Postgraduate medicine
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Postgraduate medicine · Apr 2024
Impact of on-call shifts on working memory and the role of burnout, sleep, and mental well-being in trainee physicians.
Optimal cognitive functions, including working memory (WM), are crucial to enable trainee physicians to perform and excel in their clinical practice. Several risk factors, including on-call shifts, poor mental health, burnout, and sleep problems, can impair clinical practice in trainee physicians, potentially through cognitive impairment; however, these associations have not been fully explored. ⋯ Working more on-call shifts is associated with compromised WM. Trainee physicians who experienced more depressive symptoms and burnout had worse WM.
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Postgraduate medicine · Apr 2024
Is the fluoroquinolone combination necessary for empirical antibiotic regimen in severe community-acquired pneumonia?
This study aimed to assess whether superior clinical outcomes can be attained through piperacillin/tazobactam (TZP)+fluoroquinolone (FQ) combination therapy for severe community-acquired pneumonia (CAP) compared to TZP monotherapy. ⋯ In patients with severe CAP, there were no differences in the clinical outcomes, including mortality, between the TZP and FQ combination therapy and TZP monotherapy. FQ combination was not significantly associated with in-hospital mortality.
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Postgraduate medicine · Apr 2024
ReviewOpportunities to overcome underutilization of enhanced insulin delivery technologies in people with type 2 diabetes: a narrative review.
Use of innovative technologies such as continuous glucose monitoring (CGM) and insulin delivery systems have been shown to be safe and effective in helping patients with diabetes achieve significantly improved glycemic outcomes compared to their previous therapies. However, these technologies are underutilized in many primary care practices. This narrative review discusses some of the clinical and economic benefits of tubeless insulin delivery devices and discusses how this technology can overcome the main obstacles inherent to use of conventional insulin delivery devices.
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Postgraduate medicine · Apr 2024
A machine learning stacking model accurately estimating gastric fluid volume in patients undergoing elective sedated gastrointestinal endoscopy.
The current point-of-care ultrasound (POCUS) assessment of gastric fluid volume primarily relies on the traditional linear approach, which often suffers from moderate accuracy. This study aimed to develop an advanced machine learning (ML) model to estimate gastric fluid volume more accurately. ⋯ The stacking model and its web calculator can serve as practical tools for accurately estimating gastric fluid volume in patients undergoing elective sedated GIE. It is recommended that anesthesiologists measure D1 and D2 in the patient's RLD position.