Frequency and Predictors of Suboptimal Prescribing Among a Cohort of Older Male Residents with Urinary Tract Infection

BACKGROUND Unnecessary antibiotic treatment of suspected urinary tract infection (UTI) is common in long-term care facilities (LTCFs). However, less is known about the extent of suboptimal treatment, in terms of antibiotic choice, dose, and duration, after the decision to use antibiotics has been made. METHODS We described the frequency of potentially suboptimal treatment among residents with an incident UTI (first during the study with none in the year prior) in Veterans Affairs’ (VA) Community Living Centers (CLCs, 2013-2018). Time trends were analyzed using Joinpoint regression. Residents with UTIs receiving potentially suboptimal treatment were compared to those receiving optimal treatment to identify resident characteristics predictive of suboptimal antibiotic treatment, using multivariable unconditional logistic regression models. RESULTS We identified 21,938 residents with an incident UTI treated in 120 VA CLCs, of which 96.0% were male. Potentially suboptimal antibiotic treatment was identified in 65.0% of residents and decreased 1.8% annually (p\u3c0.05). Potentially suboptimal initial drug choice was identified in 45.6% of residents, suboptimal dose frequency in 28.6%, and longer than recommended duration in 12.7%. Predictors of suboptimal antibiotic treatment included: prior fluoroquinolone exposure (adjusted odds ratio [aOR] 1.38), chronic renal disease (aOR 1.19), age \u3e85 years (aOR 1.17), prior skin infection (aOR 1.14), recent high white blood cell count (aOR 1.08), and genitourinary disorder (aOR 1.08). CONCLUSION Similar to findings in non-VA facilities, potentially suboptimal treatment was common but improving in CLC residents with an incident UTI. Predictors of suboptimal antibiotic treatment should be targeted with antibiotic stewardship interventions to improve UTI treatment

Predictors of potentially suboptimal treatment of urinary tract infections in long-term care facilities

Background: Suboptimal antibiotic treatment of urinary tract infection (UTI) is high in long-term care facilities (LTCFs) and likely varies between facilities. Large-scale evaluations have not been conducted. Aim: To identify facility-level predictors of potentially suboptimal treatment of UTI in Veterans Affairs (VA) LTCFs and to quantify variation across facilities. Methods: This was a retrospective cohort study of 21,938 residents in 120 VA LTCFs (2013–2018) known as Community Living Centers (CLCs). Potentially suboptimal treatment was assessed from drug choice, dose frequency, and/or treatment duration. To identify facility characteristics predictive of suboptimal UTI treatment, LTCFs with higher and lower rates of suboptimal treatment (≥median, \u3c median) were compared using unconditional logistic regression models. Joinpoint regression models were used to quantify average percentage difference across facilities. Multilevel logistic regression models were used to quantify variation across facilities. Findings: The rate of potentially suboptimal antibiotic treatment varied from 1.7 to 34.2 per 10,000 bed-days across LTCFs. The average percentage difference in rates across facilities was 2.5% (95% confidence interval (CI): 2.4–2.7). The only facility characteristic predictive of suboptimal treatment was the incident rate of UTI per 10,000 bed-days (odds ratio: 4.9; 95% CI: 2.3–10.3). Multilevel models demonstrated that 94% of the variation between facilities was unexplained after controlling for resident and CLC characteristics. The median odds ratio for the full multilevel model was 1.37. Conclusion: Potentially suboptimal UTI treatment was variable across VA LTCFs. However, most of the variation across LTCFs was unexplained. Future research should continue to investigate factors that are driving suboptimal antibiotic treatment in LTCFs

Targeted Gene Expression Profiling Predicts Meningioma Outcomes and Radiotherapy Responses

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P \u3c 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses

The role of networks to overcome large-scale challenges in tomography: The non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Focus on Function – a randomized controlled trial comparing two rehabilitation interventions for young children with cerebral palsy

<p>Abstract</p> <p>Background</p> <p>Children with cerebral palsy receive a variety of long-term physical and occupational therapy interventions to facilitate development and to enhance functional independence in movement, self-care, play, school activities and leisure. Considerable human and financial resources are directed at the "intervention" of the problems of cerebral palsy, although the available evidence supporting current interventions is inconclusive. A considerable degree of uncertainty remains about the appropriate therapeutic approaches to manage the habilitation of children with cerebral palsy. The primary objective of this project is to conduct a multi-site randomized clinical trial to evaluate the efficacy of a task/context-focused approach compared to a child-focused remediation approach in improving performance of functional tasks and mobility, increasing participation in everyday activities, and improving quality of life in children 12 months to 5 years of age who have cerebral palsy.</p> <p>Method/Design</p> <p>A multi-centred randomized controlled trial research design will be used. Children will be recruited from a representative sample of children attending publicly-funded regional children's rehabilitation centers serving children with disabilities in Ontario and Alberta in Canada. Target sample size is 220 children with cerebral palsy aged 12 months to 5 years at recruitment date. Therapists are randomly assigned to deliver either a context-focused approach or a child-focused approach. Children follow their therapist into their treatment arm. Outcomes will be evaluated at baseline, after 6 months of treatment and at a 3-month follow-up period. Outcomes represent the components of the International Classification of Functioning, Disability and Health, including body function and structure (range of motion), activities (performance of functional tasks, motor function), participation (involvement in formal and informal activities), and environment (parent perceptions of care, parental empowerment).</p> <p>Discussion</p> <p>This paper presents the background information, design and protocol for a randomized controlled trial comparing a task/context-focused approach to a child-focused remediation approach in improving functional outcomes for young children with cerebral palsy.</p> <p>Trial registration</p> <p>[clinical trial registration #: NCT00469872]</p

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Description of the Baseline Audiologic Characteristics of the Participants Enrolled in the Aging and Cognitive Health Evaluation in Elders Study

Purpose:The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study is a randomized clinical trial designed to determine the effects of a best-practice hearing intervention versus a successful aging health education control intervention on cognitive decline among community-dwelling older adults with untreated mild-to-moderate hearing loss. We describe the baseline audiologic characteristics of the ACHIEVE participants.Method:Participants aged 70–84 years (N = 977; Mage = 76.8) were enrolled at four U.S. sites through two recruitment routes: (a) an ongoing longitudinal study and (b) de novo through the community. Participants underwent diagnostic evaluation including otoscopy, tympanometry, pure-tone and speech audiometry, speech-in-noise testing, and provided self-reported hearing abilities. Baseline characteristics are reported as frequencies (percentages) for categorical variables or medians (interquartiles, Q1–Q3) for continuous variables. Between-groups comparisons were conducted using chi-square tests for categorical variables or Kruskal–Wallis test for continuous variables. Spearman correlations assessed relationships between measured hearing function and self-reported hearing handicap.Results:The median four-frequency pure-tone average of the better ear was 39 dB HL, and the median speech-in-noise performance was a 6-dB SNR loss, indicating mild speech-in-noise difficulty. No clinically meaningful differences were found across sites. Significant differences in subjective measures were found for recruitment route. Expected correlations between hearing measurements and self-reported handicap were found.Conclusions:The extensive baseline audiologic characteristics reported here will inform future analyses examining associations between hearing loss and cognitive decline. The final ACHIEVE data set will be publicly available for use among the scientific community

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Purpose: Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay, and seizures. To date, clinical features have been described for 11 patients with (likely) pathogenic SETD1B sequence variants. This study aims to further delineate the spectrum of the SETD1B-related syndrome based on characterizing an expanded patient cohort. Methods: We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Results: Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Conclusion: Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome