Ian Hughes

Background: Rising prevalence of neurodevelopmental disorders, including attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), has increased demand for developmental paediatric services. Ongoing medication review requirements place increasing pressure on paediatrician‐led models. Pharmacist‐led shared care may improve capacity and access; however, evidence in paediatric outpatient settings remains limited. Aim: To evaluate the impact of a paediatric‐pharmacy shared‐care model on wait times, service capacity and efficiency compared with medical‐only care. Methods: We conducted a two‐phase observational study. Phase 1 retrospectively analysed service activity from 2019 to 2024, including patient numbers, occasions of service, wait times, failure‐to‐attend rates, and financial outcomes. Phase 2 prospectively audited 100 pharmacist‐led consultations to characterise clinical activities. Results: Patient numbers increased by 87%, and the proportion receiving pharmacist‐led shared care rose from 4.1% to 25.3%. Pharmacy clinics had shorter wait times than medical clinics (1.84 vs. 7.64 months; p < 0.001). Following transition to shared care, median medical occasions decreased from 3 to 2 while total occasions increased from 3 to 5 (both p < 0.001). Pharmacy clinics demonstrated greater revenue efficiency (revenue‐to‐cost ratio 2.97 vs. 1.73). Pharmacists conducted comprehensive medication reviews including medication counselling, adherence assessment, and non‐pharmacological support within a supervised framework. Conclusion: The paediatric‐pharmacy shared‐care model was associated with shorter wait times, greater cost‐efficiency, and redistribution of routine medication reviews to pharmacists, with increased overall review frequency despite fewer medical appointments per patient. Pharmacist reviews were comprehensive and delivered within a supervised framework. These findings support pharmacist‐led shared care as a scalable strategy to improve access and workforce capacity in developmental paediatrics.

Background: Valve-in-valve transcatheter aortic valve implantation is a less invasive alternative to redo surgery for failed surgical bioprostheses, but optimal antithrombotic management is uncertain. Objectives: To compare outcomes across antithrombotic regimens after valve-in-valve procedures in real-world practice. Methods: In the Australasian Cardiac Outcomes Registry (2018–2025), 1,050 adults were grouped by discharge regimen: single antiplatelet therapy, dual antiplatelet therapy, oral anticoagulation, or oral anticoagulation plus antiplatelet therapy. Outcomes included 30-day and 12-month mortality, stroke/TIA, life-threatening or major bleeding, major adverse cardiac and cerebrovascular events, and echocardiographic valve performance. Results: Thirty-day mortality was higher with oral anticoagulation (1.7%) and combination therapy (3.6%) than with single or dual antiplatelet therapy (both 0%; p < 0.001). The 30-day MACCE rate was greater with oral anticoagulation (4.5%) and combination therapy (4.4%) than with single (1.5%) or dual antiplatelet therapy (0.4%) ( p = 0.003); stroke/TIA and bleeding were infrequent and similar across groups. At 12 months, MACCE remained highest with oral anticoagulation (11.8%) and combination therapy (10.7%) compared with single (5.0%) and dual antiplatelet therapy (3.2%) ( p = 0.001). Mortality at 12 months was numerically higher with oral anticoagulation or combination therapy (5.2% and 4.4%) than with single or dual antiplatelet therapy (1.8% and 2.4%) ( p = 0.116). At 30 days, transvalvular gradients were lower in patients receiving oral anticoagulation-containing regimens; however, no significant differences in gradients, valve area, ejection fraction, or regurgitation were observed at 12 months. In multivariable analysis, combination therapy was independently associated with higher odds of 12-month MACCE compared with SAPT (OR 2.76, 95% CI 1.03–7.37; p = 0.043). Higher STS score and greater frailty were also independently associated with 12-month MACCE. Conclusions: In this observational cohort of patients undergoing valve-in-valve TAVI, oral anticoagulation-containing regimens were associated with higher early mortality and higher 12-month MACCE rates than antiplatelet-only strategies. However, these associations should be interpreted cautiously, as they likely reflect in part the greater baseline comorbidity burden of patients prescribed anticoagulation rather than a direct treatment effect. No sustained haemodynamic benefit was observed at 12 months. Individualised antithrombotic therapy and prospective randomised studies are warranted.

Aim: Recommencing enteral feeding post‐extubation in children is often delayed. This study evaluated a Post‐Extubation Early Feeding (PEEF) protocol on early recommencement of enteral nutrition post‐extubation in a tertiary paediatric intensive care unit (PICU). Methods: The PEEF protocol involved direction to re‐commence enteral nutrition at 50% of the pre‐fasting rate within 1 h of extubation and upgrade to the pre‐extubation feeding rate within 2 h. The PEEF protocol was a quality improvement project implemented at a tertiary PICU and was evaluated through a retrospective analysis. The study included children aged 0–18 years who were admitted to PICU, intubated and subsequently underwent planned extubation pre‐PEEF (November 2019–October 2020) and post‐PEEF (November 2021–October 2022). Results: A total of 795 patients were included in the study, 372 pre‐PEEF and 423 post‐PEEF. Demographic variables and severity of illness variables were similar in the two groups. Post implementation of the PEEF protocol, the median (interquartile range) time to re‐commence enteral nutrition after extubation was 3.2 h (1.9, 4.7) compared to pre‐PEEF, 4.2 h (3.2, 5.5; p = 2.4 × 10 ⁻¹³ ). Post‐PEEF the median time to reach the pre‐fasting feeding rate was 5 h (2.6, 10.6), compared to 7.3 h (4.1, 13) pre‐PEEF ( p = 0.0005). Conclusions: Implementation of the PEEF protocol reduced the time to resume enteral nutrition and the time to reach pre‐extubation feeding rates although improvement was not consistent with the goals of PEEF. Continuing assessment and education are required to drive outcomes further towards target goals.

Purpose Rib fractures in the elderly can lead to significant morbidity and mortality. Management is generally conservative due to the perceived risks related to frailty and co-morbidities. The primary aim of this exploratory study was to describe the demographics and outcomes of traumatic rib fractures in older Australians admitted to major trauma centres. The secondary aim was to describe the management strategies employed, the involvement of specialist pain services, involvement of geriatric services, availability of surgical options and evaluate any variability in management at participating centres. Methods Multicentre, retrospective cohort. Patients ≥ 70 years with multiple rib fractures admitted to Australian Level 1 trauma centres during 2019. Outcomes included: demographics and mechanisms of injury, treatment and management practices (ICU admission, mechanical ventilation, analgesia mode and pain service use, surgery, geriatrics involvement), and patients’ clinical outcomes. Results 491 patients were included from six centres. 282 (57.4%) were male, 445 (90.6%) from home, 218 (44.4%) fell from < 1 m, with a median 5.5 fractures, and Injury Severity Score (ISS) 13. Rates of low energy fall as mechanism of injury varied by site (range 16–62%, P = 0.001), the number of fractured ribs (P = 0.45) and ISS (P = 0.1) were consistent across sites. 208 (42.4%; range 19–55%, P < 0.001) were admitted to ICU with 53 (10.8%; range 7–29%, P = 0.002) ventilated. Acute Pain Services were utilised for 340 (69.4%; range 60–88%, P = 0.07) patients, 132 (27.0%; range 19–50%, P < 0.001) had regional anaesthesia and 167 (67%; range 4–79%. P < 0.001) geriatric input. Surgical rib fixation occurred in 14 (2.9%; range 0-9.2%). Median hospital LOS was 8.1 days (IQR 4.2, 13.4) with 234 (47.7%) returning home. In-hospital mortality was 42 (8.6%). 181 patients (36.9%; range 24–53%, P = 0.02) had at least one complication. Conclusions There is significant variability in the demographics of elderly patients presenting with rib fractures and discrepancy in management of these patients at Australia’s Level 1 trauma centres. This study presents an opportunity to further investigate the presence of a causal relationship, optimise treatment strategies for best clinical outcomes and future prospective and interventional studies in this high-risk population.

Background: Artificial intelligence (AI) has the potential to address growing logistical and economic pressures on the health care system by reducing risk, increasing productivity, and improving patient safety; however, implementing digital health technologies can be disruptive. Workforce perception is a powerful indicator of technology use and acceptance, however, there is little research available on the perceptions of allied health professionals (AHPs) toward AI in health care. Objective: This study aimed to explore AHP perceptions of AI and the opportunities and challenges for its use in health care delivery. Methods: A cross-sectional survey was conducted at a health service in, Queensland, Australia, using the Shinners Artificial Intelligence Perception tool. Results: A total of 231 (22.1%) participants from 11 AHPs responded to the survey. Participants were mostly younger than 40 years (157/231, 67.9%), female (189/231, 81.8%), working in a clinical role (196/231, 84.8%) with a median of 10 years’ experience in their profession. Most participants had not used AI (185/231, 80.1%), had little to no knowledge about AI (201/231, 87%), and reported workforce knowledge and skill as the greatest challenges to incorporating AI in health care (178/231, 77.1%). Age (P=.01), profession (P=.009), and AI knowledge (P=.02) were strong predictors of the perceived professional impact of AI. AHPs generally felt unprepared for the implementation of AI in health care, with concerns about a lack of workforce knowledge on AI and losing valued tasks to AI. Prior use of AI (P=.02) and years of experience as a health care professional (P=.02) were significant predictors of perceived preparedness for AI. Most participants had not received education on AI (190/231, 82.3%) and desired training (170/231, 73.6%) and believed AI would improve health care. Ideas and opportunities suggested for the use of AI within the allied health setting were predominantly nonclinical, administrative, and to support patient assessment tasks, with a view to improving efficiencies and increasing clinical time for direct patient care. Conclusions: Education and experience with AI are needed in health care to support its implementation across allied health, the second largest workforce in health. Industry and academic partnerships with clinicians should not be limited to AHPs with high AI literacy as clinicians across all knowledge levels can identify many opportunities for AI in health care.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Artificial intelligence (AI) has the potential to address growing logistical and economic pressures on the health care system by reducing risk, increasing productivity, and improving patient safety; however, implementing digital health technologies can be disruptive. Workforce perception is a powerful indicator of technology use and acceptance, however, there is little research available on the perceptions of allied health professionals (AHPs) toward AI in health care. Objective: This study aimed to explore AHP perceptions of AI and the opportunities and challenges for its use in health care delivery. Methods: A cross-sectional survey was conducted at a health service in, Queensland, Australia, using the Shinners Artificial Intelligence Perception tool. Results: A total of 231 (22.1%) participants from 11 AHPs responded to the survey. Participants were mostly younger than 40 years (157/231, 67.9%), female (189/231, 81.8%), working in a clinical role (196/231, 84.8%) with a median of 10 years’ experience in their profession. Most participants had not used AI (185/231, 80.1%), had little to no knowledge about AI (201/231, 87%), and reported workforce knowledge and skill as the greatest challenges to incorporating AI in health care (178/231, 77.1%). Age (P=.01), profession (P=.009), and AI knowledge (P=.02) were strong predictors of the perceived professional impact of AI. AHPs generally felt unprepared for the implementation of AI in health care, with concerns about a lack of workforce knowledge on AI and losing valued tasks to AI. Prior use of AI (P=.02) and years of experience as a health care professional (P=.02) were significant predictors of perceived preparedness for AI. Most participants had not received education on AI (190/231, 82.3%) and desired training (170/231, 73.6%) and believed AI would improve health care. Ideas and opportunities suggested for the use of AI within the allied health setting were predominantly nonclinical, administrative, and to support patient assessment tasks, with a view to improving efficiencies and increasing clinical time for direct patient care. Conclusions: Education and experience with AI are needed in health care to support its implementation across allied health, the second largest workforce in health. Industry and academic partnerships with clinicians should not be limited to AHPs with high AI literacy as clinicians across all knowledge levels can identify many opportunities for AI in health care.

Objective: To describe the relationships between different methods of measuring functional fibrinogen levels in severely injured, bleeding trauma patients across multiple timepoints during hospitalisation.Methods: In 100 adult trauma patients enrolled in the FEISTY pilot randomised clinical trial at four tertiary trauma centres in Australia, blood samples were collected prospectively. Consistency of agreement was calculated, comparing functional fibrinogen levels measured by four methods – ROTEM® Delta and Sigma FIBTEM A5, TEG® 6s CFF MA, and gold‐standard Clauss Fibrinogen.Results: Comparing the ROTEM® Delta and new‐generation ROTEM® Sigma machine, consistency of agreement for FIBTEM A5, measured by calculating intraclass correlation coefficients (ICCs), was ≥0.73 across all analysed timepoints, with mean differences (Sigma minus Delta) of 0.10–3.57 mm. Corresponding values comparing the ROTEM® Sigma FIBTEM A5 and TEG® 6s CFF MA were ICC = 0.55–0.82 and ICC = 4.69–7.97 (CFF MA minus A5). Comparing ROTEM® Sigma FIBTEM A5 and Clauss Fibrinogen Analysis (CFA), among statistically significant simple linear regression models, R² was 0.25–0.67, and comparing TEG® 6s CFF MA and CFA (CFA) 0.65–0.82, although not all differences were significant with the latter comparison. Relationships across all timepoints combined were Clauss Fibrinogen (CF) (g/L) = 0.21𝑥 + 0.004 (where 𝑥 = ROTEM® Sigma FIBTEM A5 in mm) and (g/L) = 0.16𝑥 − 0.06 (where 𝑥 = TEG® 6s CFF MA in mm).Conclusions: The present study revealed acceptable agreement between four different assays measuring functional fibrinogen, with current‐ and previous‐generation ROTEM® machines (Sigma, Delta) performing similarly measuring functional fibrinogen via FIBTEM assay. This suggests that haemostatic resuscitation algorithms designed for the ROTEM® Delta can be applied to the ROTEM® Sigma to guide fibrinogen replacement.

Background Interposition microvascular grafting may be required to bridge arterial defects during digital replantation or revascularization and has traditionally been performed utilizing a venous autograft. Arterial interposition grafting has been shown to be superior in maintaining patency in large vessel surgery; there are case reports of its use in microsurgery. Methods Six fellowship-trained hand and microsurgeons performed arterial and venous interposition grafts on the femoral arteries of 40 Wistar rats. After sectioning one femoral artery a segment of the contralateral femoral artery or vein was obtained. The time was recorded per graft and patency tested 10 minutes following grafting by an independent assessor. Each surgeon also completed a questionnaire detailing regular microsurgical volume, technical ease, and conceptual preference for either graft. Results Time for arterial interposition (median time 51.7 minutes) was longer than venous grafting (median time 45.9 minutes, p = 0.075). Arterial grafts were more likely to be patent or questionably patent (odds ratio [OR] = 6.77, p = 0.031). All surgeons found arterial interposition grafting technically easier and preferred it conceptually. Improvements were noted in patency rates (OR = 11.29, p = 0.018) and avoidance of anastomotic leak (OR = 0.19, p = 0.029) when surgeons performed moderate levels or greater of microsurgery within their regular practice. Conclusion Greater immediate patency was noted with arterial interposition grafting in a rodent model when compared to venous grafting, although procedural time was greater. All surgeons found arterial grafting technically easier. Arterial microvascular grafting may be useful in the setting of digital replantation or revascularization with an arterial defect.