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Abstract Background Promoting appropriate pharmacotherapy requires understanding the factors that influence how clinicians prescribe medications. While prior work has focused on patient and clinician factors, features of the organizational setting have received less attention, though identifying sources of variation in prescribing may help identify opportunities to improve patient safety and outcomes. Objective To evaluate the relationship between the number of clinicians who prescribe medications in a facility and facility prescribing intensity of six individual medication classes by clinician specialty: benzodiazepines, antipsychotics, antiepileptics, and antidepressants by psychiatrists and antibiotics, opioids, antiepileptics, and antidepressants by primary care clinicians (PCPs). Design We used 2017 Veterans Health Administration (VHA) administrative data. Subjects We included patient-clinician dyads of older patients (> 55 years) with an outpatient encounter with a clinician in 2017. Patient-clinician data from 140 VHA facilities were included (n = 13,347,658). Analysis was repeated for years 2014 to 2016. Main measures For each medication, facility prescribing intensity measures were calculated as clinician prescribing intensity averaged over all clinicians at each facility. Clinician prescribing intensity measures included percentage of each clinician’s patients prescribed the medication and mean number of days supply per patient among all patients of each clinician. Key results As the number of prescribing clinicians in a facility increased, the intensity of prescribing decreased. Every increase of 10 facility clinicians was associated with a significant decline in prescribing intensity for both specialties for different medication classes: for psychiatrists, declines ranged from 6 to 11%, and for PCPs, from 2 to 3%. The pattern of more clinicians less prescribing was significant across all years. Conclusion Future work should explore the mechanisms that link the number of facility clinicians with prescribing intensity for benzodiazepines, antipsychotics, antiepileptics, antidepressants, antibiotics, and opioids. Facilities with fewer clinicians may need additional resources to avoid unwanted prescribing of potentially harmful or unnecessary medications.

Objective: The ability to choose one's work-location can influence burnout from employment. We sought to evaluate potential associations between autonomy in work-location decision and burnout. Methods: We used 2020 Veterans Health Administration Annual All Employee Survey data from behavioral health providers at 129 medical facilities. Based on responses to items in a COVID-19 module related to teleworking frequency and reasons for not teleworking both pre- and during COVID-19, we generated six groups representing potentially differing levels of work-location decision autonomy. We hypothesized that greater autonomy is associated with less burnout. Results: Psychologists reported highest burnout (40.1%, 1801/4494), followed by psychiatrists (35.6%, 703/1976) and social workers (31.0%, 3421/11,051). Adjusting for covariates including workload, providers newly approved for telework during COVID-19 showed 1.28 (95% CI=1.03–1.59), 1.71 (1.25–2.35), and 1.35 (0.86–2.12) times higher odds of burnout among social workers, psychologists, and psychiatrists, respectively, compared to providers chose not to telework during COVID-19. Conclusions: Providers who chose to keep coming into work in person reported less burnout than providers who previously could not telework and are teleworking during the pandemic. Greater autonomy in work-location decision might have greater importance in reducing burnout in behavioral health providers than having the ability to telework per se.

The Canadian Food Inspection Agency (CFIA) is developing an establishment-based risk assessment model to categorize rendering plants that produce livestock feed ingredients (ERA-Renderer model) according to animal and human health risks (i.e., feed safety risks) and help in determining the allocation of inspection resources based on risk. The aim of the present study was to identify and select feed-safety-related factors and assessment criteria for inclusion in the ERA-Renderer model. First, a literature review was performed to identify evidence-based factors that impact the feed safety risk of livestock feed during its rendering processes. Secondly, a refinement process was applied to retain only those that met the inclusion conditions, such as data availability, lack of ambiguity, and measurability. Finally, an expert panel helped in selecting factors and assessment criteria based on their knowledge and experience in the rendering industry. A final list of 32 factors was developed, of which 4 pertained to the inherent risk of a rendering plant, 8 were related to risk mitigation strategies, and 20 referred to the regulatory compliance of a rendering plant. A total of 179 criteria were defined to assess factors based on practices in the Canadian rendering industry. The results of this study will be used in the next step of the model development to estimate the relative risks of the assessment criteria considering their impact on feed safety. Once implemented, the CFIA’s ERA-Renderer model will provide an evidence-based, standardized, and transparent approach to help manage the feed safety risks in Canada’s rendering sector.

Abstract Background Evaluation of new treatment policies is often costly and challenging in complex conditions, such as hepatitis C virus (HCV) treatment, or in limited-resource settings. We sought to identify hypothetical policies for HCV treatment that could best balance the prevention of cirrhosis while preserving resources (financial or otherwise). Methods The cohort consisted of 3792 HCV-infected patients without a history of cirrhosis or hepatocellular carcinoma at baseline from the national Veterans Health Administration from 2015 to 2019. To estimate the efficacy of hypothetical treatment policies, we utilized historical data and reinforcement learning to allow for greater flexibility when constructing new HCV treatment strategies. We tested and compared four new treatment policies: a simple stepwise policy based on Aspartate Aminotransferase to Platelet Ratio Index (APRI), a logistic regression based on APRI, a logistic regression on multiple longitudinal and demographic indicators that were prespecified for clinical significance, and a treatment policy based on a risk model developed for HCV infection. Results The risk-based hypothetical treatment policy achieved the lowest overall risk with a score of 0.016 (90% CI 0.016, 0.019) while treating the most high-risk (346.4 ± 1.4) and the fewest low-risk (361.0 ± 20.1) patients. Compared to hypothetical treatment policies that treated approximately the same number of patients (1843.7 vs. 1914.4 patients), the risk-based policy had more untreated time per patient (7968.4 vs. 7742.9 patient visits), signaling cost reduction for the healthcare system. Conclusions Off-policy evaluation strategies are useful to evaluate hypothetical treatment policies without implementation. If a quality risk model is available, risk-based treatment strategies can reduce overall risk and prioritize patients while reducing healthcare system costs.

Abstract Background Patients with hepatitis C virus (HCV) frequently remain at risk for cirrhosis after sustained virologic response (SVR). Existing cirrhosis predictive models for HCV do not account for dynamic antiviral treatment status and are limited by fixed laboratory covariates and short follow up time. Advanced fibrosis assessment modalities, such as transient elastography, remain inaccessible in many settings. Improved cirrhosis predictive models are needed. Methods We developed a laboratory-based model to predict progression of liver disease after SVR. This prediction model used a time-varying covariates Cox model adapted to utilize longitudinal laboratory data and to account for antiretroviral treatment. Individuals were included if they had a history of detectable HCV RNA and at least 2 AST-to-platelet ratio index (APRI) scores available in the national Veterans Health Administration from 2000 to 2015, Observation time extended through January 2019. We excluded individuals with preexisting cirrhosis. Covariates included baseline patient characteristics and 16 time-varying laboratory predictors. SVR, defined as permanently undetectable HCV RNA after antiviral treatment, was modeled as a step function of time. Cirrhosis development was defined as two consecutive APRI scores > 2. We predicted cirrhosis development at 1-, 3-, and 5-years follow-up. Results In a national sample of HCV patients (n = 182,772) with a mean follow-up of 6.32 years, 42% (n = 76,854) achieved SVR before 2016 and 16.2% (n = 29,566) subsequently developed cirrhosis. The model demonstrated good discrimination for predicting cirrhosis across all combinations of laboratory data windows and cirrhosis prediction intervals. AUROCs ranged from 0.781 to 0.815, with moderate sensitivity 0.703–0.749 and specificity 0.723–0.767. Conclusion A novel adaptation of time-varying covariates Cox modeling technique using longitudinal laboratory values and dynamic antiviral treatment status accurately predicts cirrhosis development at 1-, 3-, and 5-years among patients with HCV, with and without SVR. It improves upon earlier cirrhosis predictive models and has many potential population-based applications, especially in settings without transient elastography available.

Livestock are an important source of livelihoods in agricultural systems in sub-Saharan Africa (SSA), while also being the largest source of national greenhouse gas (GHG) emissions in most African countries. As a consequence, there is a critical need for data on livestock GHG sources and sinks to develop national inventories, as well as conduct baseline measurements and intervention testing to mitigate GHG emissions and meet ambitious national climate goals. Our objective was to review studies on GHG emissions from livestock systems in SSA, as well as soil carbon storage in livestock-dominated systems (i.e., grasslands and rangelands), to evaluate best current data and suggest future research priorities. To this end, we compiled studies from SSA that determined emission factors (EFs) for enteric methane and manure emissions, along with studies on soil organic carbon (SOC) stocks in SSA. We found that there has been limited research on livestock GHG emissions and SOC relative to national ambitions for climate change mitigation in SSA. Enteric methane emission factors (EFs) in low productivity cattle systems may be lower than IPCC Tier 1 default EFs, whereas small ruminants (i.e. sheep and goats) had higher EFs compared to IPCC Tier 1 EFs. Manure EFs were equal to or lower than IPCC Tier 1 EFs for deposited manure (while grazing), manure applied as fertilizer, and manure management. SOC stocks for grasslands and rangelands in SSA show broad agreement with IPCC estimates, but there was a strong geographic bias and many studies did not report soil type, bulk density, or SOC stocks at >30 cm depth. In general, the largest data gaps included information for manure (quantity, quality, management), small ruminants, agropastoral/pastoralist systems, and in general from West Africa. Future research should focus on filling major data gaps on locally appropriate mitigation interventions and improving livestock activity data for developing Tier 2 GHG inventories in SSA. At the science-policy interface, all parties would benefit from enhanced coordination within the research community and between researchers and African governments to improve Tier 2 inventories and harmonize measurement for mitigation in livestock systems in SSA.

Current test methods for estimating biodegradability and duration in the oceans, do not consider nitrogen as a limiting factor for bacterial growth and plastic biodegradation. Algae and cyanobacteria can thrive within widely ranging Nitrogen/Phosphorous ratios from 5:1 to 100:1 The ocean's biodiversity that we know could die off if algae and cyanobacteria out compete existing dominant bacteria. Normally organic loading would be localized, but the slow degradation of microplastics allows the circulation across all the oceans. Single use plastics, such as wipes are having an increasing impact due to significant growth of demand and particularly with sanitation concerns with COVID-19. Biodegradability of plastics needs to be reassessed and the use of actual ocean conditions is needed. Verifying claims of biodegradability need to be reassessed since these are based on methods that have not considered nitrogen limitations in the ocean.

The Canada Ontario agreement requires reduction of total phosphorous (TP) loadings to prevent algae blooms in Lake Erie. This study was to consider TP loadings from the Thames River and potential methods needed to determine actual loadings. The study found TP loading in the Thames River was dominated by peak flow events and between 10 and 15% of the flow had over 60% of the loading. Identification of TP and Dissolved Reactive Phosphate (DRG) and/or Ortho phosphorous (Ortho P) have similar ratios with TP in the Thames River although are not the same in the main, north and south branches. Continuous ortho P monitoring equipment could be used to estimate TP loads based on ratios of Ortho P to TP established in the river shed. A description and cost estimate for a continuous monitoring system is included in the study. Reduction of TP loadings requires methods that can deal with the peak flows and one option could be wetlands along the river basin.

Objective To develop a prioritisation framework to support priority setting for elective surgeries after COVID-19 based on the impact on patient well-being and cost.Design We developed decision analytical models to estimate the consequences of delayed elective surgical procedures (eg, total hip replacement, bariatric surgery or septoplasty).Setting The framework was applied to a large hospital in the Netherlands.Outcome measures Quality measures impacts on quality of life and costs were taken into account and combined to calculate net monetary losses per week delay, which quantifies the total loss for society expressed in monetary terms. Net monetary losses were weighted by operating times.Results We studied 13 common elective procedures from four specialties. Highest loss in quality of life due to delayed surgery was found for total hip replacement (utility loss of 0.27, ie, 99 days lost in perfect health); the lowest for arthroscopic partial meniscectomy (utility loss of 0.05, ie, 18 days lost in perfect health). Costs of surgical delay per patient were highest for bariatric surgery (€31/pp per week) and lowest for arthroscopic partial meniscectomy (−€2/pp per week). Weighted by operating room (OR) time bariatric surgery provides most value (€1.19/pp per OR minute) and arthroscopic partial meniscectomy provides the least value (€0.34/pp per OR minute). In a large hospital the net monetary loss due to prolonged waiting times was €700 840 after the first COVID-19 wave, an increase of 506% compared with the year before.Conclusions This surgical prioritisation framework can be tailored to specific centres and countries to support priority setting for delayed elective operations during and after the COVID-19 pandemic, both in and between surgical disciplines. In the long-term, the framework can contribute to the efficient distribution of OR time and will therefore add to the discussion on appropriate use of healthcare budgets. The online framework can be accessed via: https://stanwijn.shinyapps.io/priORitize/.

Water reuse and recycling in Canada has been alive and viable where there is a need for water conservation or to reduce nutrients going to rivers and lakes. A study on response to reuse shows many people are in favour, but not for drinking or washing/bathing. This is a position when water nearby is plentiful. Reuse of water for irrigation has occurred in Canada since the 1980’s in arid areas of the country. Guidelines have been developed across the country. Provincial or Federal regulation is minimal except for British Columbia. In this paper, reuse in Canada will be broken into three groups; residential, industrial and research. Sustainable development is a driver for residential and institutional sties. Industrial application is driven by lack of availability of water or costs which has led to the Zero Liquid Discharge sites in Canada, particularly in arid areas. There are companies in Canada designing and building equipment to meet the need in Canada and elsewhere. Research is also ongoing on reuse applications for treatment systems for inside sustainable homes and buildings. We are blest with abundant water in part of the country and the arid areas are leading the future for reuse in Canada.

BackgroundHighly connected individuals disseminate information effectively within their social network. To apply this concept to inflammatory bowel disease (IBD) care and lay the foundation for network interventions to disseminate high-quality treatment, we assessed the need for improving the IBD practices of highly connected clinicians. We aimed to examine whether highly connected clinicians who treat IBD patients were more likely to provide high-quality treatment than less connected clinicians.MethodsWe used network analysis to examine connections among clinicians who shared patients with IBD in the Veterans Health Administration between 2015-2018. We created a network comprised of clinicians connected by shared patients. We quantified clinician connections using degree centrality (number of clinicians with whom a clinician shares patients), closeness centrality (reach via shared contacts to other clinicians), and betweenness centrality (degree to which a clinician connects clinicians not otherwise connected). Using weighted linear regression, we examined associations between each measure of connection and two IBD quality indicators: low prolonged steroids use, and high steroid-sparing therapy use.ResultsWe identified 62,971 patients with IBD and linked them to 1,655 gastroenterologists and 7,852 primary care providers. Clinicians with more connections (degree) were more likely to exhibit high-quality treatment (less prolonged steroids beta -0.0268, 95%CI -0.0427, -0.0110, more steroid-sparing therapy beta 0.0967, 95%CI 0.0128, 0.1805). Clinicians who connect otherwise unconnected clinicians (betweenness) displayed more prolonged steroids use (beta 0.0003, 95%CI 0.0001, 0.0006). The presence of variation is more relevant than its magnitude.ConclusionsClinicians with a high number of connections provided more high-quality IBD treatments than less connected clinicians, and may be well-positioned for interventions to disseminate high-quality IBD care. However, clinicians who connect clinicians who are otherwise unconnected are more likely to display low-quality IBD treatment. Efforts to improve their quality are needed prior to leveraging their position to disseminate high-quality care.

Laser-matter interactions during laser powder bed fusion additive manufacturing remain poorly understood. Here, the authors combine in situ X-ray imaging and finite element simulations to show how detrimental pores form under printing conditions and develop a strategy to suppress them.

Social robots hold potential for supporting children’s well-being in classrooms. However, it is unclear which robot features add to a trustworthy relationship between a child and a robot and whether social robots are just as able to reduce stress as traditional interventions, such as listening to classical music. We set up two experiments wherein children interacted with a robot in a real-life school environment. Our main results show that regardless of the robotic features tested (intonation, male/female voice, and humor) most children tend to trust a robot during their first interaction. Adding humor to the robots’ dialogue seems to have a negative impact on children’s trust, especially for girls and children without prior experience with robots. In comparing a classical music session with a social robot interaction, we found no significant differences. Both interventions were able to lower the stress levels of children, however, not significantly. Our results show the potential for robots to build trustworthy interactions with children and to lower children’s stress levels. Considering these results, we believe that social robots provide a new tool for children to make their feelings explicit, thereby enabling children to share negative experiences (such as bullying) which would otherwise stay unnoticed.

BackgroundMachine learning (ML) algorithms provide effective ways to build prediction models using longitudinal information given their capacity to incorporate numerous predictor variables without compromising the accuracy of the risk prediction. Clinical risk prediction models in chronic hepatitis C virus (CHC) can be challenging due to non-linear nature of disease progression. We developed and compared two ML algorithms to predict cirrhosis development in a large CHC-infected cohort using longitudinal data.Methods and findingsWe used national Veterans Health Administration (VHA) data to identify CHC patients in care between 2000-2016. The primary outcome was cirrhosis development ascertained by two consecutive aspartate aminotransferase (AST)-to-platelet ratio indexes (APRIs) > 2 after time zero given the infrequency of liver biopsy in clinical practice and that APRI is a validated non-invasive biomarker of fibrosis in CHC. We excluded those with initial APRI > 2 or pre-existing diagnosis of cirrhosis, hepatocellular carcinoma or hepatic decompensation. Enrollment was defined as the date of the first APRI. Time zero was defined as 2 years after enrollment. Cross-sectional (CS) models used predictors at or closest before time zero as a comparison. Longitudinal models used CS predictors plus longitudinal summary variables (maximum, minimum, maximum of slope, minimum of slope and total variation) between enrollment and time zero. Covariates included demographics, labs, and body mass index. Model performance was evaluated using concordance and area under the receiver operating curve (AuROC). A total of 72,683 individuals with CHC were analyzed with the cohort having a mean age of 52.8, 96.8% male and 53% white. There are 11,616 individuals (16%) who met the primary outcome over a mean follow-up of 7 years. We found superior predictive performance for the longitudinal Cox model compared to the CS Cox model (concordance 0.764 vs 0.746), and for the longitudinal boosted-survival-tree model compared to the linear Cox model (concordance 0.774 vs 0.764). The accuracy of the longitudinal models at 1,3,5 years after time zero also showed superior performance compared to the CS model, based on AuROC.ConclusionsBoosted-survival-tree based models using longitudinal information are statistically superior to cross-sectional or linear models for predicting development of cirrhosis in CHC, though all four models were highly accurate. Similar statistical methods could be applied to predict outcomes in other non-linear chronic disease states.

Selective laser sintering (SLS) is a prominent 3D printing modality that typically uses a polyamide (PA) powder as the substrate. One commercially available SLS material is known as PA2200, which is comprised of nylon 12 and titanium dioxide (TiO2) and is widely used to generate 3D-printed parts. Here, we report a unique optical photoluminescence (PL) characteristic of native, white PA2200, in which it yields a persistent, phosphorescence-type emission. An analysis of luminescence imaging data with emission measurements demonstrated that the anatase phase of the titanium dioxide additive is the source of the persistent PL properties. This characteristic of PA2200 enables advanced optical imaging applications, as demonstrated by luminescence imaging of an anatomical rat skeleton and a novel Derenzo-type phantom on a commercial image station. In summary, the light emission properties of PA2200 induced by the presence of anatase titanium dioxide open the door to a vast new array of complex optical applications, including the generation of imaging phantoms for training, calibration, and quality control.

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients.

An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research ‘farmlets’ in Waikato, Canterbury, and Otago (32⁻200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential ‘improved’ dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO2e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH4) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH4 from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N2O) emissions, representing 7⁻12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, ‘improved’ systems are predicted to generally result in lower emissions intensity. The ‘improved’ systems had lower GHG footprints than the ‘current’ system, except for one of the ‘improved’ systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the ‘improved’ systems were the key drivers of lower total GHG emissions in all three regions. ‘Improved’ systems designed to reduced N leaching generally also reduced GHG emissions.

X-ray Computed Tomography (CT) is one of the most commonly utilized anatomical imaging modalities for both research and clinical purposes. CT combines high-resolution, three-dimensional data with relatively fast acquisition to provide a solid platform for non-invasive human or specimen imaging. The primary limitation of CT is its inability to distinguish many soft tissues based on native contrast. While bone has high contrast within a CT image due to its material density from calcium phosphate, soft tissue is less dense and many are homogenous in density. This presents a challenge in distinguishing one type of soft tissue from another. A couple exceptions include the lungs as well as fat, both of which have unique densities owing to the presence of air or bulk hydrocarbons, respectively. In order to facilitate X-ray CT imaging of other structures, a range of contrast agents have been developed to selectively identify and visualize the anatomical properties of individual tissues. Most agents incorporate atoms like iodine, gold, or barium because of their ability to absorb X-rays, and thus impart contrast to a given organ system. Here we review the strategies available to visualize lung, fat, brain, kidney, liver, spleen, vasculature, gastrointestinal tract, and liver tissues of living mice using either innate contrast, or commercial injectable or ingestible agents with selective perfusion. Further, we demonstrate how each of these approaches will facilitate the non-invasive, longitudinal, in vivo imaging of pre-clinical disease models at each anatomical site.

Abstract Biochar, produced from the thermochemical conversion of biomass waste, has various applications owing to its broad utility and advantageous properties. This study employs a scientometric approach to comprehensively assess the advancements in biochar application from 2022 to 2023. Utilizing 13,357 bibliographic records sourced from the Web of Science Core Collection with the search term “biochar”, the analysis focuses on authorship, national contributions, and keyword trends. Findings demonstrate a continual rise in annual publications since 2009, albeit with a moderated growth rate in 2023. China leads in publication outputs, followed by USA and India, with Hailong Wang emerging as a prominent figure in biochar research. Keyword co-occurrence analyses identify key research themes such as biochar’s role in climate change mitigation, easing salinity and drought stress, immobilizing toxic metals, degrading organic pollutants, serving as additives in anaerobic digestion, and functioning as electrodes in microbial fuel cells. Among these, biochar’s application for global climate change mitigation gains significant attention, while its utilization as electrodes in microbial fuel cells emerges as a promising research frontier, indicating the growing need for sustainable energy sources. The study also outlines critical research gaps and future priorities for enhancing biochar application. Overall, it highlights the diverse applicability of biochar and offers valuable insight into research progression and forthcoming directions in biochar studies. Graphical Abstract