Neuroimaging-Based Responses to Blood Pressure Augmentation in Acute Ischaemic Stroke: A Systematic Review.

Introduction: In acute ischaemic stroke, the key treatment to reduce infarct growth is reperfusion, achieved through thrombolysis, endovascular thrombectomy, or endogenous reperfusion. Prior to definitive reperfusion therapy, blood pressure augmentation may enhance cerebral perfusion and reduce interim infarct growth. This study aimed to summarise the existing evidence from randomised controlled trials on the use of imaging for patient selection and the assessment of blood pressure augmentation in acute ischaemic stroke.

Computer-Assisted Protocol-Adherent Blood Lipid Evaluation in Vascular Outpatients (CAPABLE-Vascular).

The lack of availability of test results in vascular surgery outpatient clinics impedes the medical management of vascular risk factors, such as dyslipidaemia and diabetes mellitus. This study sought to evaluate the feasibility of using computer-assisted processes to promote the ordering of routine investigations to promote this management. After consultation with specialist clinicians, clinician-programmers developed a rule-based system to facilitate the ordering of lipid studies and HbA1c prior to vascular clinic appointments.

Epilepsy surgery candidate identification with artificial intelligence: An implementation study.

Background: To (a) evaluate the effect of a machine learning algorithm in the identification of patients suitable for epilepsy surgery evaluation, and (b) examine the performance of a large language model (LLM) in the collation of key pieces of information pertaining to epilepsy surgery evaluation referral.

Methods: Artificial intelligence analyses were performed for all patients seen in the epilepsy or first seizure clinic at a tertiary hospital over a 12-month period. This study design was intended to emulate a case review that could subsequently be conducted periodically (e.

Better off alone? Artificial intelligence can demonstrate superior performance without clinician input.

Recent studies challenge the assumption that human-artificial intelligence (AI) collaboration is universally optimal, highlighting tasks where AI alone outperforms combined efforts. This viewpoint discusses the reasons behind these findings, explores influences on synergy and emphasises the importance of identifying when clinicians add net benefit to AI performance. Maximising patient outcomes may require accepting AI autonomy in certain scenarios within healthcare practice.

Machine-learning versus traditional approaches to predict all-cause mortality for acute coronary syndrome: a systematic review and meta-analysis.

Background: Acute coronary syndrome (ACS) remains one of the leading causes of death globally. Accurate and reliable mortality risk prediction of ACS patients is essential for developing targeted treatment strategies and improve prognostication. Traditional models for risk stratification such as the GRACE and TIMI risk scores offer moderate discriminative value, and do not incorporate contemporary predictors of ACS prognosis.

Convexity subarachnoid haemorrhage from a cerebral dural arteriovenous fistula presenting with low back pain.

Convexity subarachnoid haemorrhage (SAH) has many possible causes. A 76-year-old man presented with back pain, left leg weakness, and hypertension. His brain imaging showed convexity SAH, with additional intraventricular blood and extensive spinal SAH from T3-S2.

Generative AI chatbots for reliable cancer information: Evaluating web-search, multilingual, and reference capabilities of emerging large language models.

Recent advancements in large language models (LLMs) enable real-time web search, improved referencing, and multilingual support, yet ensuring they provide safe health information remains crucial. This perspective evaluates seven publicly accessible LLMs-ChatGPT, Co-Pilot, Gemini, MetaAI, Claude, Grok, Perplexity-on three simple cancer-related queries across eight languages (336 responses: English, French, Chinese, Thai, Hindi, Nepali, Vietnamese, and Arabic). None of the 42 English responses contained clinically meaningful hallucinations, whereas 7 of 294 non-English responses did.

Female Sex is associated with reduced thrombolytic administration in an Australian Stroke Cohort: A multicentre retrospective cohort study.

Background: Female patients with AIS may not receive thrombolytic equitably.

Aims: We examined whether there were sex differences in the likelihood of receiving thrombolytic in South Australian AIS patients.

Methods: In a retrospective cohort study, consecutive patients admitted to metropolitan stroke units within South Australia between January 2019 to December 2023 with AIS without contraindication to thrombolytic were included.

Syncope in the Ophthalmology Outpatient Department.

Introduction: Syncope is a clinical symptom that occurs commonly in all medical facilities, including the ophthalmology outpatient department. A broad differential diagnosis exists for syncope, of which vasovagal syncope is the most common.

Results: Efficient recognition and management of syncope in the ophthalmology department is essential to minimise its economic and time cost to patients, staff and the healthcare system.

Machine learning approaches for risk prediction after percutaneous coronary intervention: a systematic review and meta-analysis.

Aims: Accurate prediction of clinical outcomes following percutaneous coronary intervention (PCI) is essential for mitigating risk and peri-procedural planning. Traditional risk models have demonstrated a modest predictive value. Machine learning (ML) models offer an alternative risk stratification that may provide improved predictive accuracy.

Delayed return of bowel function after general surgery in South Australia.

Introduction: Reference ranges for determining pathological versus normal postoperative return of bowel function are not well characterised for general surgery patients. This study aimed to characterise time to first postoperative passage of stool after general surgery; determine associations between clinical factors and delayed time to first postoperative stool; and evaluate the association between delay to first postoperative stool and prolonged length of hospital stay.

Methods: This study included consecutive admissions at two tertiary hospitals across a two-year period whom underwent a range of general surgery operations.

Emergency laparotomy preoperative risk assessment tool performance: A systematic review.

Background: Preoperative assessment of risk for emergency laparotomy may enhance decision making with regards to urgency or perioperative critical care admission and promote a more informed consent process for patients. Accordingly, we aimed to assess the performance of risk assessment tools in predicting mortality after emergency laparotomy.

Methods: PubMed, Embase, the Cochrane Library and CINAHL were searched to 12 February 2022 for observational studies reporting expected mortality based on a preoperative risk assessment and actual mortality after emergency laparotomy.

Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis.

Background: Accurate mortality prediction following transcatheter aortic valve implantation (TAVI) is essential for mitigating risk, shared decision-making and periprocedural planning. Surgical risk models have demonstrated modest discriminative value for patients undergoing TAVI and are typically poorly calibrated, with incremental improvements seen in TAVI-specific models. Machine learning (ML) models offer an alternative risk stratification that may offer improved predictive accuracy.

Proactive Deep Learning-Facilitated Inpatient Penicillin Allergy Delabelling: An Implementation Study.

Introduction: Erroneous penicillin allergy labels are associated with significant health and economic costs. This study aimed to determine whether deep learning-facilitated proactive consultation to facilitate delabelling may further enhance inpatient penicillin allergy delabelling.

Methods: This prospective implementation study utilised a deep learning-guided proactive consultation service, which utilised an inpatient penicillin allergy delabelling protocol.

Management of epilepsia partialis continua: A systematic review.

Purpose: Epilepsia partialis continua (EPC) is form of focal motor status epilepticus, with limited guidelines regarding effective pharmacological management. This systematic review aimed to describe previously utilized pharmacological management strategies for EPC, with a focus on patient outcomes.

Methods: A systematic review of the databases PubMed, EMBASE, and SCOPUS was performed from inception to May 2024.

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).

Charting the course: a scoping review on telehealth research trends in Australia.

This review of telehealth research describes the landscape of Australian digital health and telehealth research from 1999 to 2022, focusing on outlining past, present and future trends. A scoping review was conducted using the Joanna Briggs Institute methodology and PRISMA extension for scoping reviews framework, which identified 495 primary research studies of digital or telehealth interventions aimed at improving health outcomes. Data were charted according to technological modality, health focus, professional representation, participant location, year and size.

Perioperative aspirin and coronary artery bypass graft surgery: An updated meta-analysis of randomized controlled trials.

Background: The decision to continue aspirin before elective coronary artery bypass graft surgery remains contentious because of competing thrombotic and bleeding risks. We performed a contemporary systematic review and meta-analysis to compare outcomes between patients undergoing coronary artery bypass grafting who stopped and continued aspirin before surgery.

Methods: PubMed, MEDLINE, and CENTRAL databases were searched from inception to 4 October 2023 for randomized controlled trials comparing patients undergoing coronary artery bypass grafting who continued preoperative aspirin with those who discontinued before surgery.

Tetrodotoxin toxicity: an increasing threat.

A man aged in his sixties presented to the emergency department with vomiting, dizziness and generalised weakness preceded by perioral and peripheral paraesthesias for several hours. He did not speak English and was visiting from overseas. Examination revealed multidirectional nystagmus, subtle bilateral ptosis, marked bilateral upper limb dysmetria and heel-shin ataxia, with mild proximal limb weakness.

Statewide neurology inpatient whole body and brain 18F-fluorodeoxyglucose positron emission tomography utilisation patterns demonstrate avenues for optimisation.

18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) can provide unique insights; however, access may be difficult. In this 2-year statewide study of all neurology inpatient admissions, 27.9% (41/147) of PET (any field of view) demonstrated significant abnormalities.

Impact of frailty, malnutrition and socioeconomic status on perioperative outcomes.

Background: Frailty, malnutrition and low socioeconomic status may mutually perpetuate each other in a self-reinforcing and interdependent manner. The intertwined nature of these factors may be overlooked when investigating impacts on perioperative outcomes. This study aimed to investigate the impact of frailty, malnutrition and socioeconomic status on perioperative outcomes.