The Adelaide Score: prospective implementation of an artificial intelligence system to improve hospital and cost efficiency.

Background: The Adelaide Score is an artificial intelligence system that integrates objective vital signs and laboratory tests to predict likelihood of hospital discharge.

Methods: A prospective implementation trial was conducted at the Lyell McEwin Hospital in South Australia. The Adelaide Score was added to existing human, artificial intelligence, and other technological infrastructure for the first 28 days of April 2024 (intervention), and outcomes were compared using parametric, non-parametric and health economic analyses, to those in the first 28 days of April 2023 (control).

A Novel Crosslinking Approach for Biomanufacturing of a Collagen-Based Skin Dermal Template.

Third-degree burns result in extensive damage to the skin's epidermal and dermal layers, with limited treatment options available. Currently, xenogeneic collagen-based skin grafts are used as scaffolds to integrate into the wound bed and provide a template for neodermis formation. Existing commercial products like Integra dermal templates rely on a time-consuming and variable dehydrothermal (DHT) crosslinking process.

The Glutamate-Serine-Glycine Index as a Biomarker to Monitor the Effects of Bariatric Surgery on Non-alcoholic Fatty Liver Disease.

Objective: Bariatric surgery effectively treats non-alcoholic fatty liver disease (NAFLD). The glutamate-serine-glycine (GSG) index has emerged as a non-invasive diagnostic marker for NAFLD, but its ability to monitor treatment response remains unclear. This study investigates the GSG index's ability to monitor NAFLD's response to bariatric surgery.

Lacrimal gland enlargement in thyroid eye disease.

Purpose: This study aimed to investigate lacrimal gland (LG) enlargement in thyroid eye disease (TED) patients on magnetic resonance imaging (MRI).

Methods: A retrospective review was conducted on TED patients who had undergone fat-suppressed contrast-enhanced T1-weighted MRI of the orbits. The lacrimal gland was segmented on OsiriX in consecutive axial and coronal slices to determine its volume.

Environmental impact of large language models in medicine.

The environmental impact of large language models (LLMs) in medicine spans carbon emission, water consumption and rare mineral usage. Prior-generation LLMs, such as GPT-3, already have concerning environmental impacts. Next-generation LLMs, such as GPT-4, are more energy intensive and used frequently, posing potentially significant environmental harms.

Medication shortage behaviour change with multidisciplinary clinician-designed digital notification intervention.

Objectives: To evaluate the effect of a clinician-designed digital notification system on the use of intravenous paracetamol during a medication shortage.

Methods: An in-house digital notification platform was designed through multidisciplinary collaboration. A 4-week pre- and post-implementation methodology was employed to evaluate the effect of the intervention.

Rule-based clinician-developed programmes can facilitate haemodialysis clinical workflows.

There are routine hospital workflows that are not addressed by certain institutional electronic medical records, including the detection of patients requiring haemodialysis who are admitted under non-nephrology services. In this study, the feasibility and performance of a clinician-developed automated haemodialysis patient finder was evaluated. The programme ran with zero downtime for 6 months and had zero false negatives or false positives.

Real-World Outcomes for Localised Gastro-Oesophageal Adenocarcinoma Cancer Treated with Perioperative FLOT and Prophylactic GCSF Support in a Single Asian Centre.

Background: Perioperative FLOT (5-fluorouracil, oxaliplatin and docetaxel) is a standard of care for patients with locally advanced gastro-oesophageal adenocarcinoma (GEA) in Western guidelines, but its use is limited in Asian patients. We report outcomes from a single Asian centre of perioperative FLOT with concomitant granulocyte colony-stimulating factor (GCSF) prophylaxis.

Methods: A retrospective analysis of all 56 stage II to III GEA patients treated with perioperative FLOT at the National Cancer Centre Singapore between June 2017 and February 2024 was performed.

From COVID-19 to monkeypox: a novel predictive model for emerging infectious diseases.

The outbreak of emerging infectious diseases poses significant challenges to global public health. Accurate early forecasting is crucial for effective resource allocation and emergency response planning. This study aims to develop a comprehensive predictive model for emerging infectious diseases, integrating the blending framework, transfer learning, incremental learning, and the biological feature Rt to increase prediction accuracy and practicality.

Advancements and regulations of biomanufacturing cell-based cartilage repair therapies.

Cell-based therapies for cartilage repair, including autologous chondrocyte implantation and allogeneic stem cell treatments, show great promise but face challenges due to high costs and regulatory hurdles. This review summarizes available and investigational products, focusing on allogeneic therapies and the impact of diverse regulatory landscapes on their clinical translation.

Predictors of early removal of intragastric balloon due to intolerance: Insights from a multiethnic Asian cohort.

Introduction: Intolerance frequently limits the use of intragastric balloons (IGBs) in the treatment of obesity. This includes refractory nausea, vomiting and abdominal discomfort. Our study aims to identify predictors of balloon intolerance and early removal, which will help to guide patient selection for this intervention and peri-procedure care.

Pointing to success: a discussion of the role of professional achievements in the selection of specialist surgical trainees.

Background: In Australia and New Zealand, competitive selection processes for surgical specialty training programs often use a standardized curriculum vitae (CV) to assess criteria such as professional achievements. This review aims to assess the predictive validity, standardization, and implicit biases of these selection methods, as well as their implications for trainees and the diversity of surgical cohorts.

Methods: The 2023 CV scoring criteria were collected for all available specialty surgical programs in Australia and New Zealand.

A Pilot Survey of Patient Perspectives on an Artificial Intelligence-Generated Presenter in a Patient Information Video about Face-Down Positioning after Vitreoretinal Surgery.

Introduction: Video education is a commonly used patient education tool. However, the impact of integrating artificial intelligence (AI) into video education remains unexplored. This study aimed to examine the acceptability of an AI-generated presenter in a patient information video about face-down positioning after vitreoretinal surgery.

Push or pull? Digital notification platform implementation reduces dysglycaemia.

Pushing selected information to clinicians, as opposed to the traditional method of clinicians pulling information from an electronic medical record, has the potential to improve care. A digital notification platform was designed by clinicians and implemented in a tertiary hospital to flag dysglycaemia. There were 112 patients included in the study, and the post-implementation group demonstrated lower rates of dysglycaemia (2.

Topical dorzolamide for macular holes: A randomised, double-blind, placebo-controlled trial.

Background: To assess topical dorzolamide as medical therapy for idiopathic full-thickness macular holes (FTMHs).

Methods: Randomised, double-blinded, placebo-controlled, single-centre clinical trial involving 32 patients with idiopathic small FTMHs (<400 ). Participants in both arms used topical dorzolamide 2% or saline thrice daily for 8 weeks with monthly OCT.

Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study.

As the pandemic continues to pose challenges to global public health, developing effective predictive models has become an urgent research topic. This study aims to explore the application of multi-objective optimization methods in selecting infectious disease prediction models and evaluate their impact on improving prediction accuracy, generalizability, and computational efficiency. In this study, the NSGA-II algorithm was used to compare models selected by multi-objective optimization with those selected by traditional single-objective optimization.

A brief history of ramping.

'Ramping' is a commonly used term in contemporary Australian healthcare. It is also a part of the public and political zeitgeist. However, its precise definition varies among sources.