strategy over the bottom-up method after considering the two options. It first detects the subject, generates a bounding box around the object and then estimates the relevant feature. The POA is used to minimize the subjective influence of manually selected parameters and enhance the LSTM's parameters. Thus, the POA-LSTM is used for the classification process, achieving higher performance for each performance metric such as accuracy, sensitivity, F1-score, precision, and specificity of 99%, 98.67%, 98.88%, 98.72%, and 98.43%, respectively.

Adverse Reactions of COVID-19 Vaccines: A Scoping Review of Observational Studies.

The COVID-19 pandemic had a severe global impact. A range of campaigns and activities, including vaccines, are being implemented to counteract this pandemic. Using observational data, the goal of this scoping review is to identify adverse events connected with COVID-19 vaccinations. We conduct a scoping study and searched three databases from the start of the COVID-19 pandemic in 2020 through June 2022. Based on our criteria and searched keywords, the review included eleven papers in total, with the majority of the studies being conducted in developed countries. The study populations varied and included general community populations, healthcare professionals, military forces, and patients with systemic lupus and cancer. This study includes vaccines from Pfizer-BioNTech, Oxford-AstraZeneca, Sinopharm, and Moderna. The COVID-19 vaccine-related adverse events were classified into three types: local side effects, systemic side effects, and other side effects such as allergies. The adverse reactions to COVID-19 vaccines are mild to moderate in severity, with no significant influence or interference in individual daily activities and no unique patterns in cause of death among vaccine-related deaths. According to the findings of these investigations, the COVID-19 vaccine is safe to administer and induces protection. It is vital to convey accurate information to the public about vaccination side effects, potential adverse responses, and the safety level of the vaccines supplied. Multiple strategies must be implemented at the individual, organizational, and population levels to eliminate vaccine hesitance. Future studies could investigate the vaccine's effect on people of various ages and medical conditions.

Recent trends for practical rehabilitation robotics, current challenges and the future.

This paper presents and studies various selected literature primarily from conference proceedings, journals and clinical tests of the robotic, mechatronics, neurology and biomedical engineering of rehabilitation robotic systems. The present paper focuses of three main categories: types of rehabilitation robots, key technologies with current issues and future challenges. Literature on fundamental research with some examples from commercialized robots and new robot development projects related to rehabilitation are introduced. Most of the commercialized robots presented in this paper are well known especially to robotics engineers and scholars in the robotic field, but are less known to humanities scholars. The field of rehabilitation robot research is expanding; in light of this, some of the current issues and future challenges in rehabilitation robot engineering are recalled, examined and clarified with future directions. This paper is concluded with some recommendations with respect to rehabilitation robots.