Publications by authors named "A F Arafat"
Burnout is a significant issue among healthcare professionals, particularly nurses, due to high workloads and emotional demands. However, limited research has explored burnout among primary healthcare nurses in Saudi Arabia, who play a vital role in healthcare delivery. This study aims to address this gap by investigating burnout levels and their association with anxiety, depression and self-efficacy among primary healthcare nurses.
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- Two-dimensional TiC MXene is gaining attention as a lithium-ion battery electrode due to its excellent ion transport and lithium absorption capabilities.
- A molecular dynamics simulation study shows that TiC MXene exhibits better tensile strength and elasticity along zigzag directions, while armchair-oriented TiC MXene demonstrates greater fracture strain under certain conditions.
- The study highlights that temperature and strain rate affect the material's mechanical properties differently, and the presence of carbon vacancies significantly weakens the elastic modulus of TiC MXene.
Background: It is controversial whether pulmonary function testing should be performed routinely in cardiac surgery patients. The aim of our study was to focus on patients who have congestive heart failure, caused by left ventricular dysfunction or left-sided heart valve disease, and study the prognostic value of performing preoperative pulmonary function testing on their postoperative outcomes.
Methods: This is a retrospective propensity score matched study that included 366 patients with congestive heart failure who underwent cardiac surgery and had preoperative pulmonary function test.
Article Synopsis
- This study focused on acute myocardial infarction complicated by cardiogenic shock (AMI-CS) in the Gulf region, addressing a lack of data by analyzing 1,513 patients from 2020 to 2022.
- The incidence of AMI-CS was found to be 4.1%, with a high in-hospital mortality rate of 45.5%, and patients primarily presented with ST-elevation MI.
- Key risk factors for increased hospital mortality included previous coronary artery bypass grafts, chronic kidney disease, and SCAI shock stages D and E, with a 12-month survival rate of 51.49%.*
Background: Risk stratification for patients undergoing coronary artery bypass surgery (CABG) for left main coronary artery (LMCA) disease is essential for informed decision-making. This study explored the potential of machine learning (ML) methods to identify key risk factors associated with mortality in this patient group.
Methods: This retrospective cohort study was conducted on 866 patients from the Gulf Left Main Registry who presented between 2015 and 2019.