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Background Estimates of the prevalence of antimicrobial resistance (AMR) underpin effective antimicrobial stewardship, infection prevention and control, and optimal deployment of antimicrobial agents. Typically, the prevalence of AMR is determined from real-world antimicrobial susceptibility data that are time delimited, sparse, and often biased, potentially resulting in harmful and wasteful decision-making. Frequentist methods are resource intensive because they rely on large datasets. Objectives To determine whether a Bayesian approach could present a more reliable and more resource-efficient way to estimate population prevalence of AMR than traditional frequentist methods. Methods Retrospectively collected, open-source, real-world pseudonymized healthcare data were used to develop a Bayesian approach for estimating the prevalence of AMR by combination with prior AMR information from a contextualized review of literature. Iterative random sampling and cross-validation were used to assess the predictive accuracy and potential resource efficiency of the Bayesian approach compared with a standard frequentist approach. Results Bayesian estimation of AMR prevalence made fewer extreme estimation errors than a frequentist estimation approach [ n  = 74 (6.4%) versus n  = 136 (11.8%)] and required fewer observed antimicrobial susceptibility results per pathogen on average [mean = 28.8 (SD = 22.1) versus mean = 34.4 (SD = 30.1)] to avoid any extreme estimation errors in 50 iterations of the cross-validation. The Bayesian approach was maximally effective and efficient for drug–pathogen combinations where the actual prevalence of resistance was not close to 0% or 100%. Conclusions Bayesian estimation of the prevalence of AMR could provide a simple, resource-efficient approach to better inform population infection management where uncertainty about AMR prevalence is high. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to assess the utility of the Ages and Stages Questionnaire–3rd Edition (ASQ‐3) and the Vineland Adaptive Behavior Scales–2nd Edition (VABS‐II) as neurodevelopmental screening tools for infants exposed to antiseizure medications in utero, and to examine their suitability for use in large‐population signal generation initiatives. Methods: Participants were women with epilepsy who were recruited from 21 hospitals in England and Northern Ireland during pregnancy between 2014 and 2016. Offspring were assessed at 24 months old using the Bayley Scales of Infant Development–3rd Edition (BSID‐III), the VABS‐II, and the ASQ‐3 (n = 223). The sensitivity and specificity of the ASQ‐3 and VABS‐II to identify developmental delay at 24 months were examined, using the BSID‐III to define cases. Results: The ASQ‐3 identified 65 children (29.1%) as at risk of developmental delay at 24 months using standard referral criteria. Using a categorical approach and standard referral criteria to identify delay in the ASQ‐3 and BSID‐III at 24 months, the ASQ‐3 showed excellent sensitivity (90.9%) and moderate specificity (74.1%). Utilizing different cut‐points resulted in improved properties and may be preferred in certain contexts. The VABS‐II exhibited the strongest psychometric properties when borderline impairment (>1 SD below the mean) was compared to BSID‐III referral data (sensitivity = 100.0%, specificity = 96.6%). Significance: Both the ASQ‐3 and VABS‐II have good psychometric properties in a sample of children exposed to antiseizure medications when the purpose is the identification of at‐risk groups. These findings identify the ASQ‐3 as a measure that could be used effectively as part of a tiered surveillance system for teratogenic exposure by identifying a subset of individuals for more detailed investigations. Although the VABS‐II has excellent psychometric properties, it is more labor‐intensive for both the research team and participants and is available in fewer languages than the ASQ‐3. [ABSTRACT FROM AUTHOR]

Introduction: Various factors including body weight-associated treatment cost may influence the probability of dispensing antibiotics to dogs in first-opinion practice, but their effect on specific drug choice remains unclear. Methods: Multiple membership regression modeling was used to investigate the probability of dispensing 12 different antibiotics to dogs of different weights in the context of various disease presentations, using anonymized data obtained from electronic health records of 18 clinics between 2020 and 2022. Data from 14,259 dogs were analyzed. Results: Treatment choice varied significantly with animal weight. Higher body weight was associated with an increased likelihood of dispensing lower cost antimicrobials such as amoxicillin and trimethoprim sulfonamide, while use of higher cost antimicrobials such as cefovecin was strongly biased to smaller animals. However, these effects were limited when restricted treatment options were available for the target condition. Conclusion: This work demonstrates that anticipated financial costs may result in different treatment choices for canine patients depending on their body weight. Further work is needed to understand the impact of financial pressures on veterinarians' treatment choices, and the implications for the optimization of antimicrobial stewardship in first opinion practice. [ABSTRACT FROM AUTHOR]

Objectives: To understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks, perceived risks and the feasibility of risk mitigations from experimental mass cultural events before coronavirus disease 2019 (COVID-19) restrictions were lifted. Design: Prospective, population-wide observational study. Setting: Four events (two nightclubs, an outdoor music festival and a business conference) open to Liverpool City Region UK residents, requiring a negative lateral flow test (LFT) within the 36 h before the event, but not requiring social distancing or face-coverings. Participants: A total of 12,256 individuals attending one or more events between 28 April and 2 May 2021. Main outcome measures: SARS-CoV-2 infections detected using audience self-swabbed (5–7 days post-event) polymerase chain reaction (PCR) tests, with viral genomic analysis of cases, plus linked National Health Service COVID-19 testing data. Audience experiences were gathered via questionnaires, focus groups and social media. Indoor CO2 concentrations were monitored. Results: A total of 12 PCR-positive cases (likely 4 index, 8 primary or secondary), 10 from the nightclubs. Two further cases had positive LFTs but no PCR. A total of 11,896 (97.1%) participants with scanned tickets were matched to a negative pre-event LFT: 4972 (40.6%) returned a PCR within a week. CO2 concentrations showed areas for improving ventilation at the nightclubs. Population infection rates were low, yet with a concurrent outbreak of >50 linked cases around a local swimming pool without equivalent risk mitigations. Audience anxiety was low and enjoyment high. Conclusions: We observed minor SARS-CoV-2 transmission and low perceived risks around events when prevalence was low and risk mitigations prominent. Partnership between audiences, event organisers and public health services, supported by information systems with real-time linked data, can improve health security for mass cultural events. [ABSTRACT FROM AUTHOR]

Brain metastases represent a growing healthcare challenge with a rising incidence attributed to earlier detection and improved systemic cancer treatments. We conducted a systematic review and meta-analysis to investigate the local recurrence rate following surgical resection of a brain metastasis without adjuvant therapy. The analysis included four studies with a total of 235 cases. It was found that the rate of local recurrence by 12-months was 48.1% (95% CI 41.2–58.9). These findings underscore the high rate of patients who will experience local recurrence within 12-months of surgery, emphasising the need for vigilant surveillance when omitting adjuvant radiotherapy in favour of systemic treatments with potential but unproven CNS penetrance. The analysis highlights unmet needs in this patient population. [ABSTRACT FROM AUTHOR]

Objective: Despite widespread monotherapy use of lamotrigine or levetiracetam during pregnancy, prospectively collected, blinded child development data are still limited. The NaME (Neurodevelopment of Babies Born to Mothers With Epilepsy) Study prospectively recruited a new cohort of women with epilepsy and their offspring for longitudinal follow‐up. Methods: Pregnant women of <21 weeks gestation (n = 401) were recruited from 21 hospitals in the UK. Data collection occurred during pregnancy (recruitment, trimester 3) and at 12 and 24 months of age. The primary outcome was blinded assessment of infant cognitive, language, and motor development on the Bayley Scales of Infant and Toddler Development (3rd edition) at 24 months of age with supplementary parent reporting on the Vinelands Adaptive Behavior Scales (2nd edition). Results: There were 394 live births, with 277 children (70%) completing the Bayley assessment at 24 months. There was no evidence of an association of prenatal exposure to monotherapy lamotrigine (−.74, SE = 2.9, 95% confidence interval [CI] = −6.5 to 5.0, p =.80) or levetiracetam (−1.57, SE = 3.1, 95% CI = −4.6 to 7.7, p =.62) with poorer infant cognition, following adjustment for other maternal and child factors in comparison to nonexposed children. Similar results were observed for language and motor scores. There was no evidence of an association between increasing doses of either lamotrigine or levetiracetam. Nor was there evidence that higher dose folic acid supplementation (≥5 mg/day) or convulsive seizure exposure was associated with child development scores. Continued infant exposure to antiseizure medications through breast milk was not associated with poorer outcomes, but the number of women breastfeeding beyond 3 months was low. Significance: These data are reassuring for infant development following in utero exposure to monotherapy lamotrigine or levetiracetam, but child development is dynamic, and future follow‐up is required to rule out later emerging effects. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to examine the construct validity of the sino-nasal outcome test-22 in the setting of patients with nasal septal deviation undergoing septoplasty. Methods: Retrospective case note audit recording preoperative sino-nasal outcome test-22 scores in consecutive patients undergoing septoplasty. Statistical analysis considered 4 existing factor structures for the sino-nasal outcome test-22 survey, all of which emerged from its use in the context of chronic rhinosinusitis. Structural equation modeling and factor analysis were used to compare these existing models to data from this different context of septal deviation. Results: Between January 2017 and January 2021, 115 patients completed sino-nasal outcome test-22 scores prior to undergoing septoplasty. Using confirmatory factor analysis, none of the existing conceptual frameworks could be shown to fit data from patients with septal deviation. Subsequent exploratory factor analysis showed that multiple items failed to significantly load within a 5-factor model: Nasal obstruction, Dizziness, and Frust rated/rest less/irrit able. Conclusion: Results suggest that sino-nasal outcome test-22 does not demonstrate internal validity when considering symptom burden in patients undergoing septoplasty and suggest caution should be exercised when considering such results as either an indication for surgery or a method of reporting postoperative outcomes. We believe that the utility of sino-nasal outcome test-22, in the setting of nasal septal deviation, would be significantly enhanced with modifications made specific to this context. [ABSTRACT FROM AUTHOR]

Background Twice weekly lateral flow tests (LFTs) for secondary school children was UK Government policy from 8 March 2021. We evaluate use of LFTs (both supervised at test centres, and home test kits) in school-aged children in Cheshire and Merseyside. Methods We report (i) number of LFT positives (ii) proportion of LFT positive with confirmatory reverse transcription polymerase chain reaction (PCR) test within 2 days, and (iii) agreement between LFT-positive and confirmatory PCR, and dependence of (i–iii) on COVID-19 prevalence. Findings 1 248 468 LFTs were taken by 211 255 12–18 years old, and 163 914 by 52 116 5–11 years old between 6 November 2020 and 31 July 2021. Five thousand three hundred and fourteen (2.5%) 12–18 years old and 1996 (3.8%) 5–11 years old returned LFT positives, with 3829 (72.1%) and 1535 (76.9%) confirmatory PCRs, and 3357 (87.7%) and 1383 (90.1%) confirmatory PCR-positives, respectively. Monthly proportions of LFT positive with PCR negative varied between 4.7% and 35.3% in 12–18 years old (corresponding proportion of all tests positive: 9.7% and 0.3%). Deprivation and non-White ethnicity were associated with reduced uptake of confirmatory PCR. Interpretation Substantial inequalities in confirmatory testing need more attention to avoid further disadvantage through education loss. When prevalence is low additional measures, including confirmatory testing, are needed. Local Directors of Public Health taking more control over schools testing may be needed. Funding DHSC, MRC, NIHR, EPSRC. [ABSTRACT FROM AUTHOR]

PURPOSE Since the approval of cyclin-dependent kinase 4/6 inhibitors in 2015, this oral cancer (OC) therapy has been combined with oral endocrine therapy as first-line treatment in metastatic hormone receptor–positive breast cancer, adding unique toxicity and complexity to the successful administration of this oral medication. Implementation of OC is challenging because of delays in treatment and nonadherence and is worse among vulnerable patient populations. Pharmacists may mitigate these barriers with facilitation of prior authorizations, communication with pharmacies, toxicity management, adherence counseling, and optimization of dosing schedules and regimens. MATERIALS AND METHODS We conducted a quality improvement project to decrease the average number of treatment day delays during the first six cycles of OC. Patients were enrolled on the OPTIMAL protocol, a high-touch pharmacy intervention incorporating pharmacists within outpatient oncology clinic visits with the providers. Pharmacists met with patients, identified individual barriers to treatment, and performed counseling including toxicity and adherence assessments. RESULTS A preintervention assessment identified an average treatment day delay of 7.7 (range, 3.2-15.3) days during the first six cycles of OC. During the intervention period, 53 patients were enrolled on the OPTIMAL protocol and experienced an average treatment day delay of 2.1 (0.6-4) days, P, .0001. Delays were characterized as modifiable and unmodifiable. Pharmacists documented 640 interventions, including medication reconciliations and clinical recommendations. Forty-two patients reported treatment-related toxicities, resulting in 33 therapy and 20 dose modifications. CONCLUSION Our initiative to incorporate pharmacists in clinic visits at an outpatient breast cancer clinic was associated with decreased treatment day delays during the first six cycles of treatment. Pharmacists performed a multitude of meaningful interventions to facilitate treatment in a particularly vulnerable population and play a valuable role in comanaging patients. [ABSTRACT FROM AUTHOR]

Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making. [ABSTRACT FROM AUTHOR]

Collecting information on multiple longitudinal outcomes is increasingly common in many clinical settings. In many cases, it is desirable to model these outcomes jointly. However, in large data sets, with many outcomes, computational burden often prevents the simultaneous modeling of multiple outcomes within a single model. We develop a mean field variational Bayes algorithm, to jointly model multiple Gaussian, Poisson, or binary longitudinal markers within a multivariate generalized linear mixed model. Through simulation studies and clinical applications (in the fields of sight threatening diabetic retinopathy and primary biliary cirrhosis), we demonstrate substantial computational savings of our approximate approach when compared to a standard Markov Chain Monte Carlo, while maintaining good levels of accuracy of model parameters. [ABSTRACT FROM AUTHOR]

Background: Our study examines if SARS-CoV-2 infections varied by vaccination status, if an individual had previously tested positive and by neighbourhood socioeconomic deprivation across the Delta and Omicron epidemic waves of SARS-CoV-2.Methods: Population cohort study using electronic health records for 2.7 M residents in Cheshire and Merseyside, England (3rd June 2021 to 1st March 2022). Our outcome variable was registered positive test for SARS-CoV-2. Explanatory variables were vaccination status, previous registered positive test and neighbourhood socioeconomic deprivation. Cox regression models were used to analyse associations.Results: Originally higher SARS-CoV-2 rates in the most socioeconomically deprived neighbourhoods changed to being higher in the least deprived neighbourhoods from the 1st September 2021, and were inconsistent during the Omicron wave. Individuals who were fully vaccinated (two doses) were associated with fewer registered positive tests (e.g., individuals engaged in testing between 1st September and 27th November 2021-Hazards Ratio (HR) = 0.48, 95% Confidence Intervals (CIs) = 0.47-0.50. Individuals with a previous registered positive test were also less likely to have a registered positive test (e.g., individuals engaged in testing between 1st September and 27th November 2021-HR = 0.16, 95% CIs = 0.15-0.18. However, the Omicron period saw smaller effect sizes for both vaccination status and previous registered positive test.Conclusions: Changing patterns of SARS-CoV-2 infections during the Delta and Omicron waves reveals a dynamic pandemic that continues to affect diverse communities in sometimes unexpected ways. [ABSTRACT FROM AUTHOR]

Background and Aims: The aMAP score is a model that predicts risk of hepatocellular carcinoma (HCC) development in patients with chronic hepatitis. Its performance in a 'real world' surveillance setting has not yet been ascertained.Patients and Methods: We had access to a cohort of 3473 individuals enrolled in a rigorously implemented and prospectively accrued surveillance programme (patients undergoing regular ultrasound and biomarker examination between 1998 and 2021). During this period 445 had HCC detected. Of these, 77.8% had early stage disease (within Milan criteria), permitting potentially curative therapy to be implemented in nearly 70% of cases. We applied the recently developed aMAP score to classify patients according to their initial aMAP score in to low, medium and high-risk groups as proposed in the original publication. The performance of the aMAP score was assessed according to the concordance-index and calibration (i.e. agreement between observed and predicted risk). Allowance was made for competing causes of death.Results: The aMAP score achieved an overall C-index of 0.81 (95% CI: 0.79-0.82) consistent with the initial report and was unaffected by allowance for competing causes of death. Sub-group analysis showed that the results did not change significantly according to gender, or aetiology. However, aMAP discrimination was greater for younger individuals (versus older individuals), and also for individuals without cirrhosis. The HCC incidence rate was 0.98, 7.05 and 29.1 events per 1000 person-years in the low-, moderate- and high-risk aMAP groups, respectively.Conclusions: The results from this 'real-world' cohort demonstrate that risk stratification is a realistic prospect and that identification of a subgroup of chronic liver disease patients who have a very low risk of HCC is feasible. [ABSTRACT FROM AUTHOR]

Mixed models are a useful way of analysing longitudinal data. Random effects terms allow modelling of patient specific deviations from the overall trend over time. Correlation between repeated measurements are captured by specifying a joint distribution for all random effects in a model. Typically, this joint distribution is assumed to be a multivariate normal distribution. For Gaussian outcomes misspecification of the random effects distribution usually has little impact. However, when the outcome is discrete (e.g. counts or binary outcomes) generalised linear mixed models (GLMMs) are used to analyse longitudinal trends. Opinion is divided about how robust GLMMs are to misspecification of the random effects. Previous work explored the impact of random effects misspecification on the bias of model parameters in single outcome GLMMs. Accepting that these model parameters may be biased, we investigate whether this affects our ability to classify patients into clinical groups using a longitudinal discriminant analysis. We also consider multiple outcomes, which can significantly increase the dimensions of the random effects distribution when modelled simultaneously. We show that when there is severe departure from normality, more flexible mixture distributions can give better classification accuracy. However, in many cases, wrongly assuming a single multivariate normal distribution has little impact on classification accuracy. [ABSTRACT FROM AUTHOR]

Background: From January to May 2021 the alpha variant (B.1.1.7) of SARS-CoV-2 was the most commonly detected variant in the UK. Following this, the Delta variant (B.1.617.2) then became the predominant variant. The UK COVID-19 vaccination programme started on 8th December 2020. Prior to the Delta variant, most vaccine effectiveness studies focused on the alpha variant. We therefore aimed to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in preventing symptomatic and asymptomatic infection with respect to the Delta variant in a UK setting.Methods: We used anonymised public health record data linked to infection data (PCR) using the Combined Intelligence for Population Health Action resource. We then constructed an SIR epidemic model to explain SARS-CoV-2 infection data across the Cheshire and Merseyside region of the UK. Vaccines were assumed to be effective after 21 days for 1 dose and 14 days for 2 doses.Results: We determined that the effectiveness of the Oxford-AstraZeneca vaccine in reducing susceptibility to infection is 39% (95% credible interval [34, 43]) and 64% (95% credible interval [61, 67]) for a single dose and a double dose respectively. For the Pfizer-BioNTech vaccine, the effectiveness is 20% (95% credible interval [10, 28]) and 84% (95% credible interval [82, 86]) for a single-dose and a double dose respectively.Conclusion: Vaccine effectiveness for reducing susceptibility to SARS-CoV-2 infection shows noticeable improvement after receiving two doses of either vaccine. Findings also suggest that a full course of the Pfizer-BioNTech provides the optimal protection against infection with the Delta variant. This reinforces the need to complete the full course programme to maximise individual protection and reduce transmission. [ABSTRACT FROM AUTHOR]

Objectives Depression and anxiety are associated with more severe disease in cross-sectional studies of axial spondyloarthritis (axSpA). We examined the association between baseline symptoms of depression or anxiety and response to TNF inhibitors (TNFi) in axSpA. Methods Biologic naïve participants from a national axSpA register completed the Hospital Anxiety and Depression Scale (HADS) before initiating TNFi. Symptoms of anxiety and depression were each categorized as moderate–severe (≥11), mild (8–10) and 'none' (≤7), and compared against change in disease indices [BASDAI and AS Disease Activity Score (ASDAS)] over time and time to treatment discontinuation using marginal structural models. Inverse-probability weights balanced baseline age, gender, BMI, deprivation, education and baseline values of respective disease indices. Results Of the 742 participants (67% male, mean age 45 years), 176 (24%) had moderate–severe and 26% mild depression; 295 (40%) had moderate–severe and 23% mild anxiety. Baseline disease activity was higher in higher HADS symptom categories for both depression and anxiety. Participants with moderate–severe depression had significantly poorer response compared with those with 'none' throughout follow-up. At 6 months, the difference was approximately 2.2 BASDAI and 0.8 ASDAS units after balancing their baseline values. Equivalent comparisons for anxiety were 1.7 BASDAI and 0.7 ASDAS units. Treatment discontinuation was 1.59-fold higher (hazard ratio 95% CI: 1.12, 2.26) in participants with moderate–severe anxiety compared with 'none'. Conclusions Symptoms of depression and anxiety at TNFi initiation are associated with poorer treatment outcomes. Targeted interventions to optimize mental health have potential to substantially improve treatment response and persistence. [ABSTRACT FROM AUTHOR]

Objective Comorbidities influence disease assessment in axial spondyloarthritis (axSpA), but their association with response to TNF inhibitors (TNFi) is unclear. We examined associations between comorbidity history at TNFi initiation and: (i) change in disease indices over time; (ii) binary response definitions; and (iii) time to treatment discontinuation. Methods We studied participants starting their first TNFi from a national axSpA register. Comorbidity categories were created from 14 physician-diagnosed conditions and compared against: change in disease indices over time using linear mixed effects models; BASDAI50/2 (50% or 2-unit reduction) and BASDAI < 4 at 6 months using logistic models; and time to treatment discontinuation using Cox models. Models were adjusted for age, gender, BMI, deprivation and education. Results In total, 994 were eligible for analysis (68% male, mean age 45 years); 21% had one comorbidity and 11% had ≥2. Baseline disease severity was higher in those with comorbidities across all indices, but absolute improvement over time was comparable for BASDAI and spinal pain. Participants with ≥2 comorbidities had smaller absolute improvement in BASFI and quality of life. This group also had numerically reduced odds of achieving BASDAI50/2 [odds ratio (OR) 0.81; 95% CI: 0.45, 1.45] and BASDAI < 4 (OR 0.57; 95% CI: 0.32, 1.04). Treatment discontinuation was increased in those with two comorbidities [hazard ratio (HR) 1.32; 95% CI: 0.88, 2.00] and ≥3 comorbidities (HR 2.18; 95% CI: 1.20, 3.93) compared with none. Conclusions Participants with multiple comorbidities had poorer treatment outcomes, particularly increased treatment discontinuation and poorer improvements in function and quality of life. These results inform clinicians and educate patients about response to the first TNFi given comorbidity burden. [ABSTRACT FROM AUTHOR]

Objective Whether comorbidities influence disease activity assessment in axial SpA (axSpA) is unclear. Comorbidities inflate DAS28 in rheumatoid arthritis through the patient global score. We examined whether axSpA disease activity measures are differentially affected, and whether comorbidities inflate the AS disease activity score (ASDAS) through the patient global component. Methods We used baseline data from the British Society for Rheumatology Biologics Register for AS, including 14 physician diagnosed comorbidities. Linear models were used to compare disease activity (BASDAI, spinal pain, ASDAS) and ESR/CRP according to comorbidity count, adjusted for age, gender, BMI, smoking, socioeconomic status, and education. The same models were used to examine whether the patient global score was associated with comorbidities, additionally adjusting for other ASDAS components. Results The number of participants eligible for analysis was 2043 (67% male, mean age 49 years); 44% had at least one comorbidity. Each additional comorbidity was associated with higher BASDAI by 0.40 units (95% CI: 0.27, 0.52) and spinal pain by 0.53 (95% CI: 0.37, 0.68). Effect size for ASDAS (0.09 units; 95% CI: 0.03, 0.15) was not clinically significant. ESR and CRP were not associated with comorbidity count. Depression, heart failure and peptic ulcer were consistently associated with higher disease activity measures, but not CRP/ESR. Patient global was associated with comorbidity count, but not independently of other ASDAS components (P  = 0.75). Conclusion Comorbidities were associated with higher patient reported disease activity in axSpA. Clinicians should be mindful of the potential impact of comorbidities on patient reported outcome measures and consider additionally collecting ASDAS when comorbidities are present. [ABSTRACT FROM AUTHOR]

The aims of this systematic review and meta-analysis were to describe prevalence of cardiovascular disease in gout, compare these results with non-gout controls and consider whether there were differences according to geography. PubMed, Scopus and Web of Science were systematically searched for studies reporting prevalence of any cardiovascular disease in a gout population. Studies with non-representative sampling, where a cohort had been used in another study, small sample size (< 100) and where gout could not be distinguished from other rheumatic conditions were excluded, as were reviews, editorials and comments. Where possible meta-analysis was performed using random-effect models. Twenty-six studies comprising 949,773 gout patients were included in the review. Pooled prevalence estimates were calculated for five cardiovascular diseases: myocardial infarction (2.8%; 95% confidence interval (CI)s 1.6, 5.0), heart failure (8.7%; 95% CI 2.9, 23.8), venous thromboembolism (2.1%; 95% CI 1.2, 3.4), cerebrovascular accident (4.3%; 95% CI 1.8, 9.7) and hypertension (63.9%; 95% CI 24.5, 90.6). Sixteen studies reported comparisons with non-gout controls, illustrating an increased risk in the gout group across all cardiovascular diseases. There were no identifiable reliable patterns when analysing the results by country. Cardiovascular diseases are more prevalent in patients with gout and should prompt vigilance from clinicians to the need to assess and stratify cardiovascular risk. Future research is needed to investigate the link between gout, hyperuricaemia and increased cardiovascular risk and also to establish a more thorough picture of prevalence for less common cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Background Delay to diagnosis in axial SpA (axSpA) is longer than in many other rheumatic diseases. Prolonged delay is associate with poorer outcomes, including functional impairment and quality of life. Our aims were to describe global variation in delay to diagnosis, factors associated with delay, and delay compared with PsA. Methods We searched MEDLINE, PubMed, Embase and Web of Science using a predefined protocol. Diagnostic delay was defined as years between the age at symptom onset and at diagnosis. We pooled the mean delay using random effects inverse variance meta-analysis. We examined variations in pooled estimates using prespecified subgroup analyses and sources of heterogeneity using meta-regression. Results A total of 64 studies reported the mean diagnostic delay in axSpA patients. The pooled mean delay was 6.7 years (95% CI 6.2, 7.2) with high levels of heterogeneity. Delay to diagnosis did not improve over time when stratifying results by year of publication. Studies from high-income countries (defined by the World Bank) reported longer delays than those from middle-income countries. Factors consistently reported to be associated with longer delays were lower education levels, younger age at symptom onset and absence of extra-articular manifestations (EAMs). The pooled estimate for diagnostic delay from 8 PsA studies was significantly shorter, at 2.6 years (95% CI 1.6, 3.6). Conclusion For axSpA patients, delay to diagnosis remains unacceptably prolonged in many parts of the world. Patient factors (e.g. education) and disease presentation (onset age and EAMs) should inform campaigns to improve delay. [ABSTRACT FROM AUTHOR]

The aims of this systematic review and meta-analysis were to: (1) describe the prevalence of commonly reported comorbidities in psoriatic arthritis (PsA), (2) compare the incidence and/or prevalence of comorbidities between PsA and control populations; and (3) examine the impact of comorbidities on PsA outcomes. We systematically searched Medline, PubMed, Scopus, and Web of Science using a predefined protocol in accordance with PRISMA guidelines. Studies reporting only one comorbidity, or a few closely related diseases within one organ system, were excluded. Where possible, meta-analysis was performed using random-effects models. We included 39 studies amounting to over 152 thousand PsA patients. We performed meta-analysis for the prevalence of 21 commonly reported comorbidities. The most prevalent comorbidities were hypertension (pooled prevalence 34%), metabolic syndrome (29%), obesity (27%), hyperlipidaemia (24%) and any cardiovascular diseases (19%). Eleven studies consistently showed higher prevalence of comorbidities in PsA than controls. Five studies showed that comorbid patients had more severe disease, poorer quality of life, and increased discontinuation of treatment. Comorbidities, particularly cardiometabolic disorders, were highly prevalent in PsA and more common than in healthy controls. Comorbidities were associated with adverse disease features, but more research is needed on their impact on longitudinal outcomes such as treatment response, work productivity and mortality. [ABSTRACT FROM AUTHOR]

Objective: Systemic light-chain (AL) amyloidosis is an uncommon hematologic plasma cell dyscrasia that is becoming increasingly recognized. Therapeutic agents used in AL amyloidosis overlap with those used in multiple myeloma; however, differences in disease features change treatment efficacy and tolerance. Pharmacists must be cognizant of these distinctions. Herein, this review article provides an up-to-date guide to treatment considerations for systemic AL amyloidosis in both the front-line and relapsed settings. Data sources: A comprehensive literature search was performed using the PubMed/Medline database for articles published through (June 2020) regarding treatments for AL amyloidosis. Search criteria included therapies that are FDA approved for multiple myeloma, as well as investigational agents. This review of chemotherapeutic agents reflects the current clinical practice guidelines endorsed by NCCN along with commentary based on the experience of pharmacists from a tertiary-referral center treating many patients with AL amyloidosis. Data consists of randomized controlled trials, observational cohorts, case reports, and ongoing clinical trials. Data summary: Frontline options discussed here include high-dose melphalan with autologous stem cell transplantation and bortezomib-based regimens. Regarding the relapsed setting, supporting data are compiled and summarized for: bortezomib, ixazomib, carfilzomib, lenalidomide, pomalidomide, daratumumab, elotuzumab, isatuximab, venetoclax, NEOD001, and melflufen. Conclusions: The treatment platform for AL amyloidosis is expanding with novel agents traditionally used in multiple myeloma being adopted and modified for use in AL amyloidosis. The pharmacist's familiarity with the clinical evidence base for these agents and how they fit into standard protocols for AL amyloidosis is critical as dosing and monitoring recommendations are unique from multiple myeloma. [ABSTRACT FROM AUTHOR]

Objective To describe the prevalence of extra-articular manifestations—enthesitis, dactylitis, nail disease, uveitis and IBD—in PsA, and their impact on longitudinal disease outcomes. Methods We searched Medline, PubMed, Scopus and Web of Science using a predefined protocol in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies using imaging to define extra-articular manifestations (EAMs) were excluded. Where possible, we performed meta-analyses of prevalence estimates, reported as percentages (95% CI). Heterogeneity (I2 statistic) was examined according to study characteristics. Results We identified 65 studies amounting to a total of 163 299 PsA patients. Enthesitis was assessed in 29 studies with an average prevalence of 30% (95% CI: 24%, 38%). Dactylitis was reported in 35 studies with an average prevalence of 25% (95% CI: 20%, 31%). Nail disease was present in 60% (95% CI: 52%, 68%) across 26 studies, but definitions were often unclear. Uveitis (3.2%; 95% CI: 1.9%, 5.3%) and IBD (3.3%; 95% CI: 1.5%, 7.1%) were less common. Heterogeneity was high (>95%) in all meta-analyses, but could not be explained by study characteristics. No studies examined the impact of EAMs on longitudinal disease outcomes, except that dactylitis increases radiographic progression. Conclusion Enthesitis, dactylitis and nail disease are highly prevalent in PsA, but not uveitis and IBD. EAM patterns differ from axial SpA despite their shared disease mechanisms, which may help further understand differences between spondyloarthritides. More studies are needed on the impact of EAMs on disease outcomes such as response to treatment. [ABSTRACT FROM AUTHOR]

Objective: To describe the prevalence of depression among patients with primary systemic vasculitides (PSV); compare prevalence according to vasculitis type and against controls; and examine the impact of depression on PSV outcomes. Methods: We searched Medline, PubMed, Scopus and Web of Science using a predefined protocol in accordance with PRISMA guidelines. We included all studies that reported the prevalence or impact of depression in PSV. We also included polymyalgia rheumatica (PMR) given its association with giant cell arteritis (GCA). Meta-analyses of prevalence estimates were performed using random-effects models and reported as percentages (95% confidence interval). Results: We reviewed a total of 15 studies that described the prevalence of depression, categorised into small (n = 10) and large vessel vasculitis (n = 7). Pooled prevalence estimate for depression in a small vessel (predominantly ANCA-associated) vasculitis was 28% (95% CI 20–38%) with significant heterogeneity (I2 = 93%). Depression prevalence in large-vessel vasculitis (Takayasu and GCA/PMR) was 24% (95% CI 17–34%), again with significant heterogeneity (I2 = 96%). One study reported 56% prevalence of depression in medium vessel disease. The prevalence of depression in small vessel vasculitis was higher than healthy controls. In these patients, depression and depressive symptoms were associated with poorer quality of life, adherence, and work disability, but not disease activity or damage. Conclusion: Depression is highly prevalent among patients with primary systemic vasculitis and associated with poorer outcomes across a range of measures in studies of small vessel disease. Further studies are needed for depression in medium and large vessel vasculitides. [ABSTRACT FROM AUTHOR]

BACKGROUND: Chemotherapy-induced nausea and vomiting (CINV) is among the most feared complications of chemotherapy by patients. Deviation from clinical practice guidelines may impair the optimal management of CINV. Furthermore, any operational challenges within a healthcare system may pose a barrier to the management of CINV and may place a large time commitment burden on providers. OBJECTIVE: To minimize the incidence of CINV in patients receiving highly emetogenic chemotherapy (HEC) by achieving 90% complete response to antiemetic regimens over 6 months in an outpatient oncology clinic using a pharmacist-run protocol. protocol between November 1, 2017, and April 30, 2018. Pharmacists completed all prior authorizations, prescribed and delivered medications, and provided face-to-face patient counseling. The proportion of complete responses to antiemetic drugs--defined as the absence of any CINV symptom at days 3 and 5 of the chemotherapy cycle--the percentage of patients managed via pharmacist protocol, the rates of patient enrollment submitted by providers, and the time pharmacists spent with patients, were collected as the study metrics. The providers were surveyed before and after the study to evaluate their perceived impact of the pharmacist-run protocol on patient outcomes and provider time. The protocol included 3 plan-do-study-act cycles: first cycle (weeks 1-6), second cycle (weeks 7-12), and third cycle (weeks 8-24). RESULTS: A total of 46 patients and 163 chemotherapy cycles were managed under the pharmacist- run protocol during the 6-month study period. The complete response rates to antiemetic regimens steadily increased over the study period from 65% at baseline to >90% by the end of the study, through utilization of the pharmacist-managed protocol. A mean time of 45.7 minutes per patient was spent by the pharmacists to maintain this protocol for new patients, which was consistent with the time-savings estimated by providers in pre-intervention surveys. CONCLUSION: The implementation of a pharmacist-run protocol led to high rates of complete response to antiemetic drugs (as measured by the absence of CINV) and significant time-savings for providers in an outpatient oncology clinic. This study supports the integration of pharmacy-driven services into healthcare systems to optimize and streamline providers' time in the clinic, by using pharmacists as extenders to prescribe and manage antiemetic drugs. [ABSTRACT FROM AUTHOR]

Objective: Observational data facilitate examination of treatment-effect heterogeneity, but the risk of bias is substantial. The present study was undertaken to highlight methodologic considerations through an analysis of whether smoking affects response to tumor necrosis factor inhibitors (TNFi) in axial spondyloarthritis (SpA).Methods: We used longitudinal data from the British Society for Rheumatology Biologics Register for Ankylosing Spondylitis. Participants fulfilling the Assessment of SpondyloArthritis international Society criteria for axial SpA who started their first TNFi were eligible for analysis. In comparing the impact of smoking status, weighted generalized estimating equations were used to examine changes in several continuous outcome measures, including the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and the Ankylosing Spondylitis Disease Activity Score (ASDAS). Inverse probability weights were used to account for differences in baseline covariates and excluded participants. We separately assessed response in the first 3 months to account for nonrandom dropout.Results: For 840 participants who started on TNFi, 1,641 assessments from 627 individuals were analyzed (69% male, mean age 46 years). A total of 33% were current smokers and 30% ex-smokers. Ex-smokers and current smokers had worse disease than never smokers at baseline. Accounting for these differences, response did not differ according to smoking status. Compared to never smokers, ex-smokers (β = -0.6, 95% confidence interval [95% CI] -1.4, 0.3) and current smokers (β = -0.4, 95% CI -1.1, 0.4) had a similar response according to the BASDAI and ASDAS (ex-smokers β = -0.1, 95% CI -0.5, 0.3; current smokers β = -0.01, 95% CI -0.4, 0.4) at 3 months.Conclusion: TNFi response did not differ according to baseline smoking status in this UK cohort. Conflicting results from previous studies were likely due to methodologic differences. This analysis highlights potential sources of bias that should be addressed in future studies. [ABSTRACT FROM AUTHOR]

Objectives: To compare a Bayesian clinical decision support (CDS) dose-optimizing software program with clinician judgement in individualizing vancomycin dosing regimens to achieve vancomycin pharmacokinetic (PK)/pharmacodynamic (PD) targets in a paediatric population.Methods: A retrospective review combined with a model-based simulation of vancomycin dosing was performed on children aged 1 year to 18 years at the University of California, San Francisco Benioff Children's Hospital Mission Bay. Dosing regimens recommended by the clinical pharmacists, 'clinician-guided', were compared with alternative 'CDS-guided' dosing regimens. The primary outcome was the percentage of occasions predicted to achieve steady-state trough levels within the target range of 10-15 mg/L, with a secondary outcome of predicted attainment of AUC24 ≥400 mg·h/L. Statistical comparison between approaches was performed using a standard t-test.Results: A total of n=144 patient occasions were included. CDS-guided regimens were predicted to achieve vancomycin steady-state troughs in the target range on 70.8% (102/144) of occasions, as compared with 37.5% (54/144) in the clinician-guided arm (P<0.0001). An AUC24 of ≥400 mg·h/L was achieved on 93% (112/121) of occasions in the CDS-guided arm versus 72% (87/121) of occasions in the clinician-guided arm (P<0.0001).Conclusions: In a simulated analysis, the use of a Bayesian CDS tool was better than clinician judgement in recommending vancomycin dosing regimens in which PK/PD targets would be attained in children. [ABSTRACT FROM AUTHOR]

Objectives To examine how comorbidities cluster in axial spondyloarthritis (axSpA) and whether these clusters are associated with quality of life, global health and other outcome measures. Methods We conducted a cross-sectional study of consecutive patients meeting ASAS criteria for axSpA in Liverpool, UK. Outcome measures included quality of life (EQ5D), global health and disease activity (BASDAI). We used hierarchical cluster analysis to group patients according to 38 pre-specified comorbidities. In multivariable linear models, the associations between distinct comorbidity clusters and each outcome measure were compared, using axSpA patients with no comorbidities as the reference group. Analyses were adjusted for age, gender, symptom duration, BMI, deprivation, NSAID-use and smoking. Results We studied 419 patients (69% male, mean age 46 years). 255 patients (61%) had at least one comorbidity, among whom the median number was 1 (range 1–6). Common comorbidities were hypertension (19%) and depression (16%). Of 15 clusters identified, the most prevalent clusters were hypertension-coronary heart disease and depression-anxiety. Compared with patients with no comorbidities, the fibromyalgia-irritable bowel syndrome cluster was associated with adverse patient-reported outcome measures; these patients reported 1.5-unit poorer global health (95%CI 0.01, 2.9), reduced quality of life (0.25-unit lower EQ5D; 95%CI −0.37, −0.12) and 1.8-unit higher BASDAI (95% CI 0.4, 3.3). Similar effect estimates were found for patients in the depression-anxiety cluster. Conclusion Comorbidity is common among axSpA patients. The two most common comorbidities were hypertension and depression. Patients in the depression-anxiety and fibromyalgia-IBS clusters reported poorer health and increased axSpA severity. [ABSTRACT FROM AUTHOR]

Objective The effects of smoking on disease manifestations in axial SpA are inadequately described. Utilizing a large and well-characterized cohort, we investigated the association between smoking and extra-axial manifestations, and smoking and disease severity measures. Methods Baseline data from the British Society for Rheumatology Biologics Register for Ankylosing Spondylitis were explored. Our analyses focused on extra-axial manifestations and other disease severity measures, including scales for fatigue, sleep, anxiety and depression. Logistic and linear models were used to quantify associations between disease characteristics according to smoking status (current/ex/never) and quantity (heavy/light), adjusting for age, gender, BMI, education, deprivation, comorbidities, symptom duration and alcohol status. Results A total of 2031 participants were eligible for the current analysis (68% male, mean age 49 years). Of these, 24% were current and 32% ex-smokers. When compared with non-smokers, current smokers had lower odds of uveitis [OR 0.7, 95% CI 0.5–0.9] and higher odds of psoriasis (ORadj 1.6, 95% CI 1.1–2.3). Ex- and current smokers had incrementally more severe disease than never smokers, with higher BASDAI (β = 0.3, 95% CI 0.1–0.6; β = 0.9, 95% CI 0.6–1.2) and BASFI (β = 0.5, 95% CI 0.2–0.8; β = 1.3, 95% CI 1.0–1.6); similar associations were observed for fatigue, sleep, anxiety and depression. Conclusion In this large cross-sectional study, we observed that smoking is independently associated with an adverse disease profile in axial SpA, including worse fatigue, sleep, anxiety and depression, and higher odds of psoriasis. The paradoxical association between current smoking and reduced odds of uveitis is interesting and warrants further investigation. [ABSTRACT FROM AUTHOR]

Summary: Objective: We aim to identify people with epilepsy who are unlikely to reachieve a 12‐month remission within 2 years after experiencing a breakthrough seizure following an initial 12‐month remission. Methods: We apply a novel longitudinal discriminant approach to data from the Standard and New Antiepileptic Drugs study to dynamically predict the risk of a patient not achieving a second remission after a breakthrough seizure by combining both baseline covariates (collected at the time of breakthrough seizure) and follow‐up data. Results: The model classifies 83% of patients. Of these, 73% of patients (95% confidence interval [CI] = 58%‐88%) who did not achieve a second remission were correctly identified (sensitivity), and 84% of patients (95% CI = 69%‐96%) who achieved a second remission were correctly identified (specificity). The area under the curve from our model was 87% (95% CI = 80%‐94%). Patients who did not achieve a second remission were correctly identified on average after 10 months of observation postbreakthrough. Occurrence of seizures after breakthrough and the number of seizures experienced were the most informative longitudinal variables. These longitudinal profiles were influenced by the following baseline covariates: age at breakthrough seizure, presence of neurological insult, and number of antiepileptic drugs required to achieve first remission. Significance: Using longitudinal data gathered during patient follow‐up allows more accurate predictions than using baseline covariates in a standard Cox model. The model developed in this paper is a useful first step in developing a tool for identifying patients who develop drug resistance after an initial remission. [ABSTRACT FROM AUTHOR]

Aims: To evaluate our proposed multivariate approach to identify patients who will develop sight‐threatening diabetic retinopathy (STDR) within a 1‐year screen interval, and explore the impact of simple stratification rules on prediction. Materials and methods: A 7‐year dataset (2009‐2016) from people with diabetes (PWD) was analysed using a novel multivariate longitudinal discriminant approach. Level of diabetic retinopathy, assessed from routine digital screening photographs of both eyes, was jointly modelled using clinical data collected over time. Simple stratification rules based on retinopathy level were also applied and compared with the multivariate discriminant approach. Results: Data from 13 103 PWD (49 520 screening episodes) were analysed. The multivariate approach accurately predicted whether patients developed STDR or not within 1 year from the time of prediction in 84.0% of patients (95% confidence interval [CI] 80.4‐89.7), compared with 56.7% (95% CI 55.5‐58.0) and 79.7% (95% CI 78.8‐80.6) achieved by the two stratification rules. While the stratification rules detected up to 95.2% (95% CI 92.2‐97.6) of the STDR cases (sensitivity) only 55.6% (95% CI 54.5‐56.7) of patients who did not develop STDR were correctly identified (specificity), compared with 85.4% (95% CI 80.4‐89.7%) and 84.0% (95% CI 80.7‐87.6%), respectively, achieved by the multivariate risk model. Conclusions: Accurate prediction of progression to STDR in PWD can be achieved using a multivariate risk model whilst also maintaining desirable specificity. While simple stratification rules can achieve good levels of sensitivity, the present study indicates that their lower specificity (high false‐positive rate) would therefore necessitate a greater frequency of eye examinations. [ABSTRACT FROM AUTHOR]

The authors convey their response to a feedback about their report on the prevalence of extra-articular manifestations in psoriatic arthritis (PsA). Topics mentioned include axial involvement in PsA studies, positive association between the proportion of males and prevalence of axial involvement according to meta-regression, and the heterogeneity in definition of axial involvement reflected in the heterogeneity of meta-analysis estimates.

There is an emerging need in clinical research to accurately predict patients' disease status and disease progression by optimally integrating multivariate clinical information. Clinical data are often collected over time for multiple biomarkers of different types (e.g. continuous, binary and counts). In this paper, we present a flexible and dynamic (time-dependent) discriminant analysis approach in which multiple biomarkers of various types are jointly modelled for classification purposes by the multivariate generalized linear mixed model. We propose a mixture of normal distributions for the random effects to allow additional flexibility when modelling the complex correlation between longitudinal biomarkers and to robustify the model and the classification procedure against misspecification of the random effects distribution. These longitudinal models are subsequently used in a multivariate time-dependent discriminant scheme to predict, at any time point, the probability of belonging to a particular risk group. The methodology is illustrated using clinical data from patients with epilepsy, where the aim is to identify patients who will not achieve remission of seizures within a five-year follow-up period. [ABSTRACT FROM AUTHOR]

Abstract: Longitudinal discriminant analysis (LoDA) can be used to classify patients into prognostic groups based on their clinical history, which often involves longitudinal measurements of various clinically relevant markers. Patients' longitudinal data is first modelled using multivariate generalised linear mixed models, allowing markers of different types (e.g. continuous, binary, counts) to be modelled simultaneously. We describe three approaches to calculating a patient's posterior group membership probabilities which have been outlined in previous studies, based on the marginal distribution of the longitudinal markers, conditional distribution and distribution of the random effects. Here we compare the three approaches, first using data from the Mayo Primary Biliary Cirrhosis study and then by way of simulation study to explore in which situations each of the three approaches is expected to give the best prediction. We demonstrate situations in which the marginal or random‐effects approach perform well, but find that the conditional approach offers little extra information to the random‐effects and marginal approaches. [ABSTRACT FROM AUTHOR]

Recently developed methods of longitudinal discriminant analysis allow for classification of subjects into prespecified prognostic groups using longitudinal history of both continuous and discrete biomarkers. The classification uses Bayesian estimates of the group membership probabilities for each prognostic group. These estimates are derived from a multivariate generalised linear mixed model of the biomarker's longitudinal evolution in each of the groups and can be updated each time new data is available for a patient, providing a dynamic (over time) allocation scheme. However, the precision of the estimated group probabilities differs for each patient and also over time. This precision can be assessed by looking at credible intervals for the group membership probabilities. In this paper, we propose a new allocation rule that incorporates credible intervals for use in context of a dynamic longitudinal discriminant analysis and show that this can decrease the number of false positives in a prognostic test, improving the positive predictive value. We also establish that by leaving some patients unclassified for a certain period, the classification accuracy of those patients who are classified can be improved, giving increased confidence to clinicians in their decision making. Finally, we show that determining a stopping rule dynamically can be more accurate than specifying a set time point at which to decide on a patient's status. We illustrate our methodology using data from patients with epilepsy and show how patients who fail to achieve adequate seizure control are more accurately identified using credible intervals compared to existing methods. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) are an effective therapy for various cancers; however, they can induce immune-related adverse events (irAEs) as a side effect. Myocarditis is an uncommon, but fatal, irAE caused after ICI treatments. Currently, the mechanism of ICI-associated myocarditis is unclear. Here, we show the development of myocarditis in A/J mice induced by anti-PD-1 monoclonal antibody (mAb) administration alone without tumor cell inoculation, immunization, or viral infection. Mice with myocarditis have increased cardiac infiltration, elevated cardiac troponin levels, and arrhythmia. Anti-PD-1 mAb treatment also causes irAEs in other organs. Autoimmune T cells recognizing cardiac myosin are activated and increased in mice with myocarditis. Notably, cardiac myosin-specific T cells are present in naive mice, showing a phenotype of antigen-experienced T cells. Collectively, we establish a clinically relevant mouse model for ICI-associated myocarditis and find a contribution of cardiac myosin-specific T cells to ICI-associated myocarditis development and pathogenesis. [Display omitted] • PD-1 inhibitor treatment alone causes myocarditis development in A/J mice • Cardiac-myosin-specific T cells drive PD-1 inhibitor-induced myocarditis in mice • Cardiac-myosin-specific autoimmune T cells are present in naive mouse hearts • Cardiac-myosin-specific autoimmune T cells express PD-1 during naive conditions Won et al. demonstrate that PD-1 inhibitor treatment alone induces myocarditis in A/J mice, creating a mouse model for immune-checkpoint-inhibitor-associated myocarditis. Cardiac myosin-specific autoreactive T cells drive the pathogenesis of PD-1 inhibitor-induced myocarditis in mice. PD-1-expressing cardiac myosin-specific T cells are present in the heart during naive conditions. [ABSTRACT FROM AUTHOR]

The article presents the observational studies have shown obesity (defined using body mass index [BMI]) to be associated with rheumatoid arthritis (RA) risk, but its causal role remains unclear. Topics include the dramatic weight loss following bariatric surgery did not reduce RA risk among participants in the Swedish Obese Subjects study, and the obesity is also paradoxically associated with reduced mortality among RA patients.

An extensive literature shows that greater left, relative to right, frontal cortical activity (LFA) is involved in approach-motivated affective states and reflects stable individual differences in approach motivation. However, relatively few studies have linked LFA to behavioral indices of approach motivation. In this study, we examine the relation between LFA and effort expenditure for reward, a behavioral index of approach motivation. LFA was calculated for 51 right-handed participants (55% female) using power spectral analysis of electroencephalogram recorded at rest. Participants also completed the effort expenditure for rewards task (EEfRT), which presents a series of trials requiring a choice between a low-reward low-effort task and a high-reward high-effort task. We found that individuals with greater resting LFA were more willing to expend greater effort in the pursuit of larger rewards, particularly when reward delivery was less likely. Our findings offer a more nuanced understanding of the motivational significance of LFA, in terms of processes that mitigate the effort- and uncertainty-related costs of pursuing rewarding goals. [ABSTRACT FROM AUTHOR]

Background Blockade of the suprascapular nerve (SSN) is used frequently in shoulder surgery and in chronic shoulder pain. Anatomical landmarks may be used to locate the nerve before infiltration with local anaesthetic, with ultrasound comprising a popular method for locating the nerve. Methods Twelve cadaveric shoulders from six specimens were injected with dye using both the landmark and the ultrasound technique. The shoulders were scanned by computed tomography (CT) and then dissected to determine the accuracy of each technique. Results Using the CT scan results, we found the ultrasound group to be more accurate with respect to placing the anaesthetic needle close to the suprascapular notch (and therefore nerve), with this being statistically significant ( p = 0.021). Conclusions The findings of the present study demonstrate that ultrasound-guided block is significantly more accurate than the landmark technique, therefore suggesting that ultrasound guidance be used for blockade of the SSN. [ABSTRACT FROM AUTHOR]

Stackless traversal techniques are often used to circumvent memory bottlenecks by avoiding a stack and replacing return traversal with extra computation. This paper addresses whether the stackless traversal approaches are useful on newer hardware and technology (such as CUDA). To this end, we present a novel stackless approach for implicit kd-trees, which exploits the benefits of index-based node traversal, without incurring extra node visitation. This approach, which we term Kd-Jump, enables the traversal to immediately return to the next valid node, like a stack, without incurring extra node visitation (kd-restart). Also, Kd-Jump does not require global memory (stack) at all and only requires a small matrix in fast constant-memory. We report that Kd-Jump outperforms a stack by 10 to 20% and kd-restart by 100%. We also present a Hybrid Kd-Jump, which utilizes a volume stepper for leaf testing and a run-time depth threshold to define where kd-tree traversal stops and volume-stepping occurs. By using both methods, we gain the benefits of empty space removal, fast texture-caching and realtime ability to determine the best threshold' for current isosurface and view direction. [ABSTRACT FROM AUTHOR]

The fecal metabolome in early life has seldom been studied. We investigated its evolution in pre-term babies during their first weeks of life. Multiple (n = 152) stool samples were studied from 51 babies, all <32 weeks gestation. Volatile organic compounds (VOCs) were analyzed by headspace solid phase microextraction gas chromatography mass spectrometry. Data were interpreted using Automated Mass Spectral Deconvolution System (AMDIS) with the National Institute of Standards and Technology (NIST) reference library. Statistical analysis was based on linear mixed modelling, the number of VOCs increased over time; a rise was mainly observed between day 5 and day 10. The shift at day 5 was associated with products of branched-chain fatty acids. Prior to this, the metabolome was dominated by aldehydes and acetic acid. Caesarean delivery showed a modest association with molecules of fungal origin. This study shows how the metabolome changes in early life in pre-term babies. The shift in the metabolome 5 days after delivery coincides with the establishment of enteral feeding and the transition from meconium to feces. Great diversity of metabolites was associated with being fed greater volumes of milk. [ABSTRACT FROM AUTHOR]