Background: Our prior six-year review (n=2165) revealed 24% of patients undergoing posterior decompression surgeries (laminectomy or discectomy) sought emergency department (ED) care within three months post-surgery. We established an integrated Spine Assessment Clinic (SAC) to enhance patient outcomes and minimize unnecessary ED visits through pre-operative education, targeted QI interventions, and early post-operative follow-up. Methods: We reviewed 13 months of posterior decompression data (n=205) following SAC implementation. These patients received individualized, comprehensive pre-operative education and follow-up phone calls within 7 days post-surgery. ED visits within 90 days post-surgery were tracked using provincial databases and compared to our pre-SAC implementation data. Results: Out of 205 patients, 24 (11.6%) accounted for 34 ED visits within 90 days post-op, showing a significant reduction in ED visits from 24% to 11.6%, and decreased overall ED utilization from 42.1% to 16.6% (when accounting for multiple visits by the same patient). Early interventions including wound monitoring, outpatient bloodwork, and prescription adjustments for pain management, helped mitigate ED visits. Patient satisfaction surveys (n=62) indicated 92% were “highly satisfied” and 100% would recommend the SAC. Conclusions: The SAC reduced ED visits after posterior decompression surgery by over 50%, with pre-operative education, focused QI initiatives, and its individualized, proactive approach.

Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.

Diet is a key modifiable factor for improving suboptimal lipoprotein profiles and reducing cardiovascular disease (CVD) risk(1). Dietary patterns like the Dietary Approaches to Stop Hypertension (DASH) or the Mediterranean Diet, with varying macronutrient components, have shown positive effects on total cholesterol and low-density lipoproteins (LDL)(2). However, limited research exists on the impact of different healthy diets on lipoprotein subclass profiles, which are increasingly known to influence CVD risk. This study aims to compare the nuclear magnetic resonance (NMR)-measured 112 lipoprotein profiles across three healthy dietary patterns: a carbohydrate-rich diet (CARB), similar to the DASH diet; a protein-rich diet (PROT); and an unsaturated fat-rich diet (USFA), similar to the Mediterranean diet. Lipoprotein parameters were generated using the Bruker IVDr Lipoprotein Subclass Analysis (B.I.LISA) method(3). The lipoprotein subclasses included different molecular components of very low-density lipoprotein (VLDL, 0.950–1.006 kg/L), low-density lipoprotein (LDL, density 1.09–1.63 kg/L), intermediate-density lipoprotein (IDL, density 1.006–1.019 kg/L), and high-density lipoprotein (HDL, density 1.063–1.210 kg/L). The LDL subfraction was further divided into six density classes, and the HDL subfractions were divided into four different density classes. Plasma samples from a randomised cross-over intervention study involving 156 individuals who completed more than two dietary patterns were included for the NMR analysis (registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535). The Friedman’s test with post-hoc analysis, corrected for multiple testing, showed that all healthy dietary patterns led to a reduction in overall lipoprotein subclasses known to be associated with atherogenic risk. This reduction included large and medium-sized LDL subclasses, all intermediate-density IDL subclasses, as well as total plasma cholesterol, triglycerides, apolipoprotein-B100, apo-B100/apo-A1 ratio, and LDL-cholesterol (p < 0.05). Additional variations in lipoprotein subclasses specific to each diet were also observed. The PROT diet showed a decrease in small-sized and dense LDL, large to medium VLDL subclasses, and large-sized HDL subclasses. Conversely, the CARB diet exhibited an increase in smaller-sized and denser LDL, along with a decrease in large-sized HDL and an increase in smaller-sized HDL subclasses. The USFA diet led to decreases in LDL and overall VLDL subclasses, while increasing LDL and HDL subclasses (p < 0.05). The impact of different healthy diets with differential effects on lipoproteins suggests the possibility of targeting the cholesterol status of individuals to optimise lipoprotein profiles and thereby reduce CVD risk. Preliminary exploratory analyses based on linear mixed-effect models coupled with a latent profile analysis, adjusted for cholesterol status, showed that individual lipoprotein responses to specific diets varied. Inter-individual variations in lipoprotein responses to healthy diets were evident. A small proportion of individuals only responded to specific diets, suggesting potential of personalised nutrition based on individual lipoprotein profiles. These observed variations highlight the complexity of individual responses to dietary interventions.

The Hippoboscidae are ectoparasites of birds and mammals, which, as a group, are known to vector multiple diseases. Avipoxvirus (APV) is mechanically vectored by various arthropods and causes seasonal disease in wild birds in the United Kingdom (UK). Signs of APV and the presence of louse flies (Hippoboscidae) on Dunnocks Prunella modularis were recorded over a 16·5-year period in a rural garden in Somerset, UK. Louse flies collected from this site and other sites in England were tested for the presence of APV DNA and RNA sequences. Louse flies on Dunnocks were seen to peak seasonally three weeks prior to the peak of APV lesions, an interval consistent with the previously estimated incubation period of APV in Dunnocks. APV DNA was detected on 13/25 louse flies, Ornithomya avicularia and Ornithomya fringillina, taken from Dunnocks, both with and without lesions consistent with APV, at multiple sites in England. Collectively these data support the premise that louse flies may vector APV. The detection of APV in louse flies, from apparently healthy birds, and from sites where disease has not been observed in any host species, suggests that the Hippoboscidae could provide a non-invasive and relatively cheap method of monitoring avian diseases. This could provide advanced warnings of disease, including zoonoses, before they become clinically apparent.

This editorial considers the value and nature of academic psychiatry by asking what defines the specialty and psychiatrists as academics. We frame academic psychiatry as a way of thinking that benefits clinical services and discuss how to inspire the next generation of academics.

Background: This study investigates the utility of low-density scalp electrical source imaging (LD-ESI) of the Ictal Onset Zone (IOZ) and interictal spike ripple high frequency oscillation (ISRHFO) networks using Source Coherence Maps (SCM) in the surgical evaluation of children with medically refractory epilepsy. Invasive intracranial monitoring, the gold standard for determining epileptogenic zones, has limited spatial sampling. SCM presents a promising new non-invasive diagnostic technique. Methods: This was a retrospective review of 11 patients who underwent focal resections. SCMs were generated using Standardized Low Resolution Electromagnetic Tomography (sLORETA). SCM concordance to resection margins was assessed, noting outcomes at 3 years. Results: For 7/11 cases, ictal SCMs included the resection, and 5/7 achieved seizure freedom, indicating inclusion of the epileptogenic zone. For the 2/7 not seizure-free, the IOZ networks on the SCMs extended beyond resection margins, suggesting the epileptogenic zone also extended beyond the resection. Interictal spike ripple ESI and ISRHFO SCM were performed for 7/11, with 3/7 included in the resection and all 3 seizure-free. Conclusions: These findings may support LD-ESI of the IOZ and ISRHFO network using SCM as promising methods complementary to ictal and interictal ESI in pediatric epilepsy surgical workup, guiding electrode placement for intracranial monitoring to identify the epileptogenic zone.

Although food insecurity affects a significant proportion of young children in New Zealand (NZ)(1), evidence of its association with dietary intake and sociodemographic characteristics in this population is lacking. This study aims to assess the household food security status of young NZ children and its association with energy and nutrient intake and sociodemographic factors. This study included 289 caregiver and child (1-3 years old) dyads from the same household in either Auckland, Wellington, or Dunedin, NZ. Household food security status was determined using a validated and NZ-specific eight-item questionnaire(2). Usual dietary intake was determined from two 24-hour food recalls, using the multiple source method(3). The prevalence of inadequate nutrient intake was assessed using the Estimated Average Requirement (EAR) cut-point method and full probability approach. Sociodemographic factors (i.e., socioeconomic status, ethnicity, caregiver education, employment status, household size and structure) were collected from questionnaires. Linear regression models were used to estimate associations with statistical significance set at p <0.05. Over 30% of participants had experienced food insecurity in the past 12 months. Of all eight indicator statements, “the variety of foods we are able to eat is limited by a lack of money,” had the highest proportion of participants responding “often” or “sometimes” (35.8%). Moderately food insecure children exhibited higher fat and saturated fat intakes, consuming 3.0 (0.2, 5.8) g/day more fat, and 2.0 (0.6, 3.5) g/day more saturated fat compared to food secure children (p<0.05). Severely food insecure children had lower g/kg/day protein intake compared to food secure children (p<0.05). In comparison to food secure children, moderately and severely food insecure children had lower fibre intake, consuming 1.6 (2.8, 0.3) g/day and 2.6 (4.0, 1.2) g/day less fibre, respectively. Severely food insecure children had the highest prevalence of inadequate calcium (7.0%) and vitamin C (9.3%) intakes, compared with food secure children [prevalence of inadequate intakes: calcium (2.3%) and vitamin C (2.8%)]. Household food insecurity was more common in those of Māori or Pacific ethnicity; living in areas of high deprivation; having a caregiver who was younger, not in paid employment, or had low educational attainment; living with ≥2 other children in the household; and living in a sole-parent household. Food insecure young NZ children consume a diet that exhibits lower nutritional quality in certain measures compared to their food-secure counterparts. Food insecurity was associated with various sociodemographic factors that are closely linked with poverty or low income. As such, there is an urgent need for poverty mitigation initiatives to safeguard vulnerable young children from the adverse consequences of food insecurity.

Improving the quality and conduct of multi-center clinical trials is essential to the generation of generalizable knowledge about the safety and efficacy of healthcare treatments. Despite significant effort and expense, many clinical trials are unsuccessful. The National Center for Advancing Translational Science launched the Trial Innovation Network to address critical roadblocks in multi-center trials by leveraging existing infrastructure and developing operational innovations. We provide an overview of the roadblocks that led to opportunities for operational innovation, our work to develop, define, and map innovations across the network, and how we implemented and disseminated mature innovations.

Environmental sensors are crucial for monitoring weather conditions and the impacts of climate change. However, it is challenging to place sensors in a way that maximises the informativeness of their measurements, particularly in remote regions like Antarctica. Probabilistic machine learning models can suggest informative sensor placements by finding sites that maximally reduce prediction uncertainty. Gaussian process (GP) models are widely used for this purpose, but they struggle with capturing complex non-stationary behaviour and scaling to large datasets. This paper proposes using a convolutional Gaussian neural process (ConvGNP) to address these issues. A ConvGNP uses neural networks to parameterise a joint Gaussian distribution at arbitrary target locations, enabling flexibility and scalability. Using simulated surface air temperature anomaly over Antarctica as training data, the ConvGNP learns spatial and seasonal non-stationarities, outperforming a non-stationary GP baseline. In a simulated sensor placement experiment, the ConvGNP better predicts the performance boost obtained from new observations than GP baselines, leading to more informative sensor placements. We contrast our approach with physics-based sensor placement methods and propose future steps towards an operational sensor placement recommendation system. Our work could help to realise environmental digital twins that actively direct measurement sampling to improve the digital representation of reality.

We estimate elasticities of substitution between components of the Bank of England’s household-sector UK Divisia monetary aggregate using quarterly data from 1999 to 2019, encompassing the period surrounding the global financial crisis. The demand system includes interest-bearing sight and time deposits at monetary financial institutions as components, since deposit data for banks (excluding mutuals) and for mutuals are no longer published separately. We find that the elasticities of substitution that relate to changes in the user cost of noninterest-bearing monetary assets imply inelastic substitution over all or almost all of the sample and, consequently, a conventional monetary aggregate would be a highly misleading economic indicator relative to a Divisia monetary aggregate.