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BACKGROUND: Deferrals due to low hemoglobin are time-consuming and costly for blood donors and donation services. Furthermore, accepting donations from those with low hemoglobin could represent a significant safety issue. One approach to reduce them is to use hemoglobin concentration alongside donor characteristics to inform personalized inter-donation intervals. STUDY DESIGN AND METHODS: We used data from 17,308 donors to inform a discrete event simulation model comparing personalized inter-donation intervals using "post-donation" testing (i.e., estimating current hemoglobin from that measured by a hematology analyzer at last donation) versus the current approach in England (i.e., pre-donation testing with fixed intervals of 12-weeks for men and 16-weeks for women). We reported the impact on total donations, low hemoglobin deferrals, inappropriate bleeds, and blood service costs. Personalized inter-donation intervals were defined using mixed-effects modeling to estimate hemoglobin trajectories and probability of crossing hemoglobin donation thresholds. RESULTS: The model had generally good internal validation, with predicted events similar to those observed. Over 1 year, a personalized strategy requiring ≥90% probability of being over the hemoglobin threshold, minimized adverse events (low hemoglobin deferrals and inappropriate bleeds) in both sexes and costs in women. Donations per adverse event improved from 3.4 (95% uncertainty interval 2.8, 3.7) under the current strategy to 14.8 (11.6, 19.2) in women, and from 7.1 (6.1, 8.5) to 26.9 (20.8, 42.6) in men. In comparison, a strategy incorporating early returns for those with high certainty of being over the threshold maximized total donations in both men and women, but was less favorable in terms of adverse events, with 8.4 donations per adverse event in women (7.0, 10,1) and 14.8 (12.1, 21.0) in men. DISCUSSION: Personalized inter-donation intervals using post-donation testing combined with modeling of hemoglobin trajectories can help reduce deferrals, inappropriate bleeds, and costs.

BackgroundThe link between ethnicity and healthcare inequity, and the urgency for better data is well-recognised. This study describes ethnicity data in nation-wide electronic health records in England, UK.MethodsWe conducted a retrospective cohort study using de-identified person-level records for the England population available in the National Health Service (NHS) Digital trusted research environment. Primary care records (GDPPR) were linked to hospital and national mortality records. We assessed completeness, consistency, and granularity of ethnicity records using all available SNOMED-CT concepts for ethnicity and NHS ethnicity categories.FindingsFrom 61.8 million individuals registered with a primary care practice in England, 51.5 (83.3%) had at least one ethnicity record in GDPPR, increasing to 93·9% when linked with hospital records. Approximately 12·0% had at least two conflicting ethnicity codes in primary care records. Women were more likely to have ethnicity recorded than men. Ethnicity was missing most frequently in individuals from 18 to 39 years old and in the southern regions of England. Individuals with an ethnicity record had more comorbidities recorded than those without. Of 489 SNOMED-CT ethnicity concepts available, 255 were used in primary care records. Discrepancies between SNOMED-CT and NHS ethnicity categories were observed, specifically within “Other-” ethnicity groups.InterpretationMore than 250 ethnicity sub-groups may be found in health records for the English population, although commonly categorised into “White”, “Black”, “Asian”, “Mixed”, and “Other”. One in ten individuals do not have ethnicity information recorded in primary care or hospital records. SNOMED-CT codes represent more diversity in ethnicity groups than the NHS ethnicity classification. Improved recording of self-reported ethnicity at first point-of-care and consistency in ethnicity classification across healthcare settings can potentially improve the accuracy of ethnicity in research and ultimately care for all ethnicities.FundingBritish Heart Foundation Data Science Centre led by Health Data Research UK.Research in contextEvidence before this studyEthnicity has been highlighted as a significant factor in the disproportionate impact of SARS-CoV-2 infection and mortality. Better knowledge of ethnicity data recorded in real clinical practice is required to improve health research and ultimately healthcare. We searched PubMed from database inception to 14thJuly 2022 for publications using the search terms “ethnicity” and “electronic health records” or “EHR,” without language restrictions. 228 publications in 2019, before the COVID-19 pandemic, and 304 publications between 2020 and 2022 were identified. However, none of these publications used or reported any of over 400 available SNOMED-CT concepts for ethnicity to account for more granularity and diversity than captured by traditional high-level classification limited to 5 to 9 ethnicity groups.Added value of this studyWe provide a comprehensive study of the largest collection of ethnicity records from a national-level electronic health records trusted research environment, exploring completeness, consistency, and granularity. This work can serve as a data resource profile of ethnicity from routinely-collected EHR in England.Implications of all the available evidenceTo achieve equity in healthcare, we need to understand the differences between individuals, as well as the influence of ethnicity both on health status and on health interventions, including variation in the behaviour of tests and therapies. Thus, there is a need for measurements, thresholds, and risk estimates to be tailored to different ethnic groups. This study presents the different medical concepts describing ethnicity in routinely collected data that are readily available to researchers and highlights key elements for improving their accuracy in research. We aim to encourage researchers to use more granular ethnicity than the than typical approaches which aggregate ethnicity into a limited number of categories, failing to reflect the diversity of underlying populations. Accurate ethnicity data will lead to a better understanding of individual diversity, which will help to address disparities and influence policy recommendations that can translate into better, fairer health for all.

How behavior arises from brain physiology has been one central topic of investigation in neuroscience. Considering the recent interest in predicting behavior from brain imaging using open datasets, there is the need for a principled approach to the categorization of behavioral variables. However, this is not trivial, as the definitions of psychological constructs and their relationships—their ontology—are not always clear. Here, we propose to use exploratory factor analysis (EFA) as a data-driven approach to find robust and interpretable domains of behavior in the Human Connectome Project (HCP) dataset. Additionally, we explore the clustering of behavioral variables using consensus clustering. We find that four and five factors offer the best description of the data, a result corroborated by the consensus clustering. In the four-factor solution, factors for Mental Health, Cognition, Processing Speed, and Substance Use arise. With five factors, Mental Health splits into Well-Being and Internalizing. Clustering results show a similar pattern, with clusters for Cognition, Processing Speed, Positive Affect, Negative Affect, and Substance Use. The factor structure is replicated in an independent dataset using confirmatory factor analysis (CFA). We discuss how the content of the factors fits with previous conceptualizations of general behavioral domains.

Behavioral research has extensively documented the impact of affective states on cognitive control. Despite increasing interest in investigating how affect and emotion influence cognition, the functional neural architecture mediating these effects remains unresolved. Here, we examined how changes in brain network dynamics elicited by negative emotions modulate the subsequent recruitment of attentional processes at behavioral and neural levels. We collected fMRI BOLD activity in healthy humans during three sequential conditions (naturalistic movie watching, resting state, and cognitive control task) in either neutral or negative emotion contexts. We assessed fMRI data by using co-activation patterns (CAPs) analysis to characterize dynamic functional connectivity within whole-brain networks across experimental conditions, and then applied structural equation modelling to uncover their functional relationships. We found that neural markers of cognitive control (FPN) were modulated by prior occurrences of distinct activity patterns after negative emotions, involving (1) the salience (SN) and sensorimotor (SMN) networks during the emotion-eliciting event itself, and (2) the default mode (DMN), salience (SN), and sensorimotor (SMN) networks in a resting period following emotional elicitation. Further, these neural interactions were related to concomitant changes in behavioral measures of cognitive control after negative emotion. Altogether, our results provide new insights into the brain dynamic functional organization supporting high-order cognitive processing and its regulation by negative emotions.

We describe our analyses of data from over 49.7 million people in England, representing near-complete coverage of the relevant population, to assess the risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccination. A self-controlled case series (SCCS) design has previously reported increased risk of myocarditis after first ChAdOx1, BNT162b2, and mRNA-1273 dose and after second doses of mRNA COVID-19 vaccines in England. Here, we use a cohort design to estimate hazard ratios for hospitalised or fatal myocarditis/pericarditis after first and second doses of BNT162b2 and ChAdOx1 vaccinations. SCCS and cohort designs are subject to different assumptions and biases and therefore provide the opportunity for triangulation of evidence. In contrast to the findings from the SCCS approach previously reported for England, we found evidence for lower incidence of hospitalised or fatal myocarditis/pericarditis after first ChAdOx1 and BNT162b2 vaccination, as well as little evidence to suggest higher incidence of these events after second dose of either vaccination.

Older adults undergoing emergency abdominal surgery have significantly poorer outcomes than younger adults. For those who survive, the level of care required on discharge from hospital is unknown and such information could guide decision-making. The ELF (Emergency Laparotomy and Frailty) study aimed to determine whether preoperative frailty in older adults was associated with increased dependence at the time of discharge.The ELF study was a UK-wide multicentre prospective cohort study of older patients (65 years or more) undergoing emergency laparotomy during March and June 2017. The objective was to establish whether preoperative frailty was associated with increased care level at discharge compared with preoperative care level. The analysis used a multilevel logistic regression adjusted for preadmission frailty, patient age, sex and care level.A total of 934 patients were included from 49 hospitals. Mean(s.d.) age was 76·2(6·8) years, with 57·6 per cent women; 20·2 per cent were frail. Some 37·4 per cent of older adults had an increased care level at discharge. Increasing frailty was associated with increased discharge care level, with greater predictive power than age. The adjusted odds ratio for an increase in care level was 4·48 (95 per cent c.i. 2·03 to 9·91) for apparently vulnerable patients (Clinical Frailty Score (CFS) 4), 5·94 (2·54 to 13·90) for those mildly frail (CFS 5) and 7·88 (2·97 to 20·79) for those moderately or severely frail (CFS 6 or 7), compared with patients who were fit.Over 37 per cent of older adults undergoing emergency laparotomy required increased care at discharge. Frailty scoring was a significant predictor, and should be integrated into all acute surgical units to aid shared decision-making and discharge planning.Los adultos mayores sometidos a cirugía abdominal de urgencia tienen resultados significativamente peores que los adultos jóvenes. Para aquellos pacientes que sobreviven, el nivel de atención que requieren tras el alta hospitalaria se desconoce y esta información podría servir de guía en la toma de decisiones. El estudio ELF (Emergency Laparotomy and Frailty) tenía como objetivo determinar si la fragilidad preoperatoria en adultos mayores se asociaba con un aumento de la dependencia en el momento del alta. MÉTODOS: El estudio ELF era un estudio multicéntrico extenso efectuado en el Reino Unido (n = 49) que incluyó una cohorte prospectiva de 934 pacientes mayores ( 65 años) sometidos a laparotomía de urgencia durante marzo-junio de 2017. El objetivo fue establecer si la fragilidad preoperatoria aumentaba el nivel de asistencia en el momento del alta en comparación con el nivel de asistencia preoperatorio. Para el análisis se utilizó una regresión logística multinivel ajustada a características previas al ingreso: fragilidad, edad del paciente, género, y nivel de asistencia.La edad media de los pacientes fue 76,2 años (DE = 6,83), con un 57% de mujeres, un 20,2% de pacientes frágiles y un 37,4% de adultos mayores que presentaron un aumento en el nivel de asistencia en el momento del alta. Un aumento de la fragilidad se asoció con un incremento en el nivel de asistencia en el momento del alta (y mayor poder predictivo que la edad). La razón de oportunidades (odds ratio, OR) ajustada por el aumento del nivel de asistencia fue 4,48 (i.c. del 95% 2,03-9,91) para pacientes aparentemente vulnerables (Clinical Frailty Scale, CFS 4); 5,94 (i.c. del 95% 2,54-13,90) para aquellos ligeramente frágiles (CFS 5); y 7,88 (i.c. del 95% 2,97-20,79) para aquellos con fragilidad moderada o grave (CFS 6 and 7) en comparación con pacientes en buenas condiciones. CONCLUSIÓN: Este es el primer estudio que documenta que más del 37% de adultos mayores sometidos a laparotomía de urgencia precisaron un aumento en el nivel de asistencia en el momento del alta. La evaluación de la fragilidad debería integrarse en todas las unidades quirúrgicas de agudos para ayudar a compartir la toma de decisiones y los planes de tratamiento.

Background: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a prothrombotic state, but long-term effects of COVID-19 on incidence of vascular diseases are unclear. Methods: We studied vascular diseases after COVID-19 diagnosis in population-wide anonymized linked English and Welsh electronic health records from January 1 to December 7, 2020. We estimated adjusted hazard ratios comparing the incidence of arterial thromboses and venous thromboembolic events (VTEs) after diagnosis of COVID-19 with the incidence in people without a COVID-19 diagnosis. We conducted subgroup analyses by COVID-19 severity, demographic characteristics, and previous history. Results: Among 48 million adults, 125 985 were hospitalized and 1 319 789 were not hospitalized within 28 days of COVID-19 diagnosis. In England, there were 260 279 first arterial thromboses and 59 421 first VTEs during 41.6 million person-years of follow-up. Adjusted hazard ratios for first arterial thrombosis after COVID-19 diagnosis compared with no COVID-19 diagnosis declined from 21.7 (95% CI, 21.0–22.4) in week 1 after COVID-19 diagnosis to 1.34 (95% CI, 1.21–1.48) during weeks 27 to 49. Adjusted hazard ratios for first VTE after COVID-19 diagnosis declined from 33.2 (95% CI, 31.3–35.2) in week 1 to 1.80 (95% CI, 1.50–2.17) during weeks 27 to 49. Adjusted hazard ratios were higher, for longer after diagnosis, after hospitalized versus nonhospitalized COVID-19, among Black or Asian versus White people, and among people without versus with a previous event. The estimated whole-population increases in risk of arterial thromboses and VTEs 49 weeks after COVID-19 diagnosis were 0.5% and 0.25%, respectively, corresponding to 7200 and 3500 additional events, respectively, after 1.4 million COVID-19 diagnoses. Conclusions: High relative incidence of vascular events soon after COVID-19 diagnosis declines more rapidly for arterial thromboses than VTEs. However, incidence remains elevated up to 49 weeks after COVID-19 diagnosis. These results support policies to prevent severe COVID-19 by means of COVID-19 vaccines, early review after discharge, risk factor control, and use of secondary preventive agents in high-risk patients.

Background Thromboses in unusual locations after the Coronavirus Disease 2019 (COVID-19) vaccine ChAdOx1-S have been reported, although their frequency with vaccines of different types is uncertain at a population level. The aim of this study was to estimate the population-level risks of hospitalised thrombocytopenia and major arterial and venous thromboses after COVID-19 vaccination. Methods and findings In this whole-population cohort study, we analysed linked electronic health records from adults living in England, from 8 December 2020 to 18 March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous, and thrombocytopenic outcomes 1 to 28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages 2, sex, ethnicity, and deprivation. We also prespecified adjustment for anticoagulant medication, combined oral contraceptive medication, hormone replacement therapy medication, history of pulmonary embolism or deep vein thrombosis, and history of coronavirus infection in analyses of venous thrombosis; and diabetes, hypertension, smoking, antiplatelet medication, blood pressure lowering medication, lipid lowering medication, anticoagulant medication, history of stroke, and history of myocardial infarction in analyses of arterial thromboses. We selected further covariates with backward selection. Of 46 million adults, 23 million (51%) were women; 39 million (84%) were The crude incidence rates (per 100,000 person-years) of all venous events were as follows: prevaccination, 140 [95% confidence interval (CI): 138 to 142]; ≤28 days post-ChAdOx1-S, 294 (281 to 307); >28 days post-ChAdOx1-S, 359 (338 to 382), ≤28 days post-BNT162b2-S, 241 (229 to 253); >28 days post-BNT162b2-S 277 (263 to 291). The crude incidence rates (per 100,000 person-years) of all arterial events were as follows: prevaccination, 546 (95% CI: 541 to 555); ≤28 days post-ChAdOx1-S, 1,211 (1,185 to 1,237); >28 days post-ChAdOx1-S, 1678 (1,630 to 1,726), ≤28 days post-BNT162b2-S, 1,242 (1,214 to 1,269); >28 days post-BNT162b2-S, 1,539 (1,507 to 1,572). Adjusted HRs (aHRs) 1 to 28 days after ChAdOx1-S, compared with unvaccinated rates, at ages Rates of intracranial venous thrombosis (ICVT) and of thrombocytopenia in adults aged The main limitations of the study are as follows: (i) it relies on the accuracy of coded healthcare data to identify exposures, covariates, and outcomes; (ii) the use of primary reason for hospital admission to measure outcome, which improves the positive predictive value but may lead to an underestimation of incidence; and (iii) potential unmeasured confounding. Conclusions In this study, we observed increases in rates of ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy for 249 circulating metabolites, lipids, and lipoprotein sub-fractions has recently become available in UK Biobank for approximately 121,657 participants. Here, we describe procedures for quality control and removal of technical variation for this biomarker data. We show that technical and biological effects with linear effects on individual biomarkers can combine in a non-linear fashion on (the 61) composite biomarkers and (81) biomarker ratios, and thus composite biomarkers and ratios should be re-derived after removal of unwanted variation to avoid introducing such cryptic effects. We make available an R package, ukbnmr, for extracting the metabolic biomarker data from UK Biobank and removing the unwanted technical variation. We also make available code for re-deriving the 61 composite biomarkers and 81 ratios, and for further derivation of 76 additional biomarker ratios of potential biological significance. Finally, we demonstrate that our removal of technical variation leads to increased signal for genetic and epidemiological studies of the NMR metabolic biomarkers in UK Biobank.

BACKGROUND Although the burden of premature myocardial infarction (MI) is high in Malaysia, direct evidence on the determinants of MI in this multi-ethnic population remains sparse. OBJECTIVE The Malaysian Acute Vascular Events Risk (MAVERIK) study is a retrospective case-control study established to investigate the genomic, lipid-related, and other determinants of acute MI in Malaysia. In this paper, we report the study protocol and early results. METHODS By June 2019, we had enrolled approximately 2500 patients with their first MI and 2500 controls without cardiovascular disease, who were frequency-matched by age, sex, and ethnicity, from 17 hospitals in Malaysia. For each participant, serum and whole blood have been collected and stored. Clinical, demographic, and behavioral information has been obtained using a 200-item questionnaire. RESULTS Tobacco consumption, a history of diabetes, hypertension, markers of visceral adiposity, indicators of lower socioeconomic status, and a family history of coronary disease were more prevalent in cases than in controls. Adjusted (age and sex) logistic regression models for traditional risk factors indicated that current smoking (odds ratio [OR] 4.11, 95% CI 3.56-4.75; PP=.001), a history of high blood pressure (OR 2.13, 95% CI 1.86-2.44; PPP=.009), and obesity (BMI >30 kg/m2; OR 1.19, 95% CI 1.05-1.34; P=.009) were associated with MI in age- and sex-adjusted models. CONCLUSIONS The MAVERIK study can serve as a useful platform to investigate genetic and other risk factors for MI in an understudied Southeast Asian population. It should help to hasten the discovery of disease-causing pathways and inform regionally appropriate strategies that optimize public health action. INTERNATIONAL REGISTERED REPORT RR1-10.2196/31885

Geostrophic eddies contribute to the mixing of heat, carbon, and other climatically important tracers. A passive tracer driven by satellite-derived surface velocity fields is used to study the regional and temporal variability of lateral eddy mixing in the North Atlantic. Using a quasi-Lagrangian diffusivity diagnostic, we show that the upstream region (80°–50°W) of the Gulf Stream jet exhibits a significant mixing barrier (with diffusivity of ≈1 × 103 m2 s−1), compared to the downstream region (50°–10°W), which displays no mixing suppression (≈10 × 103 m2 s−1). The interannual variability is 10%–20% of the time mean in both regions. By analyzing linear perturbations of mixing-length diffusivity expression, we show that the across-jet mixing in the upstream region is driven by variations in the mean flow, rather than eddy velocity. In the downstream region, both the mean flow and eddy velocity contribute to the temporal variability. Our results suggest that an eddy parameterization must take into account the along-jet variation of mixing, and within jets such diffusivities may be a simple function of jet strength.

The brushing of hair requires a complex understanding of the interaction between soft hair fibers and the soft brushing device. It is also reliant on having both visual and tactile information. Guided by a recently developed model of soft tangled fiber bundles, we develop a method for optimizing hair brushing by robots which seeks to minimize pain and avoid the build up of jammed entanglements. Using an experimental setup with a custom force measuring sensor and a soft brush end effector, we perform closed-loop experiments on hair brushing of different curliness. This utilizes computer vision to assess the curliness of the hair, after which the hair is brushed using a closed loop controller. To demonstrate this approach hair brushing experiments have been performed on a wide variety of wigs with amount of curl. In addition to hair brushing the insight provided by this model driven approach could be applied to brushing of fibers for textiles, or animal fibers. © 2021 IEEE.

SUMMARYObjectiveTo compare four haemoglobin measurement methods in whole blood donors.BackgroundTo safeguard donors, blood services measure haemoglobin concentration in advance of each donation. NHS Blood and Transplant’s (NHSBT) usual method has been capillary gravimetry (copper sulphate), followed by venous HemoCue® (spectrophotometry) for donors failing gravimetry. However, gravimetry/venous HemoCue® results in 10% of donors being inappropriately bled (i.e., with haemoglobin values below the regulatory threshold).MethodsThe following were compared in 21,840 blood donors (aged ≥18 years) recruited from 10 mobile centres of NHSBT in England, with each method compared with the Sysmex XN-2000 haematology analyser, the reference standard: 1) gravimetry/venous HemoCue®; 2) “post donation” approach, i.e., estimating current haemoglobin concentration from that measured by a haematology analyser at a donor’s most recent prior donation; 3) capillary HemoCue®; and 4) non-invasive spectrometry (MBR Haemospect® or Orsense NMB200®). We assessed each method for sensitivity; specificity; proportion of donors who would have been inappropriately bled, or rejected from donation (“deferred”) incorrectly; and test preference.ResultsCompared with the reference standard, the methods ranged in test sensitivity from 17.0% (MBR Haemospect®) to 79.0% (HemoCue®) in men, and from 19.0% (MBR Haemospect®) to 82.8% (HemoCue®) in women. For specificity, the methods ranged from 87.2% (MBR Haemospect®) to 99.9% (gravimetry/venous HemoCue®) in men, and from 74.1% (Orsense NMB200®) to 99.8% (gravimetry/venous HemoCue®) in women. The proportion of donors who would have been inappropriately bled ranged from 2.2% in men for HemoCue® to 18.9% in women for MBR Haemospect®. The proportion of donors who would have been deferred incorrectly with haemoglobin concentration above the minimum threshold ranged from 0.1% in men for gravimetry/venous HemoCue® to 20.3% in women for OrSense®. Most donors preferred non-invasive spectrometry.ConclusionIn the largest study reporting head-to-head comparisons of four methods to measure haemoglobin prior to blood donation, our results support replacement of venous HemoCue® with the capillary HemoCue® when donors fail gravimetry. These results have had direct translational implications for NHS Blood and Transplant in England.

The resolution of climate models is limited by computational cost. Therefore, we must rely on parameterizations to represent processes occurring below the scale resolved by the models. Here, we foc...

Blood donors attending a donation session may be deferred from donating blood due to a failure to meet low hemoglobin (Hb) thresholds. This costs the blood donor service and donors valuable time and resources. In addition, donors who are deferred may have more symptoms, and as a direct and/or indirect effect of their experience, return rates of donors deferred for low Hb are reduced, even in repeat donors. It is therefore vital that low Hb deferral (LHD) is minimized. The aim of this updated systematic review is to expand the evidence base for factors which affect a donor's risk of deferral due to low Hb. Studies were identified by searching MEDLINE, Embase, The Cochrane Library, and the WHO International Clinical Trials Registry to March 2019. Demographic data, donor history, hematological/biological factors, and the primary outcome of deferral due to low Hb were extracted. Our primary outcome was deferral due to low Hb. Analyses were descriptive and quantitative; pooled odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by meta-analysis using random-effects models. A total of 116 studies met the inclusion criteria. Meta-analysis showed a significantly greater risk of LHD in females compared with males in studies applying universal Hb thresholds for males and females (OR 14.62 95% CI 12.43-17.19) and in those which used sex-specific thresholds (OR 5.73, 95% CI 4.36-7.53). Higher rates of LHD were also associated with increasing age in men, low body weight, shorter interdonation interval, donors of Hispanic or African descent, higher ambient temperature, donors with low ferritin levels, and donation in a fixed donor center. There was conflicting evidence on the effect of new and repeat donor status, and blood group. This work has strengthened the evidence of the previous review in identifying factors that should be considered in studies of donor deferral and highlighting areas in need of further study, including ABO and Rh blood groups, previous platelet donation, diet, smoking, time of day, and genetic data. These factors may lead to individually tailored donation criteria for safe and efficient donation in the future., This research is supported by core funding from NHS Blood and Transplant, the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre Programme (SF, CD), the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), and the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust]. AB, TB, and KM are funded by the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). SAR is funded by the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust].

BACKGROUND: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease.METHODS: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose–response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th–95th percentile 1·04–13·5]) from 71 011 participants from 37 studies.FINDINGS: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10–1·17), coronary disease excluding myocardial infarction (1·06, 1·00–1·11), heart failure (1·09, 1·03–1·15), fatal hypertensive disease (1·24, 1·15–1·33); and fatal aortic aneurysm (1·15, 1·03–1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91–0·97). In comparison to those who reported drinking >0–≤100 g per week, those who reported drinking >100–≤200 g per week, >200–≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1–2 years, or 4–5 years, respectively.INTERPRETATION: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.FUNDING: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.

Urban design and planning are increasingly geared toward increasing density, viewed by many as a way of achieving socio-economic and environmental sustainability. The quantitative measurement of density from the building-level to the area-level presents a challenge to practitioners. This paper demonstrates a new measure, Space Ratio, for the purposes of measuring and mapping the density potential of buildings and areas in London. Space Ratio describes the ratio of the existing density to the permissible density. It is a multi-variable tool that can potentially incorporate a range of measures of building, people or perceived density. Space Ratio can be utilised to test multiple density measures and scenarios. A tool for visualising density potentials, the ‘Space Ratio Chart’, has also been illustrated as part of this study. Drawing on three-dimensional data on building density and several upward density scenarios, Space Ratio has been measured and mapped in the London case study areas of Balham and Kensington. Although Space Ratio and the Space Ratio Chart are contingent on high-quality data, this study argues that they could aide the design and scenario planning of sustainable densification.

Summary Background The INTERVAL trial showed that, over a 2-year period, inter-donation intervals for whole blood donation can be safely reduced to meet blood shortages. We extended the INTERVAL trial for a further 2 years to evaluate the longer-term risks and benefits of varying inter-donation intervals, and to compare routine versus more intensive reminders to help donors keep appointments. Methods The INTERVAL trial was a parallel group, pragmatic, randomised trial that recruited blood donors aged 18 years or older from 25 static donor centres of NHS Blood and Transplant across England, UK. Here we report on the prespecified analyses after 4 years of follow-up. Participants were whole blood donors who agreed to continue trial participation on their originally allocated inter-donation intervals (men: 12, 10, and 8 weeks; women: 16, 14, and 12 weeks). They were further block-randomised (1:1) to routine versus more intensive reminders using computer-generated random sequences. The prespecified primary outcome was units of blood collected per year analysed in the intention-to-treat population. Secondary outcomes related to safety were quality of life, self-reported symptoms potentially related to donation, haemoglobin and ferritin concentrations, and deferrals because of low haemoglobin and other factors. This trial is registered with ISRCTN, number ISRCTN24760606, and has completed. Findings Between Oct 19, 2014, and May 3, 2016, 20 757 of the 38 035 invited blood donors (10 843 [58%] men, 9914 [51%] women) participated in the extension study. 10 378 (50%) were randomly assigned to routine reminders and 10 379 (50%) were randomly assigned to more intensive reminders. Median follow-up was 1·1 years (IQR 0·7–1·3). Compared with routine reminders, more intensive reminders increased blood collection by a mean of 0·11 units per year (95% CI 0·04–0·17; p=0·0003) in men and 0·06 units per year (0·01–0·11; p=0·0094) in women. During the extension study, each week shorter inter-donation interval increased blood collection by a mean of 0·23 units per year (0·21–0·25) in men and 0·14 units per year (0·12–0·15) in women (both p0.0001 for tests of linear trend by inter-donation intervals) other than a higher reported frequency of doctor-diagnosed low iron concentrations and prescription of iron supplements in men (p

Population forecasting, in which past dynamics are used to make predictions of future state, has many real-world applications. While time series of animal abundance are often modeled in ways that aim to capture the underlying biological processes involved, doing so is neither necessary nor sufficient for making good predictions. Here we report on a data science competition focused on modelling time series of Antarctic penguin abundance. We describe the best performing submitted models and compare them to a Bayesian model previously developed by domain experts and build an ensemble model that outperforms the individual component models in prediction accuracy. The top performing models varied tremendously in model complexity, ranging from very simple forward extrapolations of average growth rate to ensembles of models integrating recently developed machine learning techniques. Despite the short time frame for the competition, four of the submitted models outperformed the model previously created by the team of domain experts. We discuss the structure of the best performing models and components therein that might be useful for other ecological applications, the benefit of creating ensembles of models for ecological prediction, and the costs and benefits of including detailed domain expertise in ecological modelling. Additionally, we discuss the benefits of data science competitions, among which are increased visibility for challenging science questions, the generation of new techniques not yet adopted within the ecological community, and the ability to generate ensemble model forecasts that directly address model uncertainty.

Summary Background Limits on the frequency of whole blood donation exist primarily to safeguard donor health. However, there is substantial variation across blood services in the maximum frequency of donations allowed. We compared standard practice in the UK with shorter inter-donation intervals used in other countries. Methods In this parallel group, pragmatic, randomised trial, we recruited whole blood donors aged 18 years or older from 25 centres across England, UK. By use of a computer-based algorithm, men were randomly assigned (1:1:1) to 12-week (standard) versus 10-week versus 8-week inter-donation intervals, and women were randomly assigned (1:1:1) to 16-week (standard) versus 14-week versus 12-week intervals. Participants were not masked to their allocated intervention group. The primary outcome was the number of donations over 2 years. Secondary outcomes related to safety were quality of life, symptoms potentially related to donation, physical activity, cognitive function, haemoglobin and ferritin concentrations, and deferrals because of low haemoglobin. This trial is registered with ISRCTN, number ISRCTN24760606, and is ongoing but no longer recruiting participants. Findings 45 263 whole blood donors (22 466 men, 22 797 women) were recruited between June 11, 2012, and June 15, 2014. Data were analysed for 45 042 (99·5%) participants. Men were randomly assigned to the 12-week (n=7452) versus 10-week (n=7449) versus 8-week (n=7456) groups; and women to the 16-week (n=7550) versus 14-week (n=7567) versus 12-week (n=7568) groups. In men, compared with the 12-week group, the mean amount of blood collected per donor over 2 years increased by 1·69 units (95% CI 1·59–1·80; approximately 795 mL) in the 8-week group and by 0·79 units (0·69–0·88; approximately 370 mL) in the 10-week group (p

BackgroundIdentifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. We tested (1) whether ML techniques based on a state-of-the-art automated ML framework (AutoPrognosis) could improve CVD risk prediction compared to traditional approaches, and (2) whether considering non-traditional variables could increase the accuracy of CVD risk predictions.Methods and findingsUsing data on 423,604 participants without CVD at baseline in UK Biobank, we developed a ML-based model for predicting CVD risk based on 473 available variables. Our ML-based model was derived using AutoPrognosis, an algorithmic tool that automatically selects and tunes ensembles of ML modeling pipelines (comprising data imputation, feature processing, classification and calibration algorithms). We compared our model with a well-established risk prediction algorithm based on conventional CVD risk factors (Framingham score), a Cox proportional hazards (PH) model based on familiar risk factors (i.e, age, gender, smoking status, systolic blood pressure, history of diabetes, reception of treatments for hypertension and body mass index), and a Cox PH model based on all of the 473 available variables. Predictive performances were assessed using area under the receiver operating characteristic curve (AUC-ROC). Overall, our AutoPrognosis model improved risk prediction (AUC-ROC: 0.774, 95% CI: 0.768-0.780) compared to Framingham score (AUC-ROC: 0.724, 95% CI: 0.720-0.728, p < 0.001), Cox PH model with conventional risk factors (AUC-ROC: 0.734, 95% CI: 0.729-0.739, p < 0.001), and Cox PH model with all UK Biobank variables (AUC-ROC: 0.758, 95% CI: 0.753-0.763, p < 0.001). Out of 4,801 CVD cases recorded within 5 years of baseline, AutoPrognosis was able to correctly predict 368 more cases compared to the Framingham score. Our AutoPrognosis model included predictors that are not usually considered in existing risk prediction models, such as the individuals' usual walking pace and their self-reported overall health rating. Furthermore, our model improved risk prediction in potentially relevant sub-populations, such as in individuals with history of diabetes. We also highlight the relative benefits accrued from including more information into a predictive model (information gain) as compared to the benefits of using more complex models (modeling gain).ConclusionsOur AutoPrognosis model improves the accuracy of CVD risk prediction in the UK Biobank population. This approach performs well in traditionally poorly served patient subgroups. Additionally, AutoPrognosis uncovered novel predictors for CVD disease that may now be tested in prospective studies. We found that the "information gain" achieved by considering more risk factors in the predictive model was significantly higher than the "modeling gain" achieved by adopting complex predictive models.

Objectives To measure the effects of short-term high oxygen-transmissible (Dk) soft and rigid contact lens wear and eye rubbing on basal epithelial appearance and epithelial thickness. Methods Ten subjects were enrolled in a randomized crossover study. The subjects' left eye was used as a control, and the right eye either wore a high Dk soft lens, high Dk parallel fitted rigid gas-permeable lens, or was rubbed on 3 separate days. Epithelial basal cell regularity and central and peripheral epithelial thickness were assessed before and after 6-hr soft or rigid lens wear or 10-min rubbing using in vivo confocal microscopy and modified optical pachometry. Results Basal cell regularity was unaffected by short-term lens wear or eye rubbing (Friedman Test, P=0.11 and 0.37 in test and control eyes, respectively). The peripheral epithelium was thicker than the central epithelium (repeated-measures analysis of variance, P=0.03) but remained unaffected by short-term lens wear or eye rubbing (repeated-measures analysis of variance, P>0.05, power Conclusions Corneal epithelial thickness and basal cell morphology were not affected by short-term lens wear or eye rubbing in this pilot study.

Following cataract surgery, entrapment of the iris within the surgical wound is often managed by intensive use of miotics. As the radial fibres stretch, only a small amount of fraction is exerted upon the entrapped iris. Application of a combination of phenylephrine and pilocarpine drops causes simultaneous contraction of the pupil sphincter and the radial muscle fibres. This study investigated the relative magnitude of forces induced in the iris periphery by pilocarpine and phenylephrine and the effectiveness of adding g. phenylephrine 10% to g. pilocarpine 4% drops in the treatment of postoperative irido-corneal adhesions. The investigation was divided into two parts. First, the forces induced in the iris periphery upon exposure to pilocarpine and phenylephrine were measured in 6 cadaver irises. The mean force was 27.5 +/- 5.7 x 10(-3) N for pilocarpine and 23.3 +/- 4.0 x 10(-3) N for phenylephrine. The combination of the two drugs produced a force of 54.2 +/- 6.6 x 10(-3) N (p0.05). In the second part of the study intensive pilocarpine 4% drops were administered to 17 patients who had iris-wound entrapment on the first post-operative day. Patients with persistent adhesion were commenced on intensive g. phenylephrine 10% and assessed after 90 minutes. Of the 17 patients, 6 responded to pilocarpine drops alone; in a further 7 the irido-corneal adhesion was released only by the addition of phenylephrine drops, and in 4 patients drops were ineffective in relieving the adhesion. This study indicates that addition of phenylephrine 10% to pilocarpine 4% drops enhances the effectiveness of pharmacological treatment of post-operative irido-corneal adhesion.

Chronic patellar tendinitis can be a frustrating diagnostic and therapeutic problem. This report evaluates seven tendons in five patients with chronic patellar tendinitis. The etiologies included "jumper's knee" and Osgood-Schlatter disease. In all cases magnetic resonance images (MRI) showed thickening of the tendon. Some of the tendons had focal areas of thickening which helped establish the etiology. All cases had intratendinous areas of increased signal which, in four cases, proved to be chronic tendon tears. MRI is useful in evaluating chronic patellar tendinitis because it establishes the diagnosis, detects associated chronic tears, and may help determine appropriate rehabilitation.

We report a case of fibroblastic proliferation of the median nerve presenting as a focal mass. This report discusses the pathological and magnetic resonance correlations and reviews the differential diagnosis for median nerve masses.