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Gastro-esophageal reflux disease (GORD) has been associated with a greater risk of idiopathic pulmonary fibrosis (IPF) in observational studies, but results are limited by confounding. We used multivariable Mendelian randomization to examine their causal relationship, adjusting for BMI.

Interleukin-5 (IL-5) inhibitors have revolutionized the management of eosinophilic asthma. However, IL-5 is thought to play a protective role in atherosclerosis, and cardiovascular safety data for IL-5i are scarce. We used population-level data to examine the association between genetically proxied IL-5i and the risk of cardiovascular diseases. Genetic instruments for IL-5i were selected from a genome-wide association study of eosinophil count in 563,946 individuals. Genetic association data for coronary artery disease were obtained from 60,801 cases, 40,585 stroke cases, 7988 venous thromboembolism cases, and up to 406,111 controls. We used the inverse-variance weighted method and a series of sensitivity analyses. Nine genetic variants were selected to instrument IL-5i. Genetically proxied IL-5i was not associated with the risk of coronary heart disease (OR 0.82, 95%CI 0.65–1.03), stroke (OR 1.10; 0.95–1.27), or venous thromboembolism (OR 0.87; 0.64–1.17). We found no genetic evidence to suggest that IL-5i affects the risk of adverse cardiovascular and thromboembolic events.

Mortality rates in hospitalised patients with COVID-19 in the UK appeared to decline during the first wave of the pandemic. We aimed to quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital.

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.

Utilities replace water mains by responding to failures or proactively choosing pipes likely to fail. Machine learning can find fragile pipes more accurately than using age or historical breaks as indicators. More accurate and often less expensive than other condition assessments, machine learning uses hundreds of variables to find patterns most people can't see. Timely selection of the right pipes to inspect, repair, or replace can reduce breaks and optimize the pipes’ remaining useful life.

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). 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. 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 BASDAIand 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. TNFi response did not differ according to baseline smoking status in this UKcohort. 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.

Depression is common among patients with axial spondyloarthritis (axSpA), but reports of its prevalence are highly variable. We performed a systematic review to (i) describe the prevalence of depression in axSpA, (ii) compare its prevalence between axSpA, ankylosing spondylitis (AS) and non-radiographic axSpA (nr-axSpA) cohorts, and (iii) compare disease activity and functional impairment between those with and without depression. We searched Medline, PubMed, Web of Science, PsycINFO, CINAHL Plus, the Cochrane library and conference abstracts of the European League Against Rheumatism, British Society for Rheumatology and American College of Rheumatology using a predefined protocol in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Meta-analysis was performed using quality-effects model. Fifteen original articles and one abstract were included for analysis; 14 studies described AS cohorts and two nr-axSpA. Three screening criteria and one diagnostic criterion were used to define depression. Prevalence ranged from 11 to 64% depending on criteria and thresholds used. Pooled prevalence of at least moderate depression was 15% using the Hospital Anxiety and Depression Scale (HADS) threshold of ≥ 11. The prevalence of depression was similar between axSpA, AS and nr-axSpA cohorts. Patients with depression had significantly worse disease activity, including higher BASDAI by 1.4 units (95% CI 1.0 to 1.9), ASDAS by 0.5 units (95% CI 0.3 to 0.7) and ESR by 3.5 mm/h (95% CI 0.6 to 6.4). They also had greater functional impairment with higher BASFI and BASMI by 1.2 units (95% CI 0.6 to 1.8) and 0.6 units (95% CI 0.3 to 0.8), respectively. Mean age of each study cohort inversely correlated with depression prevalence. Depression is common among axSpA patients and is associated with more severe disease activity and functional impairment. Identifying and managing depression should form part of their holistic care. Further longitudinal studies are needed to explore the impact of depression on treatment outcomes and axSpA treatment on symptoms of depression.

Compliance with the Stage 2 Disinfectants and Disinfection Byproducts (DBP) Rule is often achieved by treating water at a treatment plant to reduce DBP formation. However, it could be more cost‐effective to use localized treatment in the distribution system to target specific problem areas.

Brain metastases (BMs) in patients with advanced and metastatic NSCLC are linked to poor prognosis. Identifying genomic alterations associated with BM development could influence screening and determine targeted treatment. We aimed to establish prevalence and incidence in these groups, stratified by genomic alterations.

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.

A survey was conducted to assess pressure management practices in water distribution systems. Most of the surveyed utilities agreed on the need to avoid low‐pressure episodes (< 20 psi). However, 56% of the utilities had no requirements for the maximum pressure delivered to customers, and 67% did not manage peak pressures in their systems. Only 13% of surveyed systems conducted pressure monitoring at critical locations—e.g., sites of highest or lowest pressure. Approximately 50% of systems reported at least one occurrence of negative pressure during the previous year; however, many more incidents of low and/or negative pressure may have gone undetected. The authors recommend that distribution system pressures be monitored in at least two locations in each pressure zone, representing the highest and lowest pressures. The recording interval could be set to 5–10 min with a 10‐s sampling interval. Impulse recording (when available) should be enabled to capture momentary pressure changes.

North American water utilities increasingly are mandating water audits and other initiatives to improve water supply efficiency. But before selecting the best water loss reduction strategy, a utility must understand the nature and extent of its losses. Numerous technologies are available to assist with an active leakage management program.

Backflow from customer service connections is of concern to water utilities, but few data about the frequency of such occurrences exist and little is known about how to monitor for backflow into the distribution system. For the first time, occurrence statistics for residential backflow have been quantified. As it turns out, backflow is a much more widespread problem than currently believed. Backflow has now been shown to occur in 1.6% of all meter reads and in 5% of homes with backflow‐sensing meters. Using pilot tests to examine the effectiveness of water quality sensors to detect a range of contaminants, the authors found that even though the monitors were sensitive to small changes in quality, they cannot be used to assess the public health effects of such events. This is because wide variations in background distribution system quality overwhelmed the ability of current data processing technology to differentiate between water quality fluctuations caused by backflow from those attributable to normal variability. Backflow‐sensing meters, combined with an effective pressure management program to minimize or eliminate pressure transients (a primary cause of backsiphonage cross‐connections) and integrated into a fixed network automated meter reading/advanced metering infrastructure system, can provide utilities with near real‐time information on backflow events. The analyses conducted in this study show that the use of backflow‐sensing meters is the best available technology for determining the occurrence of residential backflow. Given the benefits shown by these meters, their slightly higher cost ($15‐$20/meter) over regular meters is money well spent.

This article discusses advanced metering infrastructure (AMI), a metering system that records customer consumption hourly or more frequently, and provides for daily or more frequent transmittal of measurements over a communication network to a central collection point. The article describes the use of AMI in the energy (electric utilities) industry but focuses on its use in the water industry, demonstrating how the technology is ideal for the water industry challenges of managing growing water demand against shrinking supplies, higher operating costs, and reduced staff. Drivers behind the interest in AMI include: growing demand for systems that help reduce nonrevenue water losses and associated delivery costs, stem hidden water losses, support water conservation programs, manage peak loads, improve the integrity of delivery systems, and plan for future growth; curtailing water consumption during peak‐energy or drought‐induced restricted‐use periods; and, information management for water delivery and use. AMI benefits for the water industry are discussed, along with the five main components of an AMI system

On March 4, 2022, the American Medical Association (AMA) released a statement in response to the Biden administration’s plan of a test-to-treat plan allowing pharmacists to serve as locations to test and provide prescriptions for oral antivirals for treatment of COVID-19 after a positive test result. The statement by the AMA contradicts and underrepresents the impact pharmacists have in clinical practice. Pharmacists have been a crucial part of many efforts including mass vaccination efforts and furnishing of prescriptions for other complex disease states (e.g., PrEP and PEP therapy). Furthermore, health systems have proven novel approaches to mitigate operational and clinical barriers to COVID-19 therapies may offset the increased demand needed by communities. Herein, this commentary will discuss a viewpoint and counterpoint to the statement put out by the AMA, with a focus on pharmacists.

Two different analytical techniques were used to measure angiotensin converting enzyme (ACE) activity, and three different methods were used to measure each of the ACE inhibitors enalaprilat and benazeprilat. All measurements were made in human plasma. The groups of methods were compared by two different statistical approaches. First, the means of the methods were compared by the paired t test or analysis of variance, depending on whether two or three different methods were under comparison. Second, the squared coefficients of variation of the methods were compared by the Jackknife technique. The dual statistical approach employed enabled both the accuracy and the variability of the analytical methods to be compared and is a superior approach to the inappropriate use of correlation coefficients that are commonly used to compare analytical techniques. No statistically significant difference was found between the two assays used to measure ACE activity. Differences were found between the three methods to measure enalaprilat, although no obvious reason could be found for this phenomenon. Significant differences were also found between the three methods used to measure benazeprilat and were attributed to the presence of metabolites interfering in the nonspecific assay methods.

Oral and intravenous trimazosin, a quinazoline derivative, resulted in a significant reduction in blood pressure of normal subjects, particularly when the subjects rose from a supine position to standing. This hypotensive effect was maximal between 4 and 6 hr after dosing and was accompanied by a significant increase in heart rate. The responses to intravenous infusions of phenylephrine indicated that trimazosin had significant, selective, peripheral α1-antagonist properties. Kinetic analysis showed oral bioavailability of 63%, a clearance rate of 66 ml/min, and a terminal elimination t½ of approximately 3 hr. The correlation between drug levels and hypotensive effect was significantly improved by inclusion of the concentrations of trimazosin's major metabolite, 1 -hydroxy-trimazosin (CP 23445), particularly for the period of maximum effect. Our data show that acute administration of trimazosin is associated with a fall in blood pressure, an increase in heart rate, and a significant degree of α1-antagonism and that the overall hypotensive effect may in part be mediated by an active metabolite. It seems 1-hydroxy-trimazosin is a likely candidate for this role, but it is not clear whether this metabolite also has significant α-adrenoceptor antagonist properties.Clinical Pharmacology and Therapeutics (1984) 35, 156–160; doi:10.1038/clpt.1984.21

ObjectiveTo assess the performance of the SARS-CoV-2 antigen rapid lateral flow test (LFT) versus polymerase chain reaction testing in the asymptomatic general population attending testing centres.DesignObservational cohort study.SettingCommunity LFT pilot at covid-19 testing sites in Liverpool, UK.Participants5869 asymptomatic adults (≥18 years) voluntarily attending one of 48 testing sites during 6-29 November 2020.InterventionsParticipants were tested using both an Innova LFT and a quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR) test based on supervised self-administered swabbing at testing sites.Main outcome measuresSensitivity, specificity, and predictive values of LFT compared with RT-qPCR in an epidemic steady state of covid-19 among adults with no classic symptoms of the disease.ResultsOf 5869 test results, 22 (0.4%) LFT results and 343 (5.8%) RT-qPCR results were void (that is, when the control line fails to appear within 30 minutes). Excluding the void results, the LFT versus RT-qPCR showed a sensitivity of 40.0% (95% confidence interval 28.5% to 52.4%; 28/70), specificity of 99.9% (99.8% to 99.99%; 5431/5434), positive predictive value of 90.3% (74.2% to 98.0%; 28/31), and negative predictive value of 99.2% (99.0% to 99.4%; 5431/5473). When the void samples were assumed to be negative, a sensitivity was observed for LFT of 37.8% (26.8% to 49.9%; 28/74), specificity of 99.6% (99.4% to 99.8%; 5431/5452), positive predictive value of 84.8% (68.1% to 94.9%; 28/33), and negative predictive value of 93.4% (92.7% to 94.0%; 5431/5814). The sensitivity in participants with an RT-qPCR cycle threshold (Ct) of <18.3 (approximate viral loads >106RNA copies/mL) was 90.9% (58.7% to 99.8%; 10/11), a Ct of <24.4 (>104RNA copies/mL) was 69.4% (51.9% to 83.7%; 25/36), and a Ct of >24.4 (<104RNA copies/mL) was 9.7% (1.9% to 23.7%; 3/34). LFT is likely to detect at least three fifths and at most 998 in every 1000 people with a positive RT-qPCR test result with high viral load.ConclusionsThe Innova LFT can be useful for identifying infections among adults who report no symptoms of covid-19, particularly those with high viral load who are more likely to infect others. The number of asymptomatic adults with lower Ct (indicating higher viral load) missed by LFT, although small, should be considered when using single LFT in high consequence settings. Clear and accurate communication with the public about how to interpret test results is important, given the chance of missing some cases, even at high viral loads. Further research is needed to understand how infectiousness is reflected in the viral antigen shedding detected by LFT versus the viral loads approximated by RT-qPCR.

Background: Brain metastases are common in clinical practice. Many clinical scales exist for predicting survival and hence deciding on best treatment but none are individualised and none use quantitative imaging parameters. A multicenter study was carried out to evaluate the prognostic utility of a simple diffusion weighted MRI parameter, tumor apparent diffusion coefficient (ADC). Methods: A retrospective analysis of imaging and clinical data was performed on a cohort of 223 adult patients over a ten-year period 2002–2012 pooled from three institutions. All patients underwent surgical resection with histologically confirmed brain metastases and received adjuvant whole brain radiotherapy and/or chemotherapy. Survival was modelled using standard clinical variables and statistically compared with and without the addition of tumor ADC. Results: The median overall survival was 9.6 months (95% CI 7.5–11.7) for this cohort. Greater age (p= 0.002), worse performance status (p&lt; 0.0001) and uncontrolled extracranial disease (p&lt; 0.0001) were all significantly associated with shorter survival in univariate analysis. Adjuvant whole brain radiotherapy (p= 0.007) and higher tumor ADC (p&lt; 0.001) were associated with prolonged survival. Combining values of tumor ADC with conventional clinical scoring systems such as the Graded Prognostic Assessment (GPA) score significantly improved the modelling of survival (e.g. concordance increased from 0.5956 to 0.6277 with Akaike’s Information Criterion reduced from 1335 to 1324). Conclusions: Combining advanced MRI readings such as tumor ADC with clinical scoring systems is a potentially simple method for improving and individualising the estimation of survival in patients having surgery for brain metastases.

This article describes a new bulk-water fill station that was moved to a more convenient location on the grounds of the Ridley Creek Water Treatment Plant in Media, Pennsylvania. This new fill station can be accessed from outside the plant fence line and operated automatically around the clock without disrupting personnel. The article describes how it is constructed and operated, and reports on the costs incurred by the project.