Hospital-acquired malnutrition: point prevalence, risk identifiers and utility of a digital Dashboard to identify high-risk, long-stay patients in five Australian facilities.

Background: There are limited hospital-acquired malnutrition (HAM) studies among the plethora of malnutrition literature, and a few studies utilise electronic medical records to assist with malnutrition care. This study therefore aimed to determine the point prevalence of HAM in long-stay adult patients across five facilities, whether any descriptors could assist in identifying these patients and whether a digital Dashboard accurately reflected 'real-time' patient nutritional status.

Methods: HAM was defined as malnutrition first diagnosed >14 days after hospital admission.

Timing along the cardiac cycle modulates neural signals of reward-based learning.

Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations - absolute and signed prediction errors.

Effectiveness of a telehealth-delivered clinician-supported exercise and weight loss program for hip osteoarthritis - protocol for the Better Hip randomised controlled trial.

Background: Hip osteoarthritis (OA) is a leading cause of chronic pain and disability worldwide. Self-management is vital with education, exercise and weight loss core recommended treatments. However, evidence-practice gaps exist, and service models that increase patient accessibility to clinicians who can support lifestyle management are needed.

PEPS: Polygenic Epistatic Phenotype Simulation.

Genetic data is limited and generating new datasets is often an expensive, time-consuming process, involving countless moving parts to genotype and phenotype individuals. While sharing data is beneficial for quality control and software development, privacy and security are of utmost importance. Generating synthetic data is a practical solution to mitigate the cost, time and sensitivities that hamper developers and researchers in producing and validating novel biotechnological solutions to data intensive problems.