Search

Objective: The Berlin algorithm was developed to help diagnose axial SpA (axSpA), but new studies suggest some features typical of SpA are less specific than previously assumed. Furthermore, evidence is lacking for other SpA subtypes (e.g. peripheral SpA). We aimed to review the evidence on the performance of SpA features for diagnosing each SpA subtype., Methods: We conducted a systematic literature review of studies reporting the diagnostic performance of one or more SpA features in patients with suspected SpA. The external reference was the rheumatologist's diagnosis of SpA. Meta-analysis was performed, separately for each SpA subtype, to estimate pooled sensitivity, specificity and positive and negative likelihood ratios (LR+ and LR-, respectively). Meta-regression assessed the effect of covariates (e.g. feature's prevalence) on each feature's performance., Results: Of 13 844 articles screened, 46 were included. Sacroiliitis on MRI, damage on pelvic radiographs and elevated CRP had the best balance between LR+ and LR- (LR+ 3.9-17.0, LR- 0.5-0.7) for diagnosing axSpA. HLA-B27 had an LR+ lower than anticipated (LR+ 3.1). Inflammatory back pain (IBP) had a low LR+ (LR+ ≈1), but substantially decreased the likelihood of axSpA when absent (LR- 0.3). Conversely, peripheral features and extramusculoskeletal manifestations showed a high LR+ (LR+ 1.6-5.0), but were as common in axSpA as non-axSpA (LR- ≈1). The specificity of most features was reduced in settings when these were highly prevalent. Limited data precluded a detailed analysis on diagnosing other SpA subtypes., Conclusion: Imaging features and CRP have good diagnostic value for axSpA. However, the specificity of other features, especially HLA-B27 and IBP, is lower than previously known., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: This article aims to examine patient safety in general practice during COVID-19., Methods: In total, 5489 GP practices from 37 European countries and Israel filled in the online self-reported PRICOV-19 survey between November 2020 and December 2021. The outcome measures include 30 patient safety indicators on structure, process, and outcome., Results: The data showed that structural problems often impeded patient safety during COVID-19, as 58.6% of practices (3209/5479) reported limitations related to their building or infrastructure. Nevertheless, GP practices rapidly changed their processes, including the appointment systems. Implementation proved challenging as, although 76.1% of practices (3751/4932) developed a protocol to answer calls from potential COVID patients, only 34.4% (1252/3643) always used it. The proportion of practices reported having sufficient protected time in general practitioners' schedules to review guidelines remained consistent when comparing the pre-COVID (34.2%,1647/4813) with the COVID period (33.2%,1600/4813). Overall, 42.8% of practices (1966/4590) always informed home care services when patients were diagnosed with COVID-19, while this decreased to 30.1% for other major infectious diseases (1341/4458). Most practices reported at least one incident of delayed care in patients with an urgent condition, most often because the patient did not come to the practice sooner (60.4%, 2561/4237). Moreover, 31.1% of practices (1349/4199) always organized a team discussion when incidents happened. Overall, large variations were found across countries and patient safety indicators., Conclusions: The results demonstrated that European GP practices adopted numerous measures to deliver safe care during COVID-19. However, multilayered interventions are needed to improve infection control and GP practice accessibility in future pandemics., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The default mode network (DMN) is a widely distributed, intrinsic brain network thought to play a crucial role in internally directed cognition. The present study employs stereo-EEG in 13 human patients, obtaining high resolution neural recordings across multiple canonical DMN regions during two processes that have been associated with creative thinking: spontaneous and divergent thought. We probe these two DMN-associated higher cognitive functions through mind wandering and alternate uses tasks, respectively. Our results reveal DMN recruitment during both tasks, as well as a task-specific dissociation in spatiotemporal response dynamics. When compared to the fronto-parietal network, DMN activity was characterized by a stronger increase in gamma band power (30-70 Hz) coupled with lower theta band power (4-8 Hz). The difference in activity between the two networks was especially strong during the mind wandering task. Within the DMN, we found that the tasks showed different dynamics, with the alternate uses task engaging the DMN more during the initial stage of the task, and mind wandering in the later stage. Gamma power changes were mainly driven by lateral DMN sites, while theta power displayed task-specific effects. During alternate uses task, theta changes did not show spatial differences within the DMN, while mind wandering was associated to an early lateral and late dorsomedial DMN engagement. Furthermore, causal manipulations of DMN regions using direct cortical stimulation preferentially decreased the originality of responses in the alternative uses task, without affecting fluency or mind wandering. Our results suggest that DMN activity is flexibly modulated as a function of specific cognitive processes and supports its causal role in divergent thinking. These findings shed light on the neural constructs supporting different forms of cognition and provide causal evidence for the role of DMN in the generation of original connections among concepts., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: In KEYNOTE-522 (NCT03036488), neoadjuvant pembrolizumab plus chemotherapy and then adjuvant pembrolizumab significantly improved pathological complete response and event-free survival vs neoadjuvant chemotherapy in early-stage triple-negative breast cancer (TNBC). We report patient-reported outcomes (PROs) from KEYNOTE-522., Methods: Patients were randomized 2:1 to neoadjuvant pembrolizumab 200 mg or placebo every 3 weeks, plus 4 cycles of paclitaxel plus carboplatin and then 4 cycles of doxorubicin (or epirubicin) plus cyclophosphamide. After surgery, patients received adjuvant pembrolizumab or placebo for up to 9 cycles. European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) and EORTC Breast Cancer-Specific Quality of Life Questionnaire (EORTC QLQ-BR23) were prespecified secondary objectives. Between-group differences in least squares (LS) mean change from baseline (day 1 of cycle 1 in both neoadjuvant and adjuvant phases) to the prespecified latest time point with at least 60% completion and at least 80% compliance were assessed using a longitudinal model (no alpha error assigned)., Results: Week 21 (neoadjuvant phase) and week 24 (adjuvant phase) were the latest time points at which completion/compliance rates were ≥60%/80%. In the neoadjuvant phase, between-group differences (pembrolizumab plus chemotherapy [n = 762] vs placebo plus chemotherapy [n = 383]) in LS mean change from baseline to week 21 in QLQ-C30 global health status/quality of life (GHS/QoL), emotional functioning, and physical functioning were -1.04 (95% confidence interval = -3.46 to 1.38), -0.69 (95% CI = -3.13 to 1.75), and -2.85 (95% CI = -5.11 to -0.60), respectively. In the adjuvant phase, between-group differences (pembrolizumab [n = 539] vs placebo [n = 308]) in LS mean change from baseline to week 24 were -0.41 (95% CI = -2.60 to 1.77), -0.60 (95% CI = -2.99 to 1.79), and -1.57 (95% CI = -3.36 to 0.21)., Conclusions: No substantial differences in PRO assessments were observed between neoadjuvant pembrolizumab plus chemotherapy followed by adjuvant pembrolizumab vs neoadjuvant placebo plus chemotherapy in early-stage TNBC., Trial Registration: ClinicalTrials.gov, NCT03036488., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Blood-based biomarker tests can potentially change the landscape of colorectal cancer (CRC) screening. We characterize the conditions under which blood test screening would be as effective and cost-effective as annual fecal immunochemical testing or decennial colonoscopy., Methods: We used the 3 Cancer Information and Surveillance Modeling Network-Colon models to compare scenarios of no screening, annual fecal immunochemical testing, decennial colonoscopy, and a blood test meeting Centers for Medicare & Medicaid (CMS) coverage criteria (74% CRC sensitivity and 90% specificity). We varied the sensitivity to detect CRC (74%-92%), advanced adenomas (10%-50%), screening interval (1-3 years), and test cost ($25-$500). Primary outcomes included quality-adjusted life-years (QALY) gained from screening and costs for a US average-risk cohort of individuals aged 45 years., Results: Annual fecal immunochemical testing yielded 125-163 QALY gained per 1000 at a cost of $3811-$5384 per person, whereas colonoscopy yielded 132-177 QALY gained at a cost of $5375-$7031 per person. A blood test with 92% CRC sensitivity and 50% advanced adenoma sensitivity yielded 117-162 QALY gained if used every 3 years and 133-173 QALY gained if used every year but would not be cost-effective if priced above $125 per test. If used every 3 years, a $500 blood test only meeting CMS coverage criteria yielded 83-116 QALY gained at a cost of $8559-$9413 per person., Conclusion: Blood tests that only meet CMS coverage requirements should not be recommended to patients who would otherwise undergo screening by colonoscopy or fecal immunochemical testing because of lower benefit. Blood tests need higher advanced adenoma sensitivity (above 40%) and lower costs (below $125) to be cost-effective., (© The Author(s) 2024. Published by Oxford University Press.)

DNA methylation is an important epigenetic mark that modulates gene expression through the inhibition of transcriptional proteins binding to DNA. As in many other omics experiments, the issue of missing values is an important one, and appropriate imputation techniques are important in avoiding an unnecessary sample size reduction as well as to optimally leverage the information collected. We consider the case where relatively few samples are processed via an expensive high-density whole genome bisulfite sequencing (WGBS) strategy and a larger number of samples is processed using more affordable low-density, array-based technologies. In such cases, one can impute the low-coverage (array-based) methylation data using the high-density information provided by the WGBS samples. In this paper, we propose an efficient Linear Model of Coregionalisation with informative Covariates (LMCC) to predict missing values based on observed values and covariates. Our model assumes that at each site, the methylation vector of all samples is linked to the set of fixed factors (covariates) and a set of latent factors. Furthermore, we exploit the functional nature of the data and the spatial correlation across sites by assuming some Gaussian processes on the fixed and latent coefficient vectors, respectively. Our simulations show that the use of covariates can significantly improve the accuracy of imputed values, especially in cases where missing data contain some relevant information about the explanatory variable. We also showed that our proposed model is particularly efficient when the number of columns is much greater than the number of rows-which is usually the case in methylation data analysis. Finally, we apply and compare our proposed method with alternative approaches on two real methylation datasets, showing how covariates such as cell type, tissue type or age can enhance the accuracy of imputed values., (© The Author(s) 2024. Published by Oxford University Press.)

Background: A national guideline on peripheral arterial disease management in England was issued in August 2012. The impact on revascularization rates was examined and variation with socioeconomic deprivation assessed., Methods: Annual hospital admissions for England over 10 years (2008-2009 to 2017-2018) were examined using interrupted time series analysis. A pragmatic approach was used to classify admissions for revascularization into moderate and severe categories., Results: There were 309 839 admissions (56% for moderate peripheral arterial disease), with an overall annual admission rate for revascularization of 86 per 100 000 population aged 25+ years. The rate for moderate peripheral arterial disease marginally increased by 0.29 per 100 000 per year (95% c.i. -0.22 to 0.80) from 2008-2009 to 2012-2013. Following guideline introduction, this rate decreased. The equivalent for severe peripheral arterial disease increased by 1.33 per 100 000 (0.78 to 1.88). Following guideline introduction, this rate plateaued. The change in rate (slope) for moderate peripheral arterial disease of -2.81 per 100 000 per year (-3.52 to -2.10) after guideline introduction was greater than the change in rate for severe peripheral arterial disease of -1.95 per 100 000 per year (-2.73 to -1.17). For moderate peripheral arterial disease, the annual rate in the most socioeconomically deprived category was 15.6 per 100 000 lower in 2017-2018 compared with 2012-2013 (24.3% decrease). The impact progressively diminished with decreasing deprivation. In the least deprived category, the reduction was 5.2 per 100 000 (12.9% decrease). For severe peripheral arterial disease, the decrease was 1.2 per 100 000 (3.1% reduction) with no consistent variation in relation to deprivation., Conclusion: Introduction of the national peripheral arterial disease management guideline in England was associated with a reduction in admission rates for revascularization, especially for moderate peripheral arterial disease, with greater reduction in rates for moderate peripheral arterial disease in more socioeconomically deprived areas. Association, however, does not necessarily imply causation and alternative explanations cannot be ruled out., (© The Author(s) 2024. Published by Oxford University Press on behalf of BJS Foundation Ltd.)

Introduction: Zimbabwe has a smoking prevalence of 11.7% among the adult population (15 years and older). Thus, in the absence of effective tobacco control measures, the economic burden of tobacco use will be aggravated, especially considering the increasing tobacco industry activity in the country. Increasing cigarette prices is one possible strategy to reduce tobacco consumption. This study seeks to examine the relationship between cigarette prices and smoking experimentation among children in Zimbabwe, thereby expanding the evidence base for the likely impact of excise taxes on cigarette demand in low- and middle-income countries., Aims and Methods: A survival analysis using the Zimbabwe 2014 Global Youth Tobacco Survey data., Results: A 10% increase in the price of cigarettes reduces the probability of experimenting with smoking by 9%. Also, children are more likely to experiment with smoking if they have a smoking brother or father who smokes, or see teachers who smoke. The likelihood of experimenting with smoking is higher among boys than girls and is positively associated with age., Conclusions: There is strong evidence that increasing excise taxes can play an effective role in discouraging children from experimenting with cigarette smoking. Considering the relatively low excise tax burden in Zimbabwe, the government should consider substantially increasing the excise tax burden., Implications: With the number of smokers in low- and middle-income countries expected to increase as the industry intensively expands its market by targeting the youth, increasing excise taxes will play a significant role in preventing children from initiating smoking and help those who are already using tobacco to quit. An increase in the excise tax increases the retail price of tobacco products, making them less affordable, and reduces the demand for them., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Background and Aims: Most paediatric inflammatory bowel disease [IBD] studies are performed after medications are approved in adults, and the majority of participants in these studies are adolescents. We hypothesised that adolescent-onset IBD is not fundamentally different from adult-onset IBD. If this is correct, the value of delaying access to novel drugs in adolescents becomes questioned., Methods: Data from 11 randomised, double-blind, placebo-controlled, adult Phases 2 and 3 trials of four biologics were analysed. Participants were categorised as having adolescent- or adult-onset disease [diagnosed 12 to <18, or ≥18 years]. Multivariable modelling explored the association between age at diagnosis and response to treatment, after adjustment for disease duration, extent, and severity at baseline. Data from dose arms were pooled to evaluate similarity of therapeutic response between adolescent- and adult-onset IBD within the same trial [not between doses or across trials]. Ratios of odds ratios [ORs] between the two groups were evaluated., Results: Data from 6283 study participants (2575 with Crohn's disease [CD], 3708 with ulcerative colitis [UC]) were evaluated. Of 2575 study participants with CD, 325 were 12-<18 years old at diagnosis; 836 participants [32.4%] received placebo. Of 3708 participants with UC, 221 were 12-<18 years old at diagnosis; 1212 [33%] were receiving placebo. The majority of the ratios of ORs were within 2-fold, suggesting that responses in adolescent- and adult-onset participants are generally similar., Conclusion: Data presented lend support for extrapolating efficacy of biologics from adults to adolescents with IBD, which would facilitate earlier labelling and patient access., (© The Author(s) 2024. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Summary: Motivated by theoretical and practical issues that arise when applying Principal component analysis (PCA) to count data, Townes et al. introduced "Poisson GLM-PCA", a variation of PCA adapted to count data, as a tool for dimensionality reduction of single-cell RNA sequencing (scRNA-seq) data. However, fitting GLM-PCA is computationally challenging. Here we study this problem, and show that a simple algorithm, which we call "Alternating Poisson Regression" (APR), produces better quality fits, and in less time, than existing algorithms. APR is also memory-efficient and lends itself to parallel implementation on multi-core processors, both of which are helpful for handling large scRNA-seq datasets. We illustrate the benefits of this approach in three publicly available scRNA-seq datasets. The new algorithms are implemented in an R package, fastglmpca., Availability and Implementation: The fastglmpca R package is released on CRAN for Windows, macOS and Linux, and the source code is available at github.com/stephenslab/fastglmpca under the open source GPL-3 license. Scripts to reproduce the results in this paper are also available in the GitHub repository and on Zenodo., (© The Author(s) 2024. Published by Oxford University Press.)

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types., (© The Author(s) 2024. Published by Oxford University Press.)

The development and evaluation of novel treatment combinations is a key component of modern clinical research. The primary goals of factorial clinical trials of treatment combinations range from the estimation of intervention-specific effects, or the discovery of potential synergies, to the identification of combinations with the highest response probabilities. Most factorial studies use balanced or block randomization, with an equal number of patients assigned to each treatment combination, irrespective of the specific goals of the trial. Here, we introduce a class of Bayesian response-adaptive designs for factorial clinical trials with binary outcomes. The study design was developed using Bayesian decision-theoretic arguments and adapts the randomization probabilities to treatment combinations during the enrollment period based on the available data. Our approach enables the investigator to specify a utility function representative of the aims of the trial, and the Bayesian response-adaptive randomization algorithm aims to maximize this utility function. We considered several utility functions and factorial designs tailored to them. Then, we conducted a comparative simulation study to illustrate relevant differences of key operating characteristics across the resulting designs. We also investigated the asymptotic behavior of the proposed adaptive designs. We also used data summaries from three recent factorial trials in perioperative care, smoking cessation, and infectious disease prevention to define realistic simulation scenarios and illustrate advantages of the introduced trial designs compared to other study designs., (© The Author 2024. Published by Oxford University Press. All rights reserved. For Permissions, email: journals.permissions@oup.com.)

Motivation: As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data. We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth., Results: We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data., Availability and Implementation: All the code is free and open source. Docker images are also available. See gitlab.pasteur.fr/nyx/LarvaTagger.jl., (© The Author(s) 2024. Published by Oxford University Press.)

Background: We aimed to define levels of unmet supportive care needs in people with primary brain tumor and to reach expert consensus on feasibility of addressing patients' needs in clinical practice., Methods: We conducted secondary analysis of a prospective cohort study of people diagnosed with high-grade glioma (n = 116) who completed the Supportive Care Needs Survey-Short Form during adjuvant chemoradiation therapy. Participants were allocated to 1 of 3 categories: no need ("no need" for help on all items), low need ("low need" for help on at least 1 item, but no "moderate" or "high" need), or moderate/high need (at least 1 "moderate" or "high" need indicated). Clinical capacity to respond to the proportion of patients needing to be prioritized was assessed., Results: Overall, 13% (n = 5) were categorized as no need, 23% (n = 27) low need, and 64% (n = 74) moderate/high need. At least 1 moderate/high need was reported in the physical and daily living domain (42%) and the psychological (34%) domain. In recognition of health system capacity, the moderate/high need category was modified to distinguish between moderate need ("moderate" need indicated for at least 1 item but "high" need was not selected for any item) and high need (at least 1 "high" need indicated). Results revealed 24% (n = 28) moderate need and 40% (n = 46) high need. Those categorized as high need indicated needing assistance navigating the health system and information., Conclusions: Using four step allocations resulted in 40% of patients indicating high need. Categories may facilitate appropriate triaging and guide stepped models of healthcare delivery., (© The Author(s) 2024. Published by Oxford University Press.)

Mediation analysis with contemporaneously observed multiple mediators is a significant area of causal inference. Recent approaches for multiple mediators are often based on parametric models and thus may suffer from model misspecification. Also, much of the existing literature either only allow estimation of the joint mediation effect or estimate the joint mediation effect just as the sum of individual mediator effects, ignoring the interaction among the mediators. In this article, we propose a novel Bayesian nonparametric method that overcomes the two aforementioned drawbacks. We model the joint distribution of the observed data (outcome, mediators, treatment, and confounders) flexibly using an enriched Dirichlet process mixture with three levels. We use standardization (g-computation) to compute all possible mediation effects, including pairwise and all other possible interaction among the mediators. We thoroughly explore our method via simulations and apply our method to a mental health data from Wisconsin Longitudinal Study, where we estimate how the effect of births from unintended pregnancies on later life mental depression (CES-D) among the mothers is mediated through lack of self-acceptance and autonomy, employment instability, lack of social participation, and increased family stress. Our method identified significant individual mediators, along with some significant pairwise effects., (© The Author 2024. Published by Oxford University Press. All rights reserved. For Permissions, email: journals.permissions@oup.com.)

Objectives: We sought to (1) characterize the process of diagnosing pneumonia in an emergency department (ED) and (2) examine clinician reactions to a clinician-facing diagnostic discordance feedback tool., Materials and Methods: We designed a diagnostic feedback tool, using electronic health record data from ED clinicians' patients to establish concordance or discordance between ED diagnosis, radiology reports, and hospital discharge diagnosis for pneumonia. We conducted semistructured interviews with 11 ED clinicians about pneumonia diagnosis and reactions to the feedback tool. We administered surveys measuring individual differences in mindset beliefs, comfort with feedback, and feedback tool usability. We qualitatively analyzed interview transcripts and descriptively analyzed survey data., Results: Thematic results revealed: (1) the diagnostic process for pneumonia in the ED is characterized by diagnostic uncertainty and may be secondary to goals to treat and dispose the patient; (2) clinician diagnostic self-evaluation is a fragmented, inconsistent process of case review and follow-up that a feedback tool could fill; (3) the feedback tool was described favorably, with task and normative feedback harnessing clinician values of high-quality patient care and personal excellence; and (4) strong reactions to diagnostic feedback varied from implicit trust to profound skepticism about the validity of the concordance metric. Survey results suggested a relationship between clinicians' individual differences in learning and failure beliefs, feedback experience, and usability ratings., Discussion and Conclusion: Clinicians value feedback on pneumonia diagnoses. Our results highlight the importance of feedback about diagnostic performance and suggest directions for considering individual differences in feedback tool design and implementation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Despite antibiotic stewardship programs existing in most acute care hospitals, there continues to be variation in appropriate antibiotic use. While existing research examines individual prescriber behavior, contextual reasons for variation are poorly understood., Methods: We conducted an explanatory, sequential mixed-methods study of a purposeful sample of 7 hospitals with varying discharge antibiotic overuse. For each hospital, we conducted surveys, document analysis, and semi-structured interviews with antibiotic stewardship and clinical stakeholders. Data were analyzed separately and mixed during the interpretation phase, where each hospital was examined as a case, with findings organized across cases using a strengths, weaknesses, opportunities, and threats framework to identify factors accounting for differences in antibiotic overuse across hospitals., Results: Surveys included 85 respondents. Interviews included 90 respondents (31 hospitalists, 33 clinical pharmacists, 14 stewardship leaders, 12 hospital leaders). On surveys, clinical pharmacists at hospitals with lower antibiotic overuse were more likely to report feeling: respected by hospitalist colleagues (P = .001), considered valuable team members (P = .001), and comfortable recommending antibiotic changes (P = .02). Based on mixed-methods analysis, hospitals with low antibiotic overuse had 4 distinguishing characteristics: (1) robust knowledge of and access to antibiotic stewardship guidance; (2) high-quality clinical pharmacist-physician relationships; (3) tools and infrastructure to support stewardship; and (4) highly engaged infectious diseases physicians who advocated stewardship principles., Conclusions: This mixed-methods study demonstrates the importance of organizational context for high performance in stewardship and suggests that improving antimicrobial stewardship requires attention to knowledge, interactions, and relationships between clinical teams and infrastructure that supports stewardship and team interactions., Competing Interests: Potential conflicts of interest. S. A. F. reports grants or contracts, paid to institution, from BCBSM and AHRQ, and personal fees from Wiley Publishing. T. N. G. reports grants or contracts paid to institution from BCBSM and AHRQ. L. A. P. reports grants or contracts from BCBSM and AHRQ. W. R. B. reports participation on a data and safety monitoring board or advisory board as scientific advisor for research with The Joint Commission regarding outpatient stewardship. E. S. S. reports grants or contracts with the Centers for Disease Control and Prevention (CDC) Epicenter University of Utah (Matt Samore, principal investigator; author's role is a co-investigator); consulting fees for educational content paid to author from Prime Education LLC; travel expenses paid to the Society for Healthcare Epidemiology of America (SHEA) 2023 and to IDWeek 2022 (speaker). A. H. reports grants or contracts with CDC, AHRQ, and Patient-Centered Outcomes Research Institute, and a leadership or fiduciary role on the Pediatric Infectious Diseases Society Board. A. M. M. has received grant support from and is a physician consultant to the Michigan Department of Health and Human Services, unrelated to the submitted work; has received payment for expert testimony, unrelated to submitted work; was a member of the SHEA Board of Trustees 2020–2022; served as board member of Michigan Infectious Diseases Society; and is a shareholder of Pfizer. V. M. M. reports grants or contracts paid to institution from AHRQ, CDC, National Institutes of Health, and BCBSM. S. L. Z. reports grants or contracts to institution from AHRQ. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Effective molecular representation learning is very important for Artificial Intelligence-driven Drug Design because it affects the accuracy and efficiency of molecular property prediction and other molecular modeling relevant tasks. However, previous molecular representation learning studies often suffer from limitations, such as over-reliance on a single molecular representation, failure to fully capture both local and global information in molecular structure, and ineffective integration of multiscale features from different molecular representations. These limitations restrict the complete and accurate representation of molecular structure and properties, ultimately impacting the accuracy of predicting molecular properties. To this end, we propose a novel multi-view molecular representation learning method called MvMRL, which can incorporate feature information from multiple molecular representations and capture both local and global information from different views well, thus improving molecular property prediction. Specifically, MvMRL consists of four parts: a multiscale CNN-SE Simplified Molecular Input Line Entry System (SMILES) learning component and a multiscale Graph Neural Network encoder to extract local feature information and global feature information from the SMILES view and the molecular graph view, respectively; a Multi-Layer Perceptron network to capture complex non-linear relationship features from the molecular fingerprint view; and a dual cross-attention component to fuse feature information on the multi-views deeply for predicting molecular properties. We evaluate the performance of MvMRL on 11 benchmark datasets, and experimental results show that MvMRL outperforms state-of-the-art methods, indicating its rationality and effectiveness in molecular property prediction. The source code of MvMRL was released in https://github.com/jedison-github/MvMRL., (© The Author(s) 2024. Published by Oxford University Press.)

Introduction: Research on the health of older Veterans in Canada is an emerging area. Few population-based studies in Canada have included older Veterans as a specific group of interest. This paper describes a cohort of self-identified Veterans within the Canadian Longitudinal Study on Aging (CLSA)., Materials and Methods: Using data from the CLSA baseline assessment (2011-2015), we describe sociodemographic and health characteristics along with military-related variables in a cohort of Veterans in Canada. We also estimate the number of Canadian and non-Canadian Veterans living in Canada at the time of the CLSA baseline data collection., Results: We estimate that at the CLSA baseline, there were 718,893 (95% confidence interval [CI], 680,033-757,110) Canadian Veterans and 185,548 (95% CI, 165,713-205,100) non-Canadian Veterans aged 45-85 years living in Canada. Veterans were older and predominantly male compared to non-Veterans in the CLSA. Following age and sex adjustment, the distribution of sociodemographic and health characteristics was similar across all groups. The majority (> 85%) of participants in each comparison group reported self-rated general and mental health as excellent, very good, or good. Following age and sex adjustment, most characteristics across groups remained similar. One exception was mental health, where a greater proportion of Veterans screened positive for depression and anxiety relative to non-Veterans., Conclusions: Using CLSA baseline data, we estimate the number of older Veterans in Canada and present descriptive data that highlight interesting differences and similarities between Veterans and non-Veterans living in Canada. Canadian and non-Canadian Veterans in the CLSA are presented separately, with the latter group having not been previously studied in Canada. This paper presents a snapshot of a cohort of self-identified Veterans within the CLSA at study baseline and highlights the potential of the CLSA as a vehicle for studying the aging Veteran population in Canada for years to come., (© The Association of Military Surgeons of the United States 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Multigene panel testing is an important component of cancer treatment plans and risk assessment, but there are many different panel options and choosing the most appropriate panel can be challenging for health care providers and patients. Electronic tools have been proposed to help patients make informed decisions about which gene panel to choose by considering their preferences and priorities., Materials and Methods: An electronic decision aid (DA) tool was developed in line with the International Patient Decision Aids Standards collaboration. The multidisciplinary project team collaborated with an external health care communications agency and the MGH Cancer Center Patient and Family Advisory Council (PFAC) to develop the DA. Surveys of genetic counselors and patients were used to scope the content, and alpha testing was used to refine the design and content., Results: Surveys of genetic counselors (n = 12) and patients (n = 228) identified common themes in discussing panel size and strategies for helping patients decide between panels and in identifying confusing terms for patients and distribution of patients' choices. The DA, organized into 2 major sections, provides educational text, graphics, and videos to guide patients through the decision-making process. Alpha testing feedback from the PFAC (n = 4), genetic counselors (n = 3) and a group of lay people (n = 8) identified areas to improve navigation, simplify wording, and improve layout., Conclusion: The DA developed in this study has the potential to facilitate informed decision-making by patients regarding cancer genetic testing. The distinctive feature of this DA is that it addresses the specific question of which multigene panel may be most suitable for the patient. Its acceptability and effectiveness will be evaluated in future studies., (© The Author(s) 2024. Published by Oxford University Press.)

Creative idea generation plays an important role in promoting successful memory formation. Yet, its underlying neural correlates remain unclear. We investigated the self-generated learning of creative ideas motivated by the schema-linked interactions between medial prefrontal and medial temporal regions framework. This was achieved by having participants generate ideas in the alternative uses task, self-evaluating their ideas based on novelty and source (i.e. new or old), and then later being tested on the recognition performance of the generated ideas. At the behavioral level, our results indicated superior performances in discriminating novel ideas, highlighting the novelty effect on memory. At the neural level, the regions-of-interest analyses revealed that successful recognition of novel ideas was associated with greater activations in the hippocampus (HPC) and medial prefrontal cortex (mPFC) during ideation. However, only activation in the right HPC was positively related to the successful recognition of novel ideas. Importantly, the weaker the connection between the right HPC and left mPFC, the higher the recognition accuracy of novel ideas. Moreover, activations in the right HPC and left mPFC were both effective predictors of successful recognition of novel ideas. These findings uniquely highlight the role of novelty in promoting self-generated learning of creative ideas., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Objectives: To characterize the complex interplay between multiple clinical conditions in a time-to-event analysis framework using data from multiple hospitals, we developed two novel one-shot distributed algorithms for competing risk models (ODACoR). By applying our algorithms to the EHR data from eight national children's hospitals, we quantified the impacts of a wide range of risk factors on the risk of post-acute sequelae of SARS-COV-2 (PASC) among children and adolescents., Materials and Methods: Our ODACoR algorithms are effectively executed due to their devised simplicity and communication efficiency. We evaluated our algorithms via extensive simulation studies as applications to quantification of the impacts of risk factors for PASC among children and adolescents using data from eight children's hospitals including the Children's Hospital of Philadelphia, Cincinnati Children's Hospital Medical Center, Children's Hospital of Colorado covering over 6.5 million pediatric patients. The accuracy of the estimation was assessed by comparing the results from our ODACoR algorithms with the estimators derived from the meta-analysis and the pooled data., Results: The meta-analysis estimator showed a high relative bias (∼40%) when the clinical condition is relatively rare (∼0.5%), whereas ODACoR algorithms exhibited a substantially lower relative bias (∼0.2%). The estimated effects from our ODACoR algorithms were identical on par with the estimates from the pooled data, suggesting the high reliability of our federated learning algorithms. In contrast, the meta-analysis estimate failed to identify risk factors such as age, gender, chronic conditions history, and obesity, compared to the pooled data., Discussion: Our proposed ODACoR algorithms are communication-efficient, highly accurate, and suitable to characterize the complex interplay between multiple clinical conditions., Conclusion: Our study demonstrates that our ODACoR algorithms are communication-efficient and can be widely applicable for analyzing multiple clinical conditions in a time-to-event analysis framework., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Identifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene-Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene-environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB., (© The Author 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Warfare has long impeded vaccination programs in polio-endemic Afghanistan. We aimed to describe progress in access to children under 5, oral polio vaccine (OPV) coverage among children under 5 in nationwide polio campaigns, and polio surveillance performance indicators after the Islamic Republic of Afghanistan collapsed to Taliban forces in August 2021., Methods: Trends in the number of wild poliovirus type 1 (WPV1) and circulating vaccine-derived poliovirus type 2 (cVDPV2) cases and surveillance indicators from 2015 to 2023, and trends in the OPV coverage in the November 2020-June 2022 polio campaigns, were described., Results: From 2015 to mid-July 2020, 74 of 126 (58.7%) WPV1 cases were reported from inaccessible areas. In November 2020, 34.1% of target children under 5 were inaccessible; in November 2021 (the first postchange polio campaign), all were accessible. From November 2020, under-5 OPV coverage of 69.9% rose steadily to 99.9% in the May 2022 campaign. The number of cVDPV cases fell from 308 (2020) to zero (2022). June 2022's house-to-house OPV coverage was 34.2% higher than non-house-to-house modalities. Nonpolio acute flaccid paralysis and stool adequacy rates rose from 18.5/100 000 and 92.6% in 2020 to 24.3/100 000 and 94.4% in 2022, respectively., Conclusions: Children's inaccessibility no longer vitiates polio eradication; polio surveillance systems are less likely to miss any poliovirus circulation., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Objective: Deep-learning techniques, particularly the Transformer model, have shown great potential in enhancing the prediction performance of longitudinal health records. Previous methods focused on fixed-time risk prediction, however, time-to-event prediction is often more appropriate for clinical scenarios. Here, we present STRAFE, a generalizable survival analysis Transformer-based architecture for electronic health records., Materials and Methods: The input for STRAFE is a sequence of visits with SNOMED-CT codes in OMOP-CDM format. A Transformer-based architecture was developed to calculate probabilities of the occurrence of the event in each of 48 months. Performance was evaluated using a real-world claims dataset of over 130 000 individuals with stage 3 chronic kidney disease (CKD)., Results: STRAFE showed improved mean absolute error (MAE) compared to other time-to-event algorithms in predicting the time to deterioration to stage 5 CKD. Additionally, STRAFE showed an improved area under the receiver operating curve compared to binary outcome algorithms. We show that STRAFE predictions can improve the positive predictive value of high-risk patients by 3-fold. Finally, we suggest a novel visualization approach to predictions on a per-patient basis., Discussion: Time-to-event predictions are the most appropriate approach for clinical predictions. Our deep-learning algorithm outperformed not only other time-to-event prediction algorithms but also fixed-time algorithms, possibly due to its ability to train on censored data. We demonstrated possible clinical usage by identifying the highest-risk patients., Conclusions: The ability to accurately identify patients at high risk and prioritize their needs can result in improved health outcomes, reduced costs, and more efficient use of resources., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The brain networks for the first (L1) and second (L2) languages are dynamically formed in the bilingual brain. This study delves into the neural mechanisms associated with logographic-logographic bilingualism, where both languages employ visually complex and conceptually rich logographic scripts. Using functional Magnetic Resonance Imaging, we examined the brain activity of Chinese-Japanese bilinguals and Japanese-Chinese bilinguals as they engaged in rhyming tasks with Chinese characters and Japanese Kanji. Results showed that Japanese-Chinese bilinguals processed both languages using common brain areas, demonstrating an assimilation pattern, whereas Chinese-Japanese bilinguals recruited additional neural regions in the left lateral prefrontal cortex for processing Japanese Kanji, reflecting their accommodation to the higher phonological complexity of L2. In addition, Japanese speakers relied more on the phonological processing route, while Chinese speakers favored visual form analysis for both languages, indicating differing neural strategy preferences between the 2 bilingual groups. Moreover, multivariate pattern analysis demonstrated that, despite the considerable neural overlap, each bilingual group formed distinguishable neural representations for each language. These findings highlight the brain's capacity for neural adaptability and specificity when processing complex logographic languages, enriching our understanding of the neural underpinnings supporting bilingual language processing., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Shared decision making (SDM) is considered fundamental to person-centred care. However, applying SDM may be a challenge for residents in general practice, since it is a complex competence that requires the integration of knowledge and skills from several competency domains., Objective: To support learning of SDM during medical residency, we aimed to gain insight in Dutch residents' observed and perceived SDM performance in general practice., Methods: We evaluated residents' SDM performance from an observer, resident, and patient perspective. Consultations of first- and third-year residents were recorded. Trained observers used the validated Observing Patient Involvement (OPTION5) scale to assess observed SDM performance of residents in 98 actual recorded consultations. Perceived SDM performance was evaluated by residents and patients completing validated SDM questionnaires, supplemented with questions about (the context of) the consultation and perceived relevance of SDM immediately after the consultation. The data were analysed using descriptive statistics (mean, SD, minimums, and maximums) and explorative bivariate analyses., Results: The residents' observed mean SDM performance was 19.1 (range, 0-100, SD = 10.9), mean resident self-reported SDM performance was 56.9 (range, 0-100, SD = 18.5), and mean patient-reported SDM performance was 73.3 (range, 0-100, SD = 26.8). We found a significant and positive correlation between observed SDM performance and residents' perceived relevance of SDM for the consultation (t = 4.571, P ≤ 0.001) and the duration of the consultation (r = 0.390, P ≤ 0.001)., Conclusions: This study showed that there is room for increasing awareness of the potential incongruence between observed and perceived SDM performance during medical residency, in order to facilitate the implementation of SDM in clinical practice., (© The Author(s) 2024. Published by Oxford University Press.)

Introduction: Successful employment is a functional outcome of high importance for veterans after military discharge. There is a significant rising concern regarding exposure to military sexual trauma (MST) and related mental health outcomes that can impair functional outcomes, such as employment. Although resilience training is a key component of preparing for military service, to date the impact of resilience on employment outcomes for veterans with exposure to MST has yet to be examined. We sought to examine the relationship between resilience and employment in a national sample of post-9/11 veterans with and without MST exposure., Materials and Methods: A national survey was conducted between October 2021 and January 2022 to respond to the 2021 National Defense Authorization Act mandate to identify factors affecting post-9/11 women veteran's unemployment. Of veterans, 1,185 completed the survey. Of these, 565 (47.6%) were post-9/11 veterans. The survey collected data on demographics and employment; MST, adult sexual trauma (AST, outside of military), and childhood sexual trauma (CST) exposure; resilience (Response to Stressful Experiences Scale); Post Traumatic Stress Disorder (PTSD) Checklist (PCL-5); and depression (Patient Health Questionnaire-2). Multivariable logistic regression models identified gender-specific associations of resilience with employment among those exposed and not exposed to MST, adjusting for AST, CST, PTSD, and depression. Significance was set at P < .05., Results: Of 322 women and 243 men post-9/11 veterans, 86.5% were employed. MST exposure (MST[+]) was reported by 31.4% (n = 101) of women and 16.9% (n = 41) of men. MST(+) women veterans were more likely to report CST (35.6% vs. 14.5%; P < .001), AST (68.3% vs. 17.2%; P < .001), and both CST and AST (19.8% vs. 7.2%; P < .001) than MST(-) women. MST(+) men were more likely to report AST (65.9% vs. 7.9%; P < .001), and both CST and AST (14.6% vs. 1.0%; P < .001) than MST(-) men. Levels of self-reported resilience were similar for MST(+) women and men and their MST(-) counterparts (women: 11.1 vs. 11.0; men: 11.5 vs. 12.0). For MST(+) women, each unit increase in resilience was associated with a 36% increase in odds of employment (OR: 1.36, 95% CI, 1.08-1.71); resilience was not associated with increased odds of employment among MST(-) women. Among MST(+) men veterans, each unit increase in resilience was associated with an 83% increase in odds of employment (aOR: 1.83, 95% CI, 1.13-2.98), and like women veterans, resilience was not associated with employment among MST(-) men., Conclusions: Among MST(+) women and men post-9/11 veterans, higher resilience was associated with increased odds of employment, whereas resilience was not associated with employment in MST(-) veterans. These findings suggest that resiliency during and after military service is a key component for potentially improving long-term outcomes. Improving resilience using evidence-based approaches among post-9/11 veterans exposed to MST may be an important avenue for increasing successful functional outcomes such as employment. Moreover, MST(+) women and men veterans may benefit from trauma-informed care as a substantial proportion of these individuals also report exposure to CST, AST, PTSD, and depression., (Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2023. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Background: Concerning levels of stress, strain, and poorer mental health are observed in family carers of patients diagnosed with high-grade glioma (HGG). Understanding the reported unmet needs of these carers will enable future interventions to address such needs to improve their preparedness for care and well-being. In this secondary analysis, we aimed to explore: (i) what carers of people with HGG perceive could improve their preparedness to care ; and (ii) what needs carers reported they required additional support with., Methods: Responses from 188 carers of patients with HGG participating in a randomized controlled trial of the Care-IS intervention were analyzed to identify reported unmet needs. Of this larger sample, 92 participants answered a qualitative question seeking to identify perceived unmet needs in carer preparedness over 12 months. These responses comprised the data for the current secondary analysis. Content analysis was used to analyze the qualitative data and observe trends across participant responses., Results: Five overarching themes were identified: carer needs , providing emotional and practical care , coping with uncertainty , coping with the consequences of illness progression , and processing and supporting end-of-life care. Notably, the content analysis identified differences in response numbers between groups in the Care-IS trial, particularly with the control group having more needs regarding illness progression and end-of-life care., Conclusions: Future interventions aimed at improving the well-being and preparedness of carers of people with HGG should consider providing better support centered on carer needs, their changed circumstances, living with uncertainty, and care transition., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology and the European Association of Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Context: Food labelling is a global strategy recommended to reduce noncommunicable diseases. Few reviews, however, have focused on food label use in sub-Saharan Africa (SSA)., Objective: To determine the prevalence of food label use and describe determinants of food label use and purchasing decisions of adult consumers in SSA., Data Source: PubMed (Medline), Web of Science, Cochrane Central, and Google Scholar databases., Data Extraction: Search criteria included adults (aged ≥18 years), conducted in SSA, focusing on food label use or understanding and their determinants or determinants of food-purchasing decisions, and articles published in English., Study Quality and Data Analysis: Risk-of-bias assessment of included studies was done using the Joann Briggs Institute checklist for prevalence studies. Publication bias was assessed using funnel plots and Egger's test. Analysis included narrative synthesis and moderator and meta-analyses of food label use., Results: A total of 124 articles were found, of which 21 were included in the review. Of participants in the selected studies, 58% were female. About 80% reported food label use (either used sometimes or always) (70%-88%) (I2 = 97%; n = 6223), and regular use was estimated at 36% (28%-45%) (I2 = 97%; n = 5147). Food label use was influenced by level of income, education, employment status, and household size. Food-purchasing decisions were influenced by attributes such as expiry dates, price, and taste. Major recommendations reported were tailored education campaigns and reducing barriers to food label use., Conclusion: Most (80%) of adults in SSA reported using food labels; however, only about one-third used them consistently. Demographic and situation factors determined patterns in food label use, whereas product attributes influenced food purchasing decisions. Complexity of these determinants requires adopting tailored, multisectoral, theory-driven programs to improve food label use., Systematic Review Registration: Open Science Framework (https://osf.io/kc562)., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The use of MRI and arthroscopy are considered low-value care in most patients with degenerative knee disease. To reduce these modalities, there have been multiple efforts to increase awareness. Reductions have been shown for general hospitals (GH), but it is unclear whether this may be partly explained by a shift of patients receiving these modalities in independent treatment centers (ITCs). The aims of this study were to assess (i) whether the trend in use of MRI and arthroscopy in patients with degenerative knee disease differs between ITCs and GH, and (ii) whether the Dutch efforts to raise awareness on these recommendations were associated with a change in the trend for both types of providers. All patients insured by a Dutch healthcare insurer aged ≥50 years with a degenerative knee disease who were treated in a GH or ITC between July 2014 and December 2019 were included. Linear regression was used with the quarterly percentage of patients receiving an MRI or knee arthroscopy weighted by center volume, as the primary outcome. Interrupted time-series analysis was used to evaluate the effect of the Dutch efforts to raise awareness. A total of 14 702 patients included were treated in 90 GHs (n = 13 303, 90.5%) and 29 ITCs (n = 1399, 9.5%). Across the study period, ITCs on an average had a 16% higher MRI use (P < .001) and 9% higher arthroscopy use (P = .003). MRI use did not change in both provider types, but arthroscopy use significantly decreased and became stronger in ITCs (P = .01). The Dutch efforts to increase awareness did not significantly influence either MRI or arthroscopy use in ITCs (P = .55 and P = .84) and GHs (P = .13 and P = .70). MRI and arthroscopy uses were higher in ITCs than GHs. MRI use did not change significantly among patients ≥ 50 years with degenerative knee disease in both provider types between 2014 and 2019. MRI- and arthroscopy use decreased with ITCs on average having higher rates for both modalities, but also showing a stronger decrease in arthroscopy use. The Dutch efforts to increase awareness did not accelerate the already declining trend in the Netherlands., (© The Author(s) 2024. Published by Oxford University Press on behalf of International Society for Quality in Health Care.)

Background: Life course epidemiology examines associations between repeated measures of risk and health outcomes across different phases of life. Empirical research, however, is often based on discrete-time models that assume that sporadic measurement occasions fully capture underlying long-term continuous processes of risk., Methods: We propose (i) the functional relevant life course model (fRLM), which treats repeated, discrete measures of risk as unobserved continuous processes, and (ii) a testing procedure to assign probabilities that the data correspond to conceptual models of life course epidemiology (critical period, sensitive period and accumulation models). The performance of the fRLM is evaluated with simulations, and the approach is illustrated with empirical applications relating body mass index (BMI) to mRNA-seq signatures of chronic kidney disease, inflammation and breast cancer., Results: Simulations reveal that fRLM identifies the correct life course model with three to five repeated assessments of risk and 400 subjects. The empirical examples reveal that chronic kidney disease reflects a critical period process and inflammation and breast cancer likely reflect sensitive period mechanisms., Conclusions: The proposed fRLM treats repeated measures of risk as continuous processes and, under realistic data scenarios, the method provides accurate probabilities that the data correspond to commonly studied models of life course epidemiology. fRLM is implemented with publicly-available software., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Objectives: To inform an international task force about current evidence on Treat to Target (T2T) strategies in PMR and GCA., Methods: A systematic literature research (SLR) was conducted in Medline, EMBASE, Cochrane Library, clinicaltrials.gov from their inception date to May 2022, and in the EULAR/ACR abstract database (2019-2021). Randomised clinical trials (RCTs) and non-randomised interventional studies published in English and answering at least one of the eleven PICO questions on T2T strategies, treatment targets and outcomes, framed by the taskforce, were identified. Study selection process, data extraction and risk of bias assessment were conducted independently by two investigators., Results: Of 7809 screened abstracts, 397 were selected for detailed review and 76 manuscripts were finally included (31 RCTs, eight subgroup/exploratory analyses of RCTs and 37 non-randomised interventional studies). No study comparing a T2T strategy against standard of care was identified. In PMR RCTs, the most frequently applied outcomes concerned treatment (90.9% of RCTs), particularly the cumulative glucocorticoids (GC) dose and GC tapering, followed by clinical, laboratory and safety outcomes (63.3% each). Conversely, the most commonly reported outcomes in RCTs in GCA were prevention of relapses (72.2%), remission as well as treatment-related and safety outcomes (67.0% each)., Conclusions: This SLR provides evidence and highlights the knowledge gaps on T2T strategies in PMR and GCA, informing the task force developing T2T recommendations for these diseases., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

This study provides evidence that the posterior parietal cortex is causally involved in risky decision making via the processing of reward values but not reward probabilities. In the within-group experimental design, participants performed a binary lottery choice task following transcranial magnetic stimulation of the right posterior parietal cortex, left posterior parietal cortex, and a right posterior parietal cortex sham (placebo) stimulation. The continuous theta-burst stimulation protocol supposedly downregulating the cortical excitability was used. Both, mean-variance and the prospect theory approach to risky choice showed that the posterior parietal cortex stimulation shifted participants toward greater risk aversion compared with sham. On the behavioral level, after the posterior parietal cortex stimulation, the likelihood of choosing a safer option became more sensitive to the difference in standard deviations between lotteries, compared with sham, indicating greater risk avoidance within the mean-variance framework. We also estimated the shift in prospect theory parameters of risk preferences after posterior parietal cortex stimulation. The hierarchical Bayesian approach showed moderate evidence for a credible change in risk aversion parameter toward lower marginal reward value (and, hence, lower risk tolerance), while no credible change in probability weighting was observed. In addition, we observed anecdotal evidence for a credible increase in the consistency of responses after the left posterior parietal cortex stimulation compared with sham., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The sense of agency is a fundamental aspect of human self-consciousness, whose neural correlates encompass widespread brain networks. Research has explored the neuromodulatory properties of the sense of agency with noninvasive brain stimulation, which induces exogenous manipulations of brain activity; however, it is unknown whether endogenous modulation of the sense of agency is also achievable. We investigated whether the sense of agency can be self-regulated with electroencephalography-based neurofeedback. We conducted 2 experiments in which healthy humans performed a motor task while their motor control was artificially disrupted, and gave agency statements on their perceived control. We first identified the electrophysiological response to agency processing, and then applied neurofeedback in a parallel, sham-controlled design, where participants learnt to self-modulate their sense of agency. We found that behavioral measures of agency and performance on the task decreased with the increasing disruption of control. This was negatively correlated with power spectral density in the theta band, and positively correlated in the alpha and beta bands, at central and parietal electrodes. After neurofeedback training of central theta rhythms, participants improved their actual control over the task, and this was associated with a significant decrease in the frequency band trained via neurofeedback. Thus, self-regulation of theta rhythms can improve sensory-guided behavior., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Multimorbidity management poses significant challenges for general practitioners (GPs). The aim of this study is to analyse the role of resilience and social support on the burden experienced by GPs in managing patients with multiple health conditions in Portugal., Methods: Cross-sectional quantitative study conducted among GPs in Portugal using an online questionnaire that included validated measurement tools: Questionnaire of Evaluation of Burden of Management of Multimorbidity in General and Family Medicine (SoGeMM-MGF), European Portuguese Version of the Resilience Scale (ER14), and the Oslo Social Support Scale-3 (OSSS-3) in Portuguese. A multiple linear regression analysis was conducted to examine the factors influencing the burden of managing multimorbidity., Results: Two hundred and thirty-nine GPs were included, with 76.6% being female and a median age of 35 years. Most participants were specialists (66.9%) and had less than a decade of experience managing multimorbidity. Over 70% had not received specific training in multimorbidity. Female GPs and those with a higher proportion of multimorbid patients in the registries experienced higher burden levels. A multivariate regression model with moderation revealed that the effect of resilience on burden varied depending on the level of social support. Higher resilience was associated with higher burden in the "Poor Social Support" category, while it was associated with lower burden in the "Moderate Social Support" and "Strong Social Support" categories, although not statistically significant., Conclusions: The study highlights the importance of GPs' social support and resilience in managing the burden of multimorbidity, with poor social support potentially worsening the effects of high resilience., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Aims: We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS)., Methods and Results: In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE., Conclusion: The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method-based risk prediction tools for outcome prediction after AIS in new data sets., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Self-identified Black women in the United States have higher cervical cancer incidence and mortality than the general population, but these differences have not been clearly attributed across described cancer care inequities., Methods: A previously established microsimulation model of cervical cancer was adapted to reflect demographic, screening, and survival data for Black US women and compared with a model reflecting data for all US women. Each model input with stratified data (all-cause mortality, hysterectomy rates, screening frequency, screening modality, follow-up, and cancer survival) was sequentially replaced with Black-race specific data to arrive at a fully specified model reflecting Black women. At each step, we estimated the relative contribution of inputs to observed disparities., Results: Estimated (hysterectomy-adjusted) cervical cancer incidence was 8.6 per 100 000 in the all-race model vs 10.8 per 100 000 in the Black-race model (relative risk [RR] = 1.24, range = 1.23-1.27). Estimated all-race cervical cancer mortality was 2.9 per 100 000 vs 5.5 per 100 000 in the Black-race model (RR = 1.92, range = 1.85-2.00). We found the largest contributors of incidence disparities were follow-up from positive screening results (47.3% of the total disparity) and screening frequency (32.7%). For mortality disparities, the largest contributor was cancer survival differences (70.1%) followed by screening follow-up (12.7%)., Conclusion: To reduce disparities in cervical cancer incidence and mortality, it is important to understand and address differences in care access and quality across the continuum of care. Focusing on the practices and policies that drive differences in treatment and follow-up from cervical abnormalities may have the highest impact., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence., Methods: Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy., Results: Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness., Conclusion: Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Over the past 2 decades, population simulation modeling has evolved as an effective public health tool for surveillance of cancer trends and estimation of the impact of screening and treatment strategies on incidence and mortality, including documentation of persistent cancer inequities. The goal of this research was to provide a framework to support the next generation of cancer population simulation models to identify leverage points in the cancer control continuum to accelerate achievement of equity in cancer care for minoritized populations. In our framework, systemic racism is conceptualized as the root cause of inequity and an upstream influence acting on subsequent downstream events, which ultimately exert physiological effects on cancer incidence and mortality and competing comorbidities. To date, most simulation models investigating racial inequity have used individual-level race variables. Individual-level race is a proxy for exposure to systemic racism, not a biological construct. However, single-level race variables are suboptimal proxies for the multilevel systems, policies, and practices that perpetuate inequity. We recommend that future models designed to capture relationships between systemic racism and cancer outcomes replace or extend single-level race variables with multilevel measures that capture structural, interpersonal, and internalized racism. Models should investigate actionable levers, such as changes in health care, education, and economic structures and policies to increase equity and reductions in health-care-based interpersonal racism. This integrated approach could support novel research approaches, make explicit the effects of different structures and policies, highlight data gaps in interactions between model components mirroring how factors act in the real world, inform how we collect data to model cancer equity, and generate results that could inform policy., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Causal perturbations suggest that primate dorsal pulvinar plays a crucial role in target selection and saccade planning, though its basic neuronal properties remain unclear. Some functional aspects of dorsal pulvinar and interconnected frontoparietal areas-e.g. ipsilesional choice bias after inactivation-are similar. But it is unknown if dorsal pulvinar shares oculomotor properties of cortical circuitry, in particular delay and choice-related activity. We investigated such properties in macaque dorsal pulvinar during instructed and free-choice memory saccades. Most recorded units showed visual (12%), saccade-related (30%), or both types of responses (22%). Visual responses were primarily contralateral; diverse saccade-related responses were predominantly post-saccadic with a weak contralateral bias. Memory delay and pre-saccadic enhancement was infrequent (11-9%)-instead, activity was often suppressed during saccade planning (25%) and further during execution (15%). Surprisingly, only few units exhibited classical visuomotor patterns combining cue and continuous delay activity or pre-saccadic ramping; moreover, most spatially-selective neurons did not encode the upcoming decision during free-choice delay. Thus, in absence of a visible goal, the dorsal pulvinar has a limited role in prospective saccade planning, with patterns partially complementing its frontoparietal partners. Conversely, prevalent visual and post-saccadic responses imply its participation in integrating spatial goals with processing across saccades., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Background: Due to the convenience of serum creatinine (SCr) monitoring and the relative complexity of urine output (UO) monitoring, most studies have predicted acute kidney injury (AKI) only based on SCr criteria. This study aimed to compare the differences between SCr alone and combined UO criteria in predicting AKI., Methods: We applied machine learning methods to evaluate the performance of 13 prediction models composed of different feature categories on 16 risk assessment tasks (half used only SCr criteria, half used both SCr and UO criteria). The area under receiver operator characteristic curve (AUROC), the area under precision recall curve (AUPRC) and calibration were used to assess the prediction performance., Results: In the first week after ICU admission, the prevalence of any AKI was 29% under SCr criteria alone and increased to 60% when the UO criteria was combined. Adding UO to SCr criteria can significantly identify more AKI patients. The predictive importance of feature types with and without UO was different. Using only laboratory data maintained similar predictive performance to the full feature model under only SCr criteria [e.g. for AKI within the 48-h time window after 1 day of ICU admission, AUROC (95% confidence interval) 0.83 (0.82, 0.84) vs 0.84 (0.83, 0.85)], but it was not sufficient when the UO was added [corresponding AUROC (95% confidence interval) 0.75 (0.74, 0.76) vs 0.84 (0.83, 0.85)]., Conclusions: This study found that SCr and UO measures should not be regarded as equivalent criteria for AKI staging, and emphasizes the importance and necessity of UO criteria in AKI risk assessment., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)