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Aim: To examine the psychometric properties of a short form version of the Numinous Motivation Inventory (NMI) for use with healthcare providers in measuring their existential engagement with life and to assess its relationship with spiritual coping and emotional dysphoria. Design: Correlational and psychometric study. Method: Data were collected from June to December 2022. Participants included 102 physicians, recruited from across the United States. Qualtrics was utilized to collect data, and they were evaluated with the NMI short form, Spiritual Coping Questionnaire and Depression, Anxiety, and Stress scale (DASS‐21). Results: Obtained fit statistics from structural equation modelling analysis indicated close fit of the NMI short form with the original model. Multiple regression analyses demonstrated the value of the NMI as a predictor of negative affect independent of spiritual coping. The NMI did not interact with Spiritual Coping, which was independent of negative affect. Conclusions: The Numinous represents an important aspect of physicians' coping. The constructs can be utilized in training and clinical settings as a valuable and easy‐to‐use metric for promoting and assessing wellness. The implications of these findings and the value of the NMI were discussed. Impact: An understanding of existential drivers can equip one to cope with the stressors of healthcare. The NMI short form has the capability to explore an individual's existential drivers through the understanding of three domains. Reporting Method: Adhered to proper EQUATOR guidelines (GRRAS). Public Contribution: No patient or public contribution. [ABSTRACT FROM AUTHOR]

Background: Guidelines by the National Institute for Health and Care Excellence recommend an angiotensin receptor blocker (ARB) rather than an angiotensin-converting enzyme inhibitor (ACEi) for the treatment of hypertension for people of African and Caribbean descent, due to an increased risk of angioedema associated with ACEi use observed in US trials. However, the effectiveness and risk of these drugs in Black populations in UK routine care is unknown. Methods and findings: We applied a reference trial emulation approach to UK Clinical Practice Research Datalink Aurum data (linked with data from Hospital Episode Statistics and Office for National Statistics) to study the comparative effectiveness of ARB and ACEi in ethnic minority groups in England, after benchmarking results against the ONTARGET trial. Approximately 17,593 Black, 30,805 South Asian, and 524,623 White patients receiving a prescription for ARB/ACEi between 1 January 2001 and 31 July 2019 were included with a median follow-up of 5.2 years. The primary composite outcome was cardiovascular-related death, myocardial infarction, stroke, or hospitalisation for heart failure with individual components studied as secondary outcomes. Angioedema was a safety endpoint. We assessed outcomes using an inverse-probability—weighted Cox proportional hazards model for ARB versus ACEi with heterogeneity by ethnicity assessed on the relative and absolute scale. For the primary outcome, 27,327 (18.0%) events were recorded in the ARB group (event rate: 25% per 5.5 person-years) and 80,624 (19.1%) events (event rate: 26% per 5.5 person-years) in the ACEi group. We benchmarked results against ONTARGET and observed hazard ratio (HR) 0.96 (95% CI: 0.95, 0.98) for the primary outcome, with an absolute incidence rate difference (IRD)% of -1.01 (95% CI: -1.42, -0.60) per 5.5 person-years. We found no evidence of treatment effect heterogeneity by ethnicity for the primary outcome on the multiplicative (Pint = 0.422) or additive scale (Pint = 0.287). Results were consistent for most secondary outcomes. However, for cardiovascular-related death, which occurred in 37,554 (6.6%) people, there was strong evidence of heterogeneity on the multiplicative (Pint = 0.002) and additive scale (Pint < 0.001). Compared to ACEi, ARB were associated with more events in Black individuals (HR 1.20 (95% CI: 1.02, 1.40); IRD% 1.07 (95% CI: 0.10, 2.04); number-needed-to-harm (NNH): 93) and associated with fewer events in White individuals (HR 0.91 (95% CI: 0.88, 0.93); IRD% -0.87 (95% CI: -1.10, -0.63); number-needed-to-treat (NNT): 115), and no differences in South Asian individuals (HR 0.97 (95% CI: 0.86, 1.09); IRD% -0.17 (95% CI: -0.87, 0.53)). For angioedema, HR 0.56 (95% CI: 0.46, 0.67) with no heterogeneity for ARB versus ACEi on the multiplicative scale (Pint = 0.306). However, there was heterogeneity on the additive scale (Pint = 0.023). Absolute risks were higher in Black individuals (IRD% -0.49 (95% CI: -0.79, -0.18); NNT: 204) compared with White individuals (IRD% -0.06 (95% CI: -0.09, -0.03); NNT: 1667) and no difference among South Asian individuals (IRD% -0.05 (95% CI: -0.15, 0.05) for ARB versus ACEi. Conclusions: These results demonstrate variation in drug effects of ACEi and ARB for some outcomes by ethnicity and suggest the potential for adverse consequences from current UK guideline recommendations for ARB in preference to ACEi for Black individuals. Leveraging data form the UK CPRD Aurum, Paris Jade Baptiste and colleagues apply target trial emulation methods to a cohort of >570,000 participants to explore the effectiveness and risk of ACE-inhibitors and ARB according to ethnicity. Author summary: Why was this study done?: UK hypertension treatment guidelines, which include ethnicity (Black versus non-Black) as a determinant of treatment choice are based on evidence from dated randomised controlled trials (RCTs) often arising from US populations, with conclusions extrapolated to ethnic minority groups in the UK. Despite an increased risk of hypertension and cardiovascular disease among South Asian patients in the UK, little is known about comparative treatment effectiveness and risk of angiotensin receptor blocker (ARB) and angiotensi-converting enzyme inhibitor (ACEi). Using reference trial emulation (considering study design and benchmarking against an existing RCT), followed by analysis of effects in trial-underrepresented groups can add confidence to findings of observational research and bridge gaps in evidence, allowing us to explore the "real-world" generalisability of the ONTARGET trial. What did the researchers do and find?: The researchers used a reference trial emulation approach, applied to self-reported Black, South Asian, and White patients at high risk of cardiovascular disease in primary care data from England, applied trial eligibility criteria, and benchmarked findings against the ONTARGET trial, which compared ARB versus ACEi on cardiovascular outcomes. Our results support the generalisability of the ONTARGET trial results to ethnic minority populations being prescribed an ARB or ACEi in England. Results suggest for cardiovascular death, treatment with ACEi might be associated with fewer events in people who are Black and ARB with fewer events in people who are White. Relative risks of angioedema for ARB versus ACEi were similar across all ethnic groups but because of the increased incidence in Black patients, there was a marked difference in the number needed to harm for ARB compared to ACEi use. There was no difference in cardiovascular outcomes or angioedema between the ARB versus ACEi in South Asian patients. What do these findings mean?: Unlike traditional RCTs, the reference trial emulation design provides an opportunity to study effects in large, diverse samples with the possibility to identify subgroup effects among trial-underrepresented groups, including South Asian and Black patients. Our results suggest variation in drug effects of ACEi and ARB by ethnicity for some outcomes and suggest the potential for adverse consequences from current UK guideline recommendations for ARB in preference to ACEi for Black individuals. Limitions include a risk of chance findings due to multiple testing by repeating all outcomes of ONTARGET. Despite taking measures to address confounding, unmeasured confounding could remain due to the nature of the study design. Without replication, it is uncertain to what extent our finding of differences in outcomes for ARB versus ACEi by ethnicity should influence current guidelines that recommend ARB over ACEi for Black individuals. [ABSTRACT FROM AUTHOR]

Propensity score methods, such as inverse probability‐of‐treatment weighting (IPTW), have been increasingly used for covariate balancing in both observational studies and randomized trials, allowing the control of both systematic and chance imbalances. Approaches using IPTW are based on two steps: (i) estimation of the individual propensity scores (PS), and (ii) estimation of the treatment effect by applying PS weights. Thus, a variance estimator that accounts for both steps is crucial for correct inference. Using a variance estimator which ignores the first step leads to overestimated variance when the estimand is the average treatment effect (ATE), and to under or overestimated estimates when targeting the average treatment effect on the treated (ATT). In this article, we emphasize the importance of using an IPTW variance estimator that correctly considers the uncertainty in PS estimation. We present a comprehensive tutorial to obtain unbiased variance estimates, by proposing and applying a unifying formula for different types of PS weights (ATE, ATT, matching and overlap weights). This can be derived either via the linearization approach or M‐estimation. Extensive R code is provided along with the corresponding large‐sample theory. We perform simulation studies to illustrate the behavior of the estimators under different treatment and outcome prevalences and demonstrate appropriate behavior of the analytical variance estimator. We also use a reproducible analysis of observational lung cancer data as an illustrative example, estimating the effect of receiving a PET‐CT scan on the receipt of surgery. [ABSTRACT FROM AUTHOR]

Background: Non‐inferiority trials comparing different active drugs are often subject to treatment non‐adherence. Intention‐to‐treat (ITT) and per‐protocol (PP) analyses have been advocated in such studies but are not guaranteed to be unbiased in the presence of differential non‐adherence. Methods: The REMoxTB trial evaluated two 4‐month experimental regimens compared with a 6‐month control regimen for newly diagnosed drug‐susceptible TB. The primary endpoint was a composite unfavorable outcome of treatment failure or recurrence within 18 months post‐randomization. We conducted a simulation study based on REMoxTB to assess the performance of statistical methods for handling non‐adherence in non‐inferiority trials, including: ITT and PP analyses, adjustment for observed adherence, multiple imputation (MI) of outcomes, inverse‐probability‐of‐treatment weighting (IPTW), and a doubly‐robust (DR) estimator. Results: When non‐adherence differed between trial arms, ITT, and PP analyses often resulted in non‐trivial bias in the estimated treatment effect, which consequently under‐ or over‐inflated the type I error rate. Adjustment for observed adherence led to similar issues, whereas the MI, IPTW and DR approaches were able to correct bias under most non‐adherence scenarios; they could not always eliminate bias entirely in the presence of unobserved confounding. The IPTW and DR methods were generally unbiased and maintained desired type I error rates and statistical power. Conclusions: When non‐adherence differs between trial arms, ITT and PP analyses can produce biased estimates of efficacy, potentially leading to the acceptance of inferior treatments or efficacious regimens being missed. IPTW and the DR estimator are relatively straightforward methods to supplement ITT and PP approaches. [ABSTRACT FROM AUTHOR]

The article discusses a study which examined the effectiveness of two doses of coronavirus disease 2019 (COVID-19) vaccine beyond six months in England. Topics include increase in the cumulative incidence of receiving a third dose of vaccine during the eight weeks following eligibility, basis of the effectiveness of two doses during later comparison periods, and important factors in interpreting estimated vaccine effectiveness (VE).

No randomized controlled trial has evaluated the effect of long-term alcohol interventions on mortality. Results reported in existing observational studies may be subject to selection bias and time-varying confounding. Using data from the Australian Longitudinal Study on Women's Health 1946–1951 birth cohort, collected regularly from 1996–2016, we estimated all-cause and cancer mortality had women been assigned various alcohol interventions (in categories ranging from 0 to >30 g/day ethanol, or reduced to ≤20 g/day if higher) at baseline, and had they maintained these levels of consumption. The cumulative risks for all-cause and cancer mortality were 5.6% (10,118 women followed for 20 years) and 2.9% (18 years), respectively. For all-cause and cancer mortality, baseline ethanol up to 30 g/day showed lower risk and >30 g/day showed higher risk relative to abstention. Had women sustainedly followed the interventions, a similar relationship was observed for all-cause mortality. However, the negative association observed for intakes ≤30 g/day and positive association for intakes >30 g/day was not evident for cancer mortality. Our findings suggest that all-cause mortality could have been lower than observed if this cohort of women had consumed some alcohol (no more than 30 g/day) rather than no consumption, but cancer mortality might not. [ABSTRACT FROM AUTHOR]

Replicative DNA polymerases are blocked by nearly all types of DNA damage. The resulting DNA replication stress threatens genome stability. DNA replication stress is also caused by depletion of nucleotide pools, DNA polymerase inhibitors, and DNA sequences or structures that are difficult to replicate. Replication stress triggers complex cellular responses that include cell cycle arrest, replication fork collapse to one-ended DNA double-strand breaks, induction of DNA repair, and programmed cell death after excessive damage. Replication stress caused by specific structures (e.g., G-rich sequences that form G-quadruplexes) is localized but occurs during the S phase of every cell division. This review focuses on cellular responses to widespread stress such as that caused by random DNA damage, DNA polymerase inhibition/nucleotide pool depletion, and R-loops. Another form of global replication stress is seen in cancer cells and is termed oncogenic stress, reflecting dysregulated replication origin firing and/or replication fork progression. Replication stress responses are often dysregulated in cancer cells, and this too contributes to ongoing genome instability that can drive cancer progression. Nucleases play critical roles in replication stress responses, including MUS81, EEPD1, Metnase, CtIP, MRE11, EXO1, DNA2-BLM, SLX1-SLX4, XPF-ERCC1-SLX4, Artemis, XPG, FEN1, and TATDN2. Several of these nucleases cleave branched DNA structures at stressed replication forks to promote repair and restart of these forks. We recently defined roles for EEPD1 in restarting stressed replication forks after oxidative DNA damage, and for TATDN2 in mitigating replication stress caused by R-loop accumulation in BRCA1-defective cells. We also discuss how insights into biological responses to genome-wide replication stress can inform novel cancer treatment strategies that exploit synthetic lethal relationships among replication stress response factors. [ABSTRACT FROM AUTHOR]

Purpose: Prevalent new user (PNU) designs extend the active comparator new user design by allowing for the inclusion of initiators of the study drug who were previously on a comparator treatment. We performed a literature review summarising current practice. Methods: PubMed was searched for studies applying the PNU design since its proposal in 2017. The review focused on three components. First, we extracted information on the overall study design, including the database used. We summarised information on implementation of the PNU design, including key decisions relating to exposure set definition and estimation of time‐conditional propensity scores. Finally, we reviewed the analysis strategy of the matched cohort. Results: Nineteen studies met the criteria for inclusion. Most studies (73%) implemented the PNU design in electronic health record or registry databases, with the remaining using insurance claims databases. Of 15 studies including a class of prevalent users, 40% deviated from the original exposure set definition proposals in favour of a more complex definition. Four studies did not include prevalent new users but used other aspects of the PNU framework. Several studies lacked details on exposure set definition (n = 2), time‐conditional propensity score model (n = 2) or integration of complex analytical techniques, such as the high‐dimensional propensity score algorithm (n = 3). Conclusion: PNU designs have been applied in a range of therapeutic and disease areas. However, to encourage more widespread use of this design and help shape best practice, there is a need for improved accessibility, specifically through the provision of analytical code alongside guidance to support implementation and transparent reporting. [ABSTRACT FROM AUTHOR]

Clinical trials that investigate physical activity interventions often use accelerometers to measure step count at a very granular level, for example in 5-second epochs. Participants typically wear the accelerometer for a week-long period at baseline, and for one or more week-long follow-up periods after the intervention. The data is aggregated to provide daily or weekly step counts for the primary analysis. Missing data are common as participants may not wear the device as per protocol. Approaches to handling missing data in the literature have defined missingness on the day level using a threshold on daily weartime, which leads to loss of information on the time of day when data are missing. We propose an approach to identifying and classifying missingness at the finer epoch-level and present two approaches to handling missingness using multiple imputation. Firstly, we present a parametric approach which accounts for the number of missing epochs per day. Secondly, we describe a non-parametric approach where missing periods during the day are replaced by donor data from the same person where possible, or data from a different person who is matched on demographic and physical activity-related variables. Our simulation studies show that the non-parametric approach leads to estimates of the effect of treatment that are least biased while maintaining small standard errors. We illustrate the application of these different multiple imputation strategies to the analysis of the 2017 PACE-UP trial. The proposed framework is likely to be applicable to other digital health outcomes and to other wearable devices. [ABSTRACT FROM AUTHOR]

Large healthcare databases are increasingly used for research investigating the effects of medications. However, a key challenge is capturing hard-tomeasure concepts (often relating to frailty and disease severity) that can be crucial for successful confounder adjustment. The high-dimensional propensity score has been proposed as a data-driven method to improve confounder adjustment within healthcare databases and was developed in the context of administrative claims databases. We present hdps, a suite of commands implementing this approach in Stata that assesses the prevalence of codes, generates high-dimensional propensity-score covariates, performs variable selection, and provides investigators with graphical tools for inspecting the properties of selected covariates. [ABSTRACT FROM AUTHOR]

Reintroduction and translocation programs have been sparingly used for the management of endangered primate populations. Mount Tshiaberimu in eastern Democratic Republic of the Congo (DRC) contains 6 Grauer's gorillas (Gorilla beringei graueri) with only 2 adult females. Without intervention, this population is at high risk of extinction. We designed population viability analysis models to compare different release scenarios of wild‐born captive female gorillas housed at the Gorilla Rehabilitation and Conservation Education (GRACE) Center in the DRC. We identified the minimum number of females needed to maintain a viable population in this habitat. We used a stochastic Leslie matrix model and a more complex individual‐based model to project population growth. We used published demographic parameters for mountain gorillas (Gorilla b. beringei) corresponding to a 3.2% annual growth rate, and then applied a correction factor to female fertility to obtain parameters consistent with 1% and 2% growth rates. We ran each scenario over a 50‐year time period (1,000 simulations) to determine the final population size and risk of local extinction. Results from our optimistic (3.2% growth) and conservative (1% growth) individual‐based model projections indicated that the extinction risk dropped below 1% with the release of at least 2 or 3 females, respectively. Both approaches predicted similar extinction risks for all scenarios; however, the variance in final population size was higher with the individual‐based model. For long‐lived mammals like primates, we recommend the use of individual‐based models, which can incorporate life‐history parameters such as long gestation and nursing periods. Our analysis suggests a translocation of ≥3 females to rescue the Tshiaberimu gorilla population in the short term. Factors such as inbreeding depression, habitat quality, disease risks, and anthropogenic pressures will need to be evaluated in later stages of population reinforcement planning. [ABSTRACT FROM AUTHOR]

Emulating a hypothetical "target trial" using observational data assembled during vaccine rollouts can help manage potential sources of bias in observational studies of the COVID-19 vaccines. This article describes 2 approaches to target trial emulation using observational data that can help design studies that provide robust evidence to guide clinical and policy decisions. The COVID-19 vaccines were developed and rigorously evaluated in randomized trials during 2020. However, important questions, such as the magnitude and duration of protection, their effectiveness against new virus variants, and the effectiveness of booster vaccination, could not be answered by randomized trials and have therefore been addressed in observational studies. Analyses of observational data can be biased because of confounding and because of inadequate design that does not consider the evolution of the pandemic over time and the rapid uptake of vaccination. Emulating a hypothetical "target trial" using observational data assembled during vaccine rollouts can help manage such potential sources of bias. This article describes 2 approaches to target trial emulation. In the sequential approach, on each day, eligible persons who have not yet been vaccinated are matched to a vaccinated person. The single-trial approach sets a single baseline at the start of the rollout and considers vaccination as a time-varying variable. The nature of the confounding depends on the analysis strategy: Estimating "per-protocol" effects (accounting for vaccination of initially unvaccinated persons after baseline) may require adjustment for both baseline and "time-varying" confounders. These issues are illustrated by using observational data from 2 780 931 persons in the United Kingdom aged 70 years or older to estimate the effect of a first dose of a COVID-19 vaccine. Addressing the issues discussed in this article should help authors of observational studies provide robust evidence to guide clinical and policy decisions. [ABSTRACT FROM AUTHOR]

This article introduces 'ArtActivistBarbie', a modern day Trickster who draws upon the Trickster archetype and traditions found in folklore and myth. This involves the provocative staging of Barbie dolls in national art museums and galleries as 'ArtActivistBarbie', a fearless feminist activist. Thousands follow ArtActivistBarbie on Twitter, enjoying her performative work in what she describes as 'Patriarchal Palaces of Painting', and which is often served with a dash of wit. Her subversive, playful disruption and creative interventions asks questions and raises issues about gender and the inequalities in many public art collections. There is a need for more contemporary female Tricksters such as ArtActivistBarbie to illuminate and challenge societal injustice. [ABSTRACT FROM AUTHOR]

One of the main challenges when using observational data for causal inference is the presence of confounding. A classic approach to account for confounding is the use of propensity score techniques that provide consistent estimators of the causal treatment effect under four common identifiability assumptions for causal effects, including that of no unmeasured confounding. Propensity score matching is a very popular approach which, in its simplest form, involves matching each treated patient to an untreated patient with a similar estimated propensity score, that is, probability of receiving the treatment. The treatment effect can then be estimated by comparing treated and untreated patients within the matched dataset. When missing data arises, a popular approach is to apply multiple imputation to handle the missingness. The combination of propensity score matching and multiple imputation is increasingly applied in practice. However, in this article we demonstrate that combining multiple imputation and propensity score matching can lead to over‐coverage of the confidence interval for the treatment effect estimate. We explore the cause of this over‐coverage and we evaluate, in this context, the performance of a correction to Rubin's rules for multiple imputation proposed by finding that this correction removes the over‐coverage. [ABSTRACT FROM AUTHOR]

Adjustment for baseline covariates in randomized trials has been shown to lead to gains in power and can protect against chance imbalances in covariates. For continuous covariates, there is a risk that the the form of the relationship between the covariate and outcome is misspecified when taking an adjusted approach. Using a simulation study focusing on individually randomized trials with small sample sizes, we explore whether a range of adjustment methods are robust to misspecification, either in the covariate–outcome relationship or through an omitted covariate–treatment interaction. Specifically, we aim to identify potential settings where G-computation, inverse probability of treatment weighting (IPTW), augmented inverse probability of treatment weighting (AIPTW) and targeted maximum likelihood estimation (TMLE) offer improvement over the commonly used analysis of covariance (ANCOVA). Our simulations show that all adjustment methods are generally robust to model misspecification if adjusting for a few covariates, sample size is 100 or larger, and there are no covariate–treatment interactions. When there is a non-linear interaction of treatment with a skewed covariate and sample size is small, all adjustment methods can suffer from bias; however, methods that allow for interactions (such as G-computation with interaction and IPTW) show improved results compared to ANCOVA. When there are a high number of covariates to adjust for, ANCOVA retains good properties while other methods suffer from under- or over-coverage. An outstanding issue for G-computation, IPTW and AIPTW in small samples is that standard errors are underestimated; they should be used with caution without the availability of small-sample corrections, development of which is needed. These findings are relevant for covariate adjustment in interim analyses of larger trials. [ABSTRACT FROM AUTHOR]

Purpose: The BCL-2 family of anti-apoptotic proteins, BCL-2, BCL-XL and MCL-1, can mediate survival of some types of cancer. DT2216 is a PROteolysis-TArgeting Chimera (PROTAC) that degrades BCL-XL specifically and is in phase 1 trials. We sought to define the frequency and mechanism of resistance to DT2216 in T-cell acute lymphoblastic leukemia (T-ALL) cell lines. Methods: We measured cell survival and protein levels of BCL-XL, BCL-2, MCL-1 and the pro-apoptotic BIM in 13 distinct T-ALL cell lines after exposure to varying concentrations of DT2216. Results: We identified concentrations of DT2216 which were cytotoxic to each T-ALL cell line. These concentrations have no correlation with the initial protein levels of BCL-XL, BCL-2, MCL-1 or BIM in each cell line. However, there was a correlation between survival to DT2216 and the efficiency of degradation of BCL-XL by DT2216. Only one cell line, SUP-T1, had significant resistance to DT2216, defined as an IC50 above what is achievable in murine tumors in vivo. Conclusion: Resistance to DT2216 is rare in a wide variety of T-ALL cells but when it occurs is correlated with decreased BCL-XL degradation. Resistance to DT2216 in T-ALL is not predicted by initial BCL-XL or BIM protein levels, or BCL-2 or MCL-1 levels before or after treatment. These data imply that a phase 2 clinical trial of DT2216 in T-ALL should be widely available and not limited to a subset of patients. [ABSTRACT FROM AUTHOR]

Background Ethnic differences in the risk of severe COVID-19 may be linked to household composition. We quantified the association between household composition and risk of severe COVID-19 by ethnicity for older individuals. Methods With the approval of NHS England, we analysed ethnic differences in the association between household composition and severe COVID-19 in people aged 67 or over in England. We defined households by number of age-based generations living together, and used multivariable Cox regression stratified by location and wave of the pandemic and accounted for age, sex, comorbidities, smoking, obesity, housing density and deprivation. We included 2 692 223 people over 67 years in Wave 1 (1 February 2020–31 August 2020) and 2 731 427 in Wave 2 (1 September 2020–31 January 2021). Results Multigenerational living was associated with increased risk of severe COVID-19 for White and South Asian older people in both waves [e.g. Wave 2, 67+ living with three other generations vs 67+-year-olds only: White hazard ratio (HR) 1.61 95% CI 1.38–1.87, South Asian HR 1.76 95% CI 1.48–2.10], with a trend for increased risks of severe COVID-19 with increasing generations in Wave 2. There was also an increased risk of severe COVID-19 in Wave 1 associated with living alone for White (HR 1.35 95% CI 1.30–1.41), South Asian (HR 1.47 95% CI 1.18–1.84) and Other (HR 1.72 95% CI 0.99–2.97) ethnicities, an effect that persisted for White older people in Wave 2. Conclusions Both multigenerational living and living alone were associated with severe COVID-19 in older adults. Older South Asian people are over-represented within multigenerational households in England, especially in the most deprived settings, whereas a substantial proportion of White older people live alone. The number of generations in a household, number of occupants, ethnicity and deprivation status are important considerations in the continued roll-out of COVID-19 vaccination and targeting of interventions for future pandemics. [ABSTRACT FROM AUTHOR]

In studies that compare physical activity between groups of individuals, it is common for physical activity to be quantified by step count, which is measured by accelerometers or other wearable devices. Missing step count data often arise in these settings and can lead to bias or imprecision in the estimated effect if handled inappropriately. Replacing each missing value in accelerometer data with a single value using the Expectation–Maximization (EM) algorithm has been advocated in the literature, but it can lead to underestimation of variances and could seriously compromise study conclusions. We compare the performance in terms of bias and variance of two missing data methods, the EM algorithm and Multiple Imputation (MI), through a simulation study where data are generated from a parametric model to reflect characteristics of a trial on physical activity. We also conduct a reanalysis of the 2019 MOVE-IT trial. The EM algorithm leads to an underestimate of the variance of effects of interest, in both the simulation study and the reanalysis of the MOVE-IT trial. MI should be the preferred approach to handling missing data in accelerometer, which provides valid point and variance estimates. [ABSTRACT FROM AUTHOR]

Objectives: To demonstrate that surgical sperm retrieval (SSR) and spermatogonial stem cell retrieval (SSCR) in an oncological context are safe and successful. Patients and Methods: This a retrospective study in a tertiary hospital in the UK. Patients requiring fertility preservation from December 2017 to January 2020 were included. Data were analysed with Microsoft Excel 2016 and the Statistical Package for the Social Sciences (version 20). Results: Among 1264 patients referred to the Reproductive Medical Unit at the University College of London Hospitals for cryopreservation prior to gonadotoxic treatment, 39 chose to go forward with SSR/SSCR because they presented as azoo‐/cryptozoospermic or an inability to masturbate/ejaculate. Interventions were testicular sperm extraction (23 patients) or aspiration (one), electroejaculation (one), and testicular wedge biopsy for SSCR (14). The median (range) age was 15.0 (10–65) years and the median testosterone level was 4.4 nmoL/L. Primary diagnoses were sarcoma in 11 patients, leukaemia in nine, lymphoma in eight, testicular tumour in five, other oncological haematological entities in two, other solid cancers in two, while two patients had non‐oncological haematological diseases. SSR/SSCR could be offered within 7.5 days on average. Chemotherapy could follow within 2 days from SSR/SSCR, and bone marrow transplant occurred within 19.5 days (all expressed as medians). The success rate for SSR was 68.0% (at least one vial/straw collected). The mean (SD) Johnsen score of testicular biopsies was 5.23 (2.25) with a trend towards positive correlation with SSR success (P = 0.07). However, age, hormonal profile and type of cancer did not predict SSR outcome. Conclusion: We show that SSR and SSCR in an oncological context are valid treatment options with a high success rate for patients in which sperm cryopreservation from semen is impossible. By providing an effective pathway, fertility preservation is possible with minimal delay to oncological treatment. [ABSTRACT FROM AUTHOR]

Over the last half-century, the world's human population has doubled, impacting almost all ocean and land areas. The threats facing primates in the wild have never been greater or more complex. Primatologists have long been aware of these threats and, since the 1970s, have coordinated efforts to safeguard these threatened species, through the International Union for Conservation of Nature Species Survival Commission (IUCN SSC) Primate Specialist Group (PSG). In an effort to stem the threat of extinction to primates, this group of now 700 experts+ has published 17 conservation action plans since 1977. As we look toward the next half-century, we take stock of the history of primate action planning to better understand the costs and benefits of these plans as a conservation tool. Here, we reviewed all plans published by the IUCN SSC PSG. In total, they described USD 246 million in planned primate conservation programming and were cited 1657 times by others. We found that half of the plans had been assessed in regard to their implementation, although these assessments were not standardized. Those that had been assessed, showed evidence of positive impacts on awareness raising, collaboration, fundraising, project implementation and policy, although the impact varied by plan. For example, three of the plans directly resulted in USD 15.92 million in funds raised; four plans quantified implementation rates, which ranged from 38% to 74% of actions partially or completely achieved 5 years after plan publication; and four plans attributed the gazettement of 19 protected areas across 11 countries as indirect successes following the publication of plans. Considered together, we reflect on the 'return-on-investment' for developing these plans and consider a range of 'lessons learned' for future primate action planning efforts. [ABSTRACT FROM AUTHOR]

Background: While the vaccines against COVID-19 are highly effective, COVID-19 vaccine breakthrough is possible despite being fully vaccinated. With SARS-CoV-2 variants still circulating, describing the characteristics of individuals who have experienced COVID-19 vaccine breakthroughs could be hugely important in helping to determine who may be at greatest risk.Methods: With the approval of NHS England, we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY-TPP database of fully vaccinated individuals, linked to secondary care and death registry data and described the characteristics of those experiencing COVID-19 vaccine breakthroughs.Results: As of 1st November 2021, a total of 15,501,550 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: ​107-179). From within this population, a total of 579,780 (<4%) individuals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate (IR) was 98.06 (95% CI 97.93-98.19). There were 28,580 COVID-19-related hospital admissions, 1980 COVID-19-related critical care admissions and 6435 COVID-19-related deaths; corresponding IRs 4.77 (95% CI 4.74-4.80), 0.33 (95% CI 0.32-0.34) and 1.07 (95% CI 1.06-1.09), respectively. The highest rates of breakthrough COVID-19 were seen in those in care homes and in patients with chronic kidney disease, dialysis, transplant, haematological malignancy or who were immunocompromised.Conclusions: While the majority of COVID-19 vaccine breakthrough cases in England were mild, some differences in rates of breakthrough cases have been identified in several clinical groups. While it is important to note that these findings are simply descriptive and cannot be used to answer why certain groups have higher rates of COVID-19 breakthrough than others, the emergence of the Omicron variant of COVID-19 coupled with the number of positive SARS-CoV-2 tests still occurring is concerning and as numbers of fully vaccinated (and boosted) individuals increases and as follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, to assess vaccine waning and rates of breakthrough COVID-19 between different variants, aimed at identifying individuals at higher risk, are needed. [ABSTRACT FROM AUTHOR]

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) alpha variant (B.1.1.7) is associated with higher transmissibility than wild-type virus, becoming the dominant variant in England by January 2021. We aimed to describe the severity of the alpha variant in terms of the pathway of disease from testing positive to hospital admission and death. Methods With the approval of NHS England, we linked individual-level data from primary care with SARS-CoV-2 community testing, hospital admission, and Office for National Statistics all-cause death data. We used testing data with S-gene target failure as a proxy for distinguishing alpha and wild-type cases, and stratified Cox proportional hazards regression to compare the relative severity of alpha cases with wild-type diagnosed from 16 November 2020 to 11 January 2021. Results Using data from 185 234 people who tested positive for SARS-CoV-2 in the community (alpha = 93 153; wild-type = 92 081), in fully adjusted analysis accounting for individual-level demographics and comorbidities as well as regional variation in infection incidence, we found alpha associated with 73% higher hazards of all-cause death (adjusted hazard ratio [aHR]: 1.73; 95% confidence interval [CI]: 1.41–2.13; P  < .0001) and 62% higher hazards of hospital admission (1.62; 1.48–1.78; P  < .0001) compared with wild-type virus. Among patients already admitted to the intensive care unit, the association between alpha and increased all-cause mortality was smaller and the CI included the null (aHR: 1.20; 95% CI:.74–1.95; P  = .45). Conclusions The SARS-CoV-2 alpha variant is associated with an increased risk of both hospitalization and mortality than wild-type virus. [ABSTRACT FROM AUTHOR]

Background: Early evidence has shown that anticoagulant reduces the risk of thrombotic events in those infected with COVID-19. However, evidence of the role of routinely prescribed oral anticoagulants (OACs) in COVID-19 outcomes is limited. Aim: To investigate the association between OACs and COVID-19 outcomes in those with atrial fibrillation and a CHA2DS2-VASc score of 2. Design and setting: On behalf of NHS England, a population-based cohort study was conducted. Method: The study used primary care data and pseudonymously-linked SARS-CoV-2 antigen testing data, hospital admissions, and death records from England. Cox regression was used to estimate hazard ratios (HRs) for COVID-19 outcomes comparing people with current OAC use versus non-use, accounting for age, sex, comorbidities, other medications, deprivation, and general practice. Results: Of 71 103 people with atrial fibrillation and a CHA2DS2-VASc score of 2, there were 52 832 current OAC users and 18 271 non-users. No difference in risk of being tested for SARS-CoV-2 was associated with current use (adjusted HR [aHR] 0.99, 95% confidence interval [CI] = 0.95 to 1.04) versus non-use. A lower risk of testing positive for SARS-CoV-2 (aHR 0.77, 95% CI = 0.63 to 0.95) and a marginally lower risk of COVID-19-related death (aHR, 0.74, 95% CI = 0.53 to 1.04) were associated with current use versus non-use. Conclusion: Among those at low baseline stroke risk, people receiving OACs had a lower risk of testing positive for SARS-CoV-2 and severe COVID-19 outcomes than non-users; this might be explained by a causal effect of OACs in preventing severe COVID-19 outcomes or unmeasured confounding, including more cautious behaviours leading to reduced infection risk. [ABSTRACT FROM AUTHOR]

Background: Socioeconomic factors have been consistently associated with suicide, and economic recessions are linked to rising suicide rates. However, evidence on the impact of socioeconomic interventions to reduce suicide rates is limited. This study investigates the association of the world's largest conditional cash transfer programme with suicide rates in a cohort of half of the Brazilian population.Methods and Findings: We used data from the 100 Million Brazilian Cohort, covering a 12-year period (2004 to 2015). It comprises socioeconomic and demographic information on 114,008,317 individuals, linked to the "Bolsa Família" programme (BFP) payroll database, and nationwide death registration data. BFP was implemented by the Brazilian government in 2004. We estimated the association of BFP using inverse probability of treatment weighting, estimating the weights for BFP beneficiaries (weight = 1) and nonbeneficiaries by the inverse probability of receiving treatment (weight = E(ps)/(1-E(ps))). We used an average treatment effect on the treated (ATT) estimator and fitted Poisson models to estimate the incidence rate ratios (IRRs) for suicide associated with BFP experience. At the cohort baseline, BFP beneficiaries were younger (median age 27.4 versus 35.4), had higher unemployment rates (56% versus 32%), a lower level of education, resided in rural areas, and experienced worse household conditions. There were 36,742 suicide cases among the 76,532,158 individuals aged 10 years, or older, followed for 489,500,000 person-years at risk. Suicide rates among beneficiaries and nonbeneficiaries were 5.4 (95% CI = 5.32, 5.47, p < 0.001) and 10.7 (95% CI = 10.51, 10.87, p < 0.001) per 100,000 individuals, respectively. BFP beneficiaries had a lower suicide rate than nonbeneficiaries (IRR = 0.44, 95% CI = 0.42, 0.45, p < 0.001). This association was stronger among women (IRR = 0.36, 95% CI = 0.33, 0.38, p < 0.001), and individuals aged between 25 and 59 (IRR = 0.41, 95% CI = 0.40, 0.43, p < 0.001). Study limitations include a lack of control for previous mental disorders and access to means of suicide, and the possible under-registration of suicide cases due to stigma.Conclusions: We observed that BFP was associated with lower suicide rates, with similar results in all sensitivity analyses. These findings should help to inform policymakers and health authorities to better design suicide prevention strategies. Targeting social determinants using cash transfer programmes could be important in limiting suicide, which is predicted to rise with the economic recession, consequent to the Coronavirus Disease 2019 (COVID-19) pandemic. [ABSTRACT FROM AUTHOR]

Simple Summary: The Coronavirus Disease 2019 (COVID-19) pandemic has made it harder to effectively protect and manage biodiversity, and this could make it more difficult for countries to show progress towards the Sustainable Development Goals (SDGs). Here, we surveyed experts in early 2022 from 30 countries to collect data on the impacts of COVID-19 on non-human primate research and conservation initiatives. Of the 93 experts that responded to our survey, we found that 39% had not been able to visit any of their field sites since March 2020 and only one out of ten had managed to achieve at least 76–100% of their planned primate-related work since March 2020. Six out of ten respondents (61%) felt that primate conservation efforts in protected areas were worse than before the onset of the COVID-19 pandemic and one-third (33%) felt hunting was happening more frequently than before. This study provides evidence of the impacts of COVID-19 on progress towards achieving SDG15 (Life on Land) and provides practical lessons learned for biodiversity conservation efforts moving forward. There is evidence to suggest that the Coronavirus Disease 2019 (COVID-19) pandemic may hamper our achievement of the Sustainable Development Goals (SDGs). Here, we use non-human primates as a case study to examine the impacts of COVID-19 on the ability to achieve biodiversity conservation and management sustainability targets. We collected data through a survey of members of the IUCN SSC Primate Specialist Group from January to March 2022. Of the 93 experts that responded to our survey, we found that 39% had not been able to visit any of their field sites since March 2020, 54% said they had less funding available for their primate-related work, and only one out of ten said they had managed to achieve at least 76–100% of their planned primate-related work since March 2020. Six out of ten respondents (61%) felt that primate conservation efforts in protected areas were worse than before the onset of the COVID-19 pandemic and one-third (33%) felt hunting was happening more frequently than before. This study provides evidence of the impacts of COVID-19 on progress towards achieving the SDGs, and provides practical lessons learned for biodiversity conservation efforts moving forward. [ABSTRACT FROM AUTHOR]

Background: It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates but it is not clear how to choose among them.Methods: Taking the perspective of writing a statistical analysis plan, we consider how to choose between the three most promising broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting.Results: The three approaches are similar in being asymptotically efficient, in losing efficiency with mis-specified covariate functions and in handling designed balance. If a marginal estimand is targeted (for example, a risk difference or survival difference), then direct adjustment should be avoided because it involves fitting non-standard models that are subject to convergence issues. Convergence is most likely with IPTW. Robust standard errors used by IPTW are anti-conservative at small sample sizes. All approaches can use similar methods to handle missing covariate data. With missing outcome data, each method has its own way to estimate a treatment effect in the all-randomised population. We illustrate some issues in a reanalysis of GetTested, a randomised trial designed to assess the effectiveness of an electonic sexually transmitted infection testing and results service.Conclusions: No single approach is always best: the choice will depend on the trial context. We encourage trialists to consider all three methods more routinely. [ABSTRACT FROM AUTHOR]

Background: Little data exists on the prevalence of chronic kidney disease (CKD) in the Russian population. We aimed to estimate the prevalence of CKD in a population-based study in Russia, compare with a similar study in Norway, and investigate whether differences in risk factors explained between-study differences in CKD.Methods: We compared age- and sex-standardised prevalence of reduced eGFR (< 60 ml/min/1.73m2 CKD-EPI creatinine equation), albuminuria and or a composite indicator of CKD (one measure of either reduced eGFR or albuminuria) between participants aged 40-69 in the population-based Know Your Heart (KYH) study, Russia (2015-2018 N = 4607) and the seventh Tromsø Study (Tromsø7), Norway (2015-2016 N = 17,646). We assessed the contribution of established CKD risk factors (low education, diabetes, hypertension, antihypertensive use, smoking, obesity) to between-study differences using logistic regression.Results: Prevalence of reduced eGFR or albuminuria was 6.5% (95% Confidence Interval (CI) 5.4, 7.7) in KYH and 4.6% (95% CI 4.0, 5.2) in Tromsø7 standardised for sex and age. Odds of both clinical outcomes were higher in KYH than Tromsø7 (reduced eGFR OR 2.06 95% CI 1.67, 2.54; albuminuria OR 1.54 95% CI 1.16, 2.03) adjusted for sex and age. Risk factor adjustment explained the observed between-study difference in albuminuria (OR 0.92 95% CI 0.68, 1.25) but only partially reduced eGFR (OR 1.42 95% CI 1.11, 1.82). The strongest explanatory factors for the between-study difference was higher use of antihypertensives (Russian sample) for reduced eGFR and mean diastolic blood pressure for albuminuria.Conclusions: We found evidence of a higher burden of CKD within the sample from the population in Arkhangelsk and Novosibirsk compared to Tromsø, partly explained by between-study population differences in established risk factors. In particular hypertension defined by medication use was an important factor associated with the higher CKD prevalence in the Russian sample. [ABSTRACT FROM AUTHOR]

Purpose The high‐dimensional propensity score (HDPS) is a semi‐automated procedure for confounder identification, prioritisation and adjustment in large healthcare databases that requires investigators to specify data dimensions, prioritisation strategy and tuning parameters. In practice, reporting of these decisions is inconsistent and this can undermine the transparency, and reproducibility of results obtained. We illustrate reporting tools, graphical displays and sensitivity analyses to increase transparency and facilitate evaluation of the robustness of analyses involving HDPS. Methods: Using a study from the UK Clinical Practice Research Datalink that implemented HDPS we demonstrate the application of the proposed recommendations. Results: We identify seven considerations surrounding the implementation of HDPS, such as the identification of data dimensions, method for code prioritisation and number of variables selected. Graphical diagnostic tools include assessing the balance of key confounders before and after adjusting for empirically selected HDPS covariates and the identification of potentially influential covariates. Sensitivity analyses include varying the number of covariates selected and assessing the impact of covariates behaving empirically as instrumental variables. In our example, results were robust to both the number of covariates selected and the inclusion of potentially influential covariates. Furthermore, our HDPS models achieved good balance in key confounders. Conclusions: The data‐adaptive approach of HDPS and the resulting benefits have led to its popularity as a method for confounder adjustment in pharmacoepidemiological studies. Reporting of HDPS analyses in practice may be improved by the considerations and tools proposed here to increase the transparency and reproducibility of study results. [ABSTRACT FROM AUTHOR]

Objective: To investigate whether herpes zoster (HZ) was associated with subsequent increased risk of dementia diagnosis. Methods: We conducted a historical cohort study using primary care electronic health records from the Clinical Practice Research Datalink in the United Kingdom. Individuals with incident HZ aged ≥40 years from 2000 to 2017 were matched with up to four individuals without HZ by age, sex, primary care practise and calendar time. The primary outcome was a new diagnosis of all‐cause dementia. We used the Cox proportional hazards regression adjusting for demographic, lifestyle and clinical confounders to assess any association between HZ and dementia. We investigated interactions with sex, frailty index and antiviral treatment and conducted various sensitivity analyses. Results: The cohort comprised 177,144 individuals with HZ and 706,901 matched unexposed individuals (median age 65 years (IQR 55.1–75.0), 40% male) followed for a median duration of 4.6 years (IQR 2.0–8.1). In total, 26,585 (3%) patients had an incident dementia diagnosis recorded and 113,056 patients died (12.8%). HZ was associated with a small reduction in dementia diagnosis (adjusted HR 0.92 (95% CI 0.89–0.95)), occurring predominantly in frail individuals and females. For patients who were fit (578,115, 65%), no association was seen (adjusted HR 0.97, 95% CI 0.92–1.02). There was no association between HZ and a composite outcome of dementia or death (adjusted HR 1.00, 95% CI 0.99–1.02). Dementia risk did not vary by prescription of antiviral agents. Sensitivity analyses showed consistent results. Interpretation: HZ was not associated with increased dementia diagnosis in a UK primary care‐based cohort. [ABSTRACT FROM AUTHOR]

We examined demographic and lifestyle risk factors for incidence of gastroesophageal reflux disease (GERD) and Barrett's esophagus (BE) in an Australian cohort of 20,975 participants aged 40–63 at recruitment (1990–1994). Information on GERD and BE was collected between 2007 and 2010. GERD symptoms were defined as self-reported heartburn or acid regurgitation. BE was defined as endoscopically confirmed columnar-lined esophagus. Risk factors for developing GERD symptoms, BE diagnosis, age at symptom onset, and age at BE diagnosis were quantified using regression. During a mean follow-up of 15.8 years, risk of GERD symptoms was 7.5% (n  = 1,318) for daily, 7.5% (n  = 1,333) for 2–6 days/week, and 4.3% (n  = 751) for 1 day/week. There were 210 (1.0%) endoscopically diagnosed BE cases, of whom 141 had histologically confirmed esophageal intestinal metaplasia. Female sex, younger age, lower socioeconomic position (SEP) and educational attainment, and former smoking were associated with higher GERD risk. Male sex and smoking were associated with earlier GERD symptom onset. Men, older participants, those with higher SEP, and former smokers were at higher BE risk. There was some evidence higher SEP was associated with earlier BE diagnosis. GERD and BE had different demographic risk factors but shared similar lifestyle factors. Earlier GERD symptom onset for men and smokers might have contributed to higher BE risk. The SEP patterns observed for GERD and BE suggest potential inequity in access to care. These findings would be important in the development of clinical risk prediction models for early detection of BE. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has disrupted healthcare activity. The NHS stopped non-urgent work in March 2020, later recommending services be restored to near-normal levels before winter where possible.Aim: To describe the volume and variation of coded clinical activity in general practice, taking respiratory disease and laboratory procedures as examples.Design and Setting: Working on behalf of NHS England, a cohort study was conducted of 23.8 million patient records in general practice, in situ using OpenSAFELY.Method: Activity using Clinical Terms Version 3 codes and keyword searches from January 2019 to September 2020 are described.Results: Activity recorded in general practice declined during the pandemic, but largely recovered by September. There was a large drop in coded activity for laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was the international normalised ratio test, with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 6.9). The pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as 'no change'. Respiratory infections exhibited a sustained drop, not returning to pre-pandemic levels by September. Asthma reviews experienced a small drop but recovered, whereas chronic obstructive pulmonary disease reviews remained below baseline.Conclusion: An open-source software framework was delivered to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September, with some important tests less affected and recording of respiratory disease codes was mixed. [ABSTRACT FROM AUTHOR]

Background: Long COVID describes new or persistent symptoms at least 4 weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were recently created.Aim: To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time.Design and Setting: Population-based cohort study in English primary care.Method: Working on behalf of NHS England, OpenSAFELY data were used encompassing 96% of the English population between 1 February 2020 and 25 May 2021. The proportion of people with a recorded code for long COVID was measured overall and by demographic factors, electronic health record software system (EMIS or TPP), and week.Results: Long COVID was recorded for 23 273 people. Coding was unevenly distributed among practices, with 26.7% of practices having never used the codes. Regional variation ranged between 20.3 per 100 000 people for East of England (95% confidence interval [CI] = 19.3 to 21.4) and 55.6 per 100 000 people in London (95% CI = 54.1 to 57.1). Coding was higher among females (52.1, 95% CI = 51.3 to 52.9) than males (28.1, 95% CI = 27.5 to 28.7), and higher among practices using EMIS (53.7, 95% CI = 52.9 to 54.4) than those using TPP (20.9, 95% CI = 20.3 to 21.4).Conclusion: Current recording of long COVID in primary care is very low, and variable between practices. This may reflect patients not presenting; clinicians and patients holding different diagnostic thresholds; or challenges with the design and communication of diagnostic codes. Increased awareness of diagnostic codes is recommended to facilitate research and planning of services, and also surveys with qualitative work to better evaluate clinicians' understanding of the diagnosis. [ABSTRACT FROM AUTHOR]

Background: Thromboembolism has been reported as a consequence of severe COVID-19. Although warfarin is a commonly used anticoagulant, it acts by antagonising vitamin K, which is low in patients with severe COVID-19. To date, the clinical evidence on the impact of regular use of warfarin on COVID-19-related thromboembolism is lacking. Methods: On behalf of NHS England, we conducted a population-based cohort study investigating the association between warfarin and COVID-19 outcomes compared with direct oral anticoagulants (DOACs). We used the OpenSAFELY platform to analyse primary care data and pseudonymously linked SARS-CoV-2 antigen testing data, hospital admissions and death records from England. We used Cox regression to estimate hazard ratios (HRs) for COVID-19-related outcomes comparing warfarin with DOACs in people with non-valvular atrial fibrillation. We also conducted negative control outcome analyses (being tested for SARS-CoV-2 and non-COVID-19 death) to assess the potential impact of confounding. Results: A total of 92,339 warfarin users and 280,407 DOAC users were included. We observed a lower risk of all outcomes associated with warfarin versus DOACs [testing positive for SARS-CoV-2, HR 0.73 (95% CI 0.68–0.79); COVID-19-related hospital admission, HR 0.75 (95% CI 0.68–0.83); COVID-19-related deaths, HR 0.74 (95% CI 0.66–0.83)]. A lower risk of negative control outcomes associated with warfarin versus DOACs was also observed [being tested for SARS-CoV-2, HR 0.80 (95% CI 0.79–0.81); non-COVID-19 deaths, HR 0.79 (95% CI 0.76–0.83)]. Conclusions: Overall, this study shows no evidence of harmful effects of warfarin on severe COVID-19 disease. [ABSTRACT FROM AUTHOR]

Background: To examine the association between circulating 25(OH)D concentrations and incidence of total hip replacement for osteoarthritis in a prospective cohort study.Methods: This study examined a random sample of 2651 participants in the Melbourne Collaborative Cohort Study who had 25(OH)D concentrations measured from dried blood spots collected in 1990-1994. Participants who underwent total hip replacement for osteoarthritis between January 2001 and December 2018 were identified by linking the cohort records to the Australian Orthopaedic Association National Joint Replacement Registry. Cox proportional hazard regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) of total hip replacement for osteoarthritis in relation to 25(OH)D concentrations, adjusted for confounders.Results: Eighty-six men and eighty-seven women had a total hip replacement for osteoarthritis. Compared with men in the lowest (1st) quartile of 25(OH)D concentration, the HR for total hip replacement was 2.32 (95% CI 1.05, 5.13) for those in the 2nd quartile, 2.77 (95% CI 1.28, 6.00) for those in the 3rd quartile, and 1.73 (95% CI 0.75, 4.02) for those in the highest quartile of 25(OH)D concentrations (p for trend 0.02). There was little evidence of an association in women.Conclusions: Higher circulating 25(OH)D concentrations were associated with an increased risk of total hip replacement for osteoarthritis in men but not in women. Although the underlying mechanism warrants further investigation, our findings highlight the need to determine the optimal levels of circulating 25(OH)D to reduce the risk of hip osteoarthritis. [ABSTRACT FROM AUTHOR]

Objective: To examine associations between diet and risk of developing gastro-oesophageal reflux disease (GERD).Design: Prospective cohort with a median follow-up of 15·8 years. Baseline diet was measured using a FFQ. GERD was defined as self-reported current or history of daily heartburn or acid regurgitation beginning at least 2 years after baseline. Sex-specific logistic regressions were performed to estimate OR for GERD associated with diet quality scores and intakes of nutrients, food groups and individual foods and beverages. The effect of substituting saturated fat for monounsaturated or polyunsaturated fat on GERD risk was examined.Setting: Melbourne, Australia.Participants: A cohort of 20 926 participants (62 % women) aged 40-59 years at recruitment between 1990 and 1994.Results: For men, total fat intake was associated with increased risk of GERD (OR 1·05 per 5 g/d; 95 % CI 1·01, 1·09; P = 0·016), whereas total carbohydrate (OR 0·89 per 30 g/d; 95 % CI 0·82, 0·98; P = 0·010) and starch intakes (OR 0·84 per 30 g/d; 95 % CI 0·75, 0·94; P = 0·005) were associated with reduced risk. Nutrients were not associated with risk for women. For both sexes, substituting saturated fat for polyunsaturated or monounsaturated fat did not change risk. For both sexes, fish, chicken, cruciferous vegetables and carbonated beverages were associated with increased risk, whereas total fruit and citrus were associated with reduced risk. No association was observed with diet quality scores.Conclusions: Diet is a possible risk factor for GERD, but food considered as triggers of GERD symptoms might not necessarily contribute to disease development. Potential differential associations for men and women warrant further investigation. [ABSTRACT FROM AUTHOR]

Aim: Modelling African great ape distribution has until now focused on current or past conditions, while future scenarios remain scarcely explored. Using an ensemble forecasting approach, we predicted changes in taxon‐specific distribution under future scenarios of climate, land use and human populations for (1) areas outside protected areas (PAs) only (assuming complete management effectiveness of PAs), (2) the entire study region and (3) interspecies range overlap. Location: Tropical Africa. Methods: We compiled occurrence data (n = 5,203) on African apes from the IUCN A.P.E.S. database and extracted relevant climate‐, habitat‐ and human‐related predictors representing current and future (2050) conditions to predict taxon‐specific range change under a best‐ and a worst‐case scenario, using ensemble forecasting. Results: The predictive performance of the models varied across taxa. Synergistic interactions between predictors are shaping African ape distribution, particularly human‐related variables. On average across taxa, a range decline of 50% is expected outside PAs under the best scenario if no dispersal occurs (61% in worst scenario). Otherwise, an 85% range reduction is predicted to occur across study regions (94% worst). However, range gains are predicted outside PAs if dispersal occurs (52% best, 21% worst), with a slight increase in gains expected across study regions (66% best, 24% worst). Moreover, more than half of range losses and gains are predicted to occur outside PAs where interspecific ranges overlap. Main Conclusions: Massive range decline is expected by 2050, but range gain is uncertain as African apes will not be able to occupy these new areas immediately due to their limited dispersal capacity, migration lag and ecological constraints. Given that most future range changes are predicted outside PAs, Africa's current PA network is likely to be insufficient for preserving suitable habitats and maintaining connected ape populations. Thus, conservation planners urgently need to integrate land use planning and climate change mitigation measures at all decision‐making levels both in range countries and abroad. [ABSTRACT FROM AUTHOR]

Aim: To investigate the association between proton pump inhibitors (PPIs) and both all‐cause and cause‐specific mortality. Methods: We conducted a cohort study using the UK Clinical Practice Research Datalink GOLD database. We compared 733 885 new users of PPIs to 124 410 new users of H2 receptor antagonists (H2Ras). In a secondary analysis we compared 689 602 PPI new users to 1 361 245 nonusers of acid suppression therapy matched on age, sex and calendar year. Hazard ratios for all‐cause and cause‐specific mortality were estimated using propensity score (PS) weighted Cox models. Results: PPI prescription was associated with increased risk of all‐cause mortality, with hazard ratios decreasing considerably by increasing adjustment (unadjusted hazard ratio [HR] 1.65, 95% confidence interval [CI] 1.62‐1.69; PS‐weighted HR 1.38, 95% CI 1.33‐1.44; high‐dimensional PS‐weighted HR 1.31, 95% CI 1.26‐1.37). Short‐term associations were observed with mortality from causes where a causal short‐term association is unexpected (eg, lung cancer mortality: PS‐weighted HR at 6 months 1.77, 95% CI 1.39‐2.25). Adjusted hazard ratios were substantially higher when compared to nonusers (PS‐weighted HR all‐cause mortality 1.96, 95% CI 1.94‐1.99) rather than H2RA users. Conclusions: PPI prescription was strongly associated with all‐cause and cause‐specific mortality. However, the change in hazard ratios (a) by increasing adjustment and (b) between comparator groups indicates that residual confounding is likely to explain the association between poor health outcomes and PPI use, and fully accounting for this using observational data may not be possible. [ABSTRACT FROM AUTHOR]

Aims: To investigate whether the introduction of minimum unit pricing (MUP) in Scotland on 1 May 2018 was reflected in changes in the likelihood of alcohol‐related queries submitted to an internet search engine, and in particular whether there was any evidence of increased interest in purchasing of alcohol from outside Scotland. Design Observational study in which individual queries to the internet Bing search engine for 2018 in Scotland and England were captured and analysed. Fluctuations over time in the likelihood of specific topic searches were examined. The patterns seen in Scotland were contrasted with those in England. Setting: Scotland and England. Participants: People who used the Bing search engine during 2018. Measurements Numbers of daily queries submitted to Bing in 2018 on eight alcohol‐related topics expressed as a proportion of queries on that day on any topic. These daily likelihoods were smoothed using a 14‐day moving average for Scotland and England separately. Findings There were substantial peaks in queries about MUP itself, cheap sources of alcohol and online alcohol outlets at the time of introduction of MUP in May 2018 in Scotland, but not England. These were relatively short‐lived. Queries related to intoxication and alcohol problems did not show a MUP peak, but were appreciably higher in Scotland than in England throughout 2018. Conclusions: Analysis of internet search engine queries appears to show that a fraction of people in Scotland may have considered circumventing minimum unit pricing in 2018 by looking for on‐line alcohol retailers. The overall higher levels of queries related to alcohol problems in Scotland compared with England mirrors the corresponding differences in alcohol consumption and harms between the countries. [ABSTRACT FROM AUTHOR]

Objectives: To assess the association between routinely prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and deaths from COVID-19 using OpenSAFELY, a secure analytical platform.Methods: We conducted two cohort studies from 1 March to 14 June 2020. Working on behalf of National Health Service England, we used routine clinical data in England linked to death data. In study 1, we identified people with an NSAID prescription in the last 3 years from the general population. In study 2, we identified people with rheumatoid arthritis/osteoarthritis. We defined exposure as current NSAID prescription within the 4 months before 1 March 2020. We used Cox regression to estimate HRs for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, accounting for age, sex, comorbidities, other medications and geographical region.Results: In study 1, we included 536 423 current NSAID users and 1 927 284 non-users in the general population. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR 0.96, 95% CI 0.80 to 1.14) in the multivariable-adjusted model. In study 2, we included 1 708 781 people with rheumatoid arthritis/osteoarthritis, of whom 175 495 (10%) were current NSAID users. In the multivariable-adjusted model, we observed a lower risk of COVID-19 related death (HR 0.78, 95% CI 0.64 to 0.94) associated with current use of NSAID versus non-use.Conclusions: We found no evidence of a harmful effect of routinely prescribed NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about the routine therapeutic use of NSAIDs. [ABSTRACT FROM AUTHOR]

Chemokines are small proteins that promote leukocyte migration during development, infection, and inflammation. We and others isolated the unique chemokine CCL21, a potent chemo-attractant for naïve T-cells, naïve B-cells, and immature dendritic cells. CCL21 has a 37 amino acid carboxy terminal extension that is distinct from the rest of the chemokine family, which is thought to anchor it to venule endothelium where the amino terminus can interact with its cognate receptor, CCR7. We and others have reported that venule endothelium expressing CCL21 plays a crucial role in attracting naïve immune cells to sites of antigen presentation. In this study we generated a series of monoclonal antibodies to the amino terminus of CCL21 in an attempt to generate an antibody that blocked the interaction of CCL21 with its receptor CCR7. We found one humanized clone that blocked naïve T-cell migration towards CCL21, while memory effector T-cells were less affected. Using this monoclonal antibody, we also demonstrated that CCL21 is expressed in the mucosal venule endothelium of the large majority of inflammatory bowel diseases (IBD), including Crohn's disease, ulcerative colitis, and also in celiac disease. This expression correlated with active IBD in 5 of 6 cases, whereas none of 6 normal bowel biopsies had CCL21 expression. This study raises the possibility that this monoclonal antibody could be used to diagnose initial or recurrent of IBD. Significantly, this antibody could also be used for therapeutic intervention in IBD by selectively interfering with recruitment of naïve immune effector cells to sites of antigen presentation, without harming overall memory immunity. [ABSTRACT FROM AUTHOR]