LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals.

Markerless three-dimensional (3D) pose estimation has become an indispensable tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by multi-view triangulation of deep network-based two-dimensional (2D) pose estimates. However, triangulation requires multiple synchronized cameras and elaborate calibration protocols that hinder its widespread adoption in laboratory studies. Here we describe LiftPose3D, a deep network-based method that overcomes these barriers by reconstructing 3D poses from a single 2D camera view. We illustrate LiftPose3D's versatility by applying it to multiple experimental systems using flies, mice, rats and macaques, and in circumstances where 3D triangulation is impractical or impossible. Our framework achieves accurate lifting for stereotypical and nonstereotypical behaviors from different camera angles. Thus, LiftPose3D permits high-quality 3D pose estimation in the absence of complex camera arrays and tedious calibration procedures and despite occluded body parts in freely behaving animals.

State Department of Health's Equitable Funding Allocation Methodology to Address COVID-19 Health Disparities Among High-Risk and Underserved Populations.

The Washington State Department of Health developed an equitable funding allocation methodology incorporating quantitative and qualitative decision-making components. We describe the methodology and an implementation evaluation performed by an external evaluation team using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) evaluation framework. The evaluation team concluded that the methodology was developed in a way that used a racial equity lens and prioritized intersectionalities in the communities that the funding was intended to serve. (Am J Public Health. 2024;114(S7):S575-S579. https://doi.org/10.2105/AJPH.2024.307833).

Impact of the early COVID-19 pandemic on adult mental health-related dispensed medications, hospitalizations and specialist outpatient visits in Norway and Sweden: Interrupted time series analysis.

AIMS: Norway and Sweden had different early pandemic responses that may have impacted mental health management. The aim was to assess the impact of the early COVID-19 pandemic on mental health-related care. METHODS: We used national registries in Norway and Sweden (1 January 2018-31 December 2020) to define 2 cohorts: (i) general adult population; and (ii) mental health adult population. Interrupted times series regression analyses evaluated step and slope changes compared to prepandemic levels for monthly rates of medications (antidepressants, antipsychotics, anxiolytics, hypnotics/sedatives, lithium, opioid analgesics, psychostimulants), hospitalizations (for anxiety, bipolar, depressive/mood, eating and schizophrenia/delusional disorders) and specialist outpatient visits. RESULTS: In Norway, immediate reductions occurred in the general population for medications (-12% antidepressants to -7% hypnotics/sedatives) except for antipsychotics; and hospitalizations (-33% anxiety disorders to -17% bipolar disorders). Increasing slope change occurred for all medications except psychostimulants (+1.1%/month hypnotics/sedatives to +1.7%/month antidepressants); and hospitalization for anxiety disorders (+5.5%/month), depressive/mood disorders (+1.7%/month) and schizophrenia/delusional disorders (+2%/month). In Sweden, immediate reductions occurred for antidepressants (-7%) and opioids (-10%) and depressive/mood disorder hospitalizations (-11%) only with increasing slope change in psychostimulant prescribing of (0.9%/month). In contrast to Norway, increasing slope changes occurred in specialist outpatient visits for depressive/mood disorders, eating disorders and schizophrenia/delusional disorders (+1.5, +1.9 and +2.3%/month, respectively). Similar changes occurred in the pre-existing mental health cohorts. CONCLUSION: Differences in early COVID-19 policy response may have contributed to differences in adult mental healthcare provision in Norway and Sweden.

Studying the Impact of European Union Regulatory Interventions for Minimising Risks From Medicines: Lessons Learnt and Recommendations.

PURPOSE: The European Medicines Agency's (EMA) Pharmacovigilance Risk Assessment Committee (PRAC) launched a strategy to examine the public health impact of major regulatory interventions aimed at minimising risks of medicinal products. We conducted a lessons learnt analysis of impact studies completed between 2015 and 2023. METHODS: We surveyed PRAC Sponsors and (Co-)Rapporteurs involved in the evaluation of 12 impact studies (10 commissioned by EMA and 2 conducted collaboratively by Member States) to explore how these support regulatory decision-making. Questions covered achievement of study objectives, risk minimisation effectiveness, added value for regulatory decision-making, and recommendations for future impact studies. Themes were generated using thematic content analysis. RESULTS: Survey responses from 15 PRAC Sponsors and (Co-)Rapporteurs from 10 European Union Member States were included in the analysis. Among four cross-sectional surveys and eight drug utilisation studies, 50% achieved all objectives, the other studies partially due to limitations. Two studies concluded that risk minimisation measures were overall effective, two were effective with variation across countries, two were partially effective and four studies showed limited effectiveness. Two studies were deemed inconclusive due to limitations. The reasons for the limited effectiveness of risk minimisation may be explored using mixed-method approaches. Assessment of study feasibility and a priori discussion of effectiveness measurements is important. CONCLUSION: Despite limitations, impact research adds value to regulatory decision-making by addressing knowledge gaps and providing additional information on unintended consequences of regulatory interventions. Our recommendations will help to improve planning, conducting and interpretating future impact studies.

Long-Term Impact of the Bloor Viaduct Suicide Barrier on Suicides in Toronto: A Time-Series Analysis: Effet à long terme de la barrière anti-suicide du viaduc Bloor sur les suicides à Toronto : une analyse chronologique.

BACKGROUND: A suicide prevention barrier was installed at Toronto's Bloor Viaduct bridge in 2003. It was associated with short-term location substitution, possibly mediated by media effects that did not persist over 1 decade. The long-term impact of the barrier is unknown. METHODS: We examined rates of suicides by jumping from the Bloor Viaduct, other bridges and by other methods using coroner's records in Toronto (1998-2020). We used interrupted time-series Poisson regression analyses to model changes in quarterly bridge-related suicides after barrier installation. A secondary analysis explored the potential substitution effects of suicide by other methods. RESULTS: Of 5219 suicides from 1998 to 2020, 303 were by jumping from bridges. After controlling for covariates, installation of the Bloor Viaduct suicide barrier was associated with a 49% step decrease in bridge-related suicide in the next quarter in Toronto (incidence rate ratio [IRR] = 0.51, 95% CI, 0.30 to 0.86) with no rebound increase in bridge-related suicide during the subsequent 17 years after the original drop (IRR = 0.99, 95% CI, 0.96 to 1.03). There was also no associated change in suicides by other methods after the barrier (IRR = 1.04, 95% CI, 0.90 to 1.20). CONCLUSIONS: Contrary to initial findings, these results indicate an enduring suicide prevention effect of the Bloor Viaduct suicide barrier. They support the long-term utility of structural interventions at high-frequency sites for suicide.

The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: A cross-sectional study using a large, primary care population dataset.

BACKGROUND: Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. METHODS AND FINDINGS: We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as ≥2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in ≥1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p < 0.001) when considering all 80 conditions. The threshold number of conditions at which multimorbidity prevalence was >99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of "comorbidity." Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. CONCLUSIONS: In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence.

Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service.

BACKGROUND: Measurement of multimorbidity in research is variable, including the choice of the data source used to ascertain conditions. We compared the estimated prevalence of multimorbidity and associations with mortality using different data sources. METHODS: A cross-sectional study of SAIL Databank data including 2,340,027 individuals of all ages living in Wales on 01 January 2019. Comparison of prevalence of multimorbidity and constituent 47 conditions using data from primary care (PC), hospital inpatient (HI), and linked PC-HI data sources and examination of associations between condition count and 12-month mortality. RESULTS: Using linked PC-HI compared with only HI data, multimorbidity was more prevalent (32.2% versus 16.5%), and the population of people identified as having multimorbidity was younger (mean age 62.5 versus 66.8 years) and included more women (54.2% versus 52.6%). Individuals with multimorbidity in both PC and HI data had stronger associations with mortality than those with multimorbidity only in HI data (adjusted odds ratio 8.34 [95% CI 8.02-8.68] versus 6.95 (95%CI 6.79-7.12] in people with ≥ 4 conditions). The prevalence of conditions identified using only PC versus only HI data was significantly higher for 37/47 and significantly lower for 10/47: the highest PC/HI ratio was for depression (14.2 [95% CI 14.1-14.4]) and the lowest for aneurysm (0.51 [95% CI 0.5-0.5]). Agreement in ascertainment of conditions between the two data sources varied considerably, being slight for five (kappa < 0.20), fair for 12 (kappa 0.21-0.40), moderate for 16 (kappa 0.41-0.60), and substantial for 12 (kappa 0.61-0.80) conditions, and by body system was lowest for mental and behavioural disorders. The percentage agreement, individuals with a condition identified in both PC and HI data, was lowest in anxiety (4.6%) and highest in coronary artery disease (62.9%). CONCLUSIONS: The use of single data sources may underestimate prevalence when measuring multimorbidity and many important conditions (especially mental and behavioural disorders). Caution should be used when interpreting findings of research examining individual and multiple long-term conditions using single data sources. Where available, researchers using electronic health data should link primary care and hospital inpatient data to generate more robust evidence to support evidence-based healthcare planning decisions for people with multimorbidity.

Curriculum Guidelines for Graduate and Undergraduate Virology Courses.

Curriculum guidelines for virology are needed to best guide student learning due to the continuous and ever-increasing volume of virology information, the need to ensure that undergraduate and graduate students have a foundational understanding of key virology concepts, and the importance in being able to communicate that understanding to both other virologists and nonvirologists. Such guidelines, developed by virology educators and the American Society for Virology Education and Career Development Committee, are described herein.

Changing co-morbidity and increasing deprivation among people living with HIV: UK population-based cross-sectional study.

BACKGROUND: The great success of HIV treatments means that, increasingly, people living with HIV (PLHIV) are growing old enough to develop age-associated comorbid conditions. We investigated the evolution of comorbid conditions and demographics among PLHIV in England. METHODS: In a cross-sectional study linking Clinical Practice Research Datalink (CPRD) primary care, hospitalization, death registry and Index of Multiple Deprivation data, we measured the prevalence of 304 individual health conditions, categorized into 47 condition groups (36 non-communicable, 11 communicable). Using logistic regression, we calculated odds ratios (ORs) for the likelihood of each condition and condition group in 2015 versus 2008, adjusting for age, sex and deprivation. RESULTS: In 2015, there were 964 CPRD-registered PLHIV compared with 1987 in 2008; 62% were male and 38% female in both cohorts. The 2015 cohort was older, with 51.1% aged 45-64 years and 7.2% aged 65-84 years compared with 31.8% and 3.2%, respectively, in 2008. Deprivation was higher in 2015, at 23.9% (quintile 4) and 28.7% (quintile 5) compared with 5.8% and 6.6%, respectively, in 2008. Of 36 non-communicable condition groups, 14 (39%) occurred in ≥ 10% of PLHIV in 2015, of which seven were more likely in 2015 than in 2008: renal-chronic-kidney-disease [odds ratio (OR) = 1.96 (95% CI: 1.33-2.90); endocrine-obesity [OR = 1.76 (1.12-2.77)]; rheumatology [OR = 1.64 (1.30-2.07)]; dermatology [OR = 1.55(1.29-1.85)]; genito-urinary-gynaecological [OR = 1.44(1.18-1.76)]; eyes-ears/nose/throat [OR = 1.31(1.08-1.59)]; and gastro-intestinal conditions [OR = 1.28 (1.04-1.58)]. Two condition groups, respiratory-chronic-obstructive-pulmonary-disease [OR = 0.36 (0.19-0.69)] and endocrine-diabetes [OR = 0.49 (0.34-0.70)], were less likely in 2015. Ten out of 11 communicable infectious condition groups were less likely in 2015. CONCLUSIONS: Although infections in PLHIV have fallen, chronic non-communicable comorbidity is increasingly prevalent. Alongside the marked increases in deprivation and ageing, this study suggests that socio-economic measures in addition to healthcare provision are needed to achieve holistic health for PLHIV.

Intranasal steroid use and COVID-19 mortality among patients with asthma and COPD: A retrospective cohort study.

BACKGROUND: Systemic corticosteroids have been widely used for treating patients with severe acute respiratory distress syndrome. Inhaled corticosteroids may have a protective effect for treating acute coronavirus disease 2019 (COVID-19); however, little is known about the potential effect of intranasal corticosteroids (INCS) on COVID-19 outcomes and severity. OBJECTIVE: To assess the impact of prior long-term INCS exposure on COVID-19 mortality among patients with chronic respiratory disease and in the general population. METHODS: A retrospective cohort study was conducted. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between INCS exposure and all-cause and COVID-19 mortality, adjusted by age, sex, deprivation, exacerbations in the last year, and comorbidities. RESULTS: Exposure to INCS did not have a significant association with COVID-19 mortality among the general population or cohorts with chronic obstructive pulmonary disease or asthma, with HRs of 0.8 (95% CI, 0.6-1.0, P = .06), 0.6 (95% CI, 0.3-1.1, P = .1), and 0.9 (95% CI, 0.2-3.9, P = .9), respectively. Exposure to INCS was, however, significantly associated with reduction in all-cause mortality in all groups, which was 40% lower (HR, 0.6 [95% CI, 0.5-0.6, P < .001]) among the general population, 30% lower (HR, 0.7; 95% CI, 0.6-0.8, P < .001) among patients with chronic obstructive pulmonary disease, and 50% lower (HR, 0.5; 95% CI, 0.3-0.7, P = .003) among patients with asthma. CONCLUSION: The role of INCS in COVID-19 is still unclear, but exposure to INCS does not adversely affect COVID-19 mortality. Further studies are needed to explore the association between their use and inflammatory activation, viral load, angiotensin-converting enzyme 2 gene expression, and outcomes, exploring different types and doses of INCS.

Diffuse intrinsic pontine gliomas: First registry effort in Mexico.

INTRODUCTION: Brainstem tumors comprise 10.9% of all brain tumors, and pediatric diffuse intrinsic pontine gliomas (DIPG) have a fatal prognosis. Some countries have developed national and international register databases to characterize their populations to aid clinical and public policy decisions. This study provides information regarding the clinical characteristics of a retrospective cohort of children with DIPG in México from 2001 to 2021, and assesses the proposed prognostic factors previously described for survival outcome. METHODS: Health institutions from Mexico were invited to contribute to a retrospective electronic registry of patients with DIPG based on the International DIPG Registry. Fisher's exact test was used to compare long- and short-term survivors. Overall survival was estimated using the Kaplan-Meier method. Differences between survival curves were evaluated using the log-rank test and Cox proportional hazard regression analysis. RESULTS: Total 110 patients were included. The median age of the patients at diagnosis was 7 years. Sixty patients (54.5%) presented with symptoms in less than 6 months; the most frequent symptom was ataxia (56.4%). Ninety patients received treatment (81.8%), the overall survival at 4 years was 11.4%, and 16 patients (14.5%) were admitted for palliative end-of-life care. We found no significant survival differences for any of the prognostic factors. CONCLUSION: This study highlights the need to develop strategies to standardize healthcare processes and enhance the quality of care to improve clinical diagnosis in Mexico. We also observed a barrier to the acceptance of palliative end-of-life care in the family and medical teams.

The expression of Oct3/4A mRNA and not its isoforms is upregulated by the HPV16 E7 oncoprotein.

PURPOSE: Oct3/4 a transcription factor is involved in maintaining the characteristics of cancer stem cells. Oct3/4 can be expressed differentially with respect to the progression of cervical cancer (CC). In addition, Oct3/4 can give rise to three isoforms by alternative splicing of the mRNA Oct3/4A, Oct3/4B and Oct3/4B1. The aim of this study was to evaluate the mRNA expression from Oct3/4A, Oct3/4B and Oct3/4B1 in low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL), CC samples, and measure the effect of the HPV16 E7 oncoprotein on the mRNA expression from Oct3/4 isoforms in the C-33A cell line. METHODS: The expression levels of Oct3/4A, Oct3/4B and Oct3/4B1 mRNA were analyzed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in patients with LSILs, HSILs and CC. Additionally, C-33A cells that expressed the HPV16 E7 oncoprotein were established to evaluate the effect of E7 on the expression of Oct3/4 mRNA isoforms. RESULTS: Oct3/4A (p = 0.02), Oct3/4B (p = 0. 001) and Oct3/4B1 (p < 0. 0001) expression is significantly higher in patients with LSIL, HSIL and CC than in woman with non-IL. In the C-33A cell line, the expression of Oct3/4A mRNA in the presence of the E7 oncoprotein increased compared to that in nontransfected C-33A cells. CONCLUSION: Oct3/4B and Oct3/4B1 mRNA were expressed at similar levels among the different groups. These data indicate that only the mRNA of Oct3/4A is upregulated by the HPV16 E7 oncoprotein.

External validation of the QLifetime cardiovascular risk prediction tool: population cohort study.

BACKGROUND: Prediction of lifetime cardiovascular disease (CVD) risk is recommended in many clinical guidelines, but lifetime risk models are rarely externally validated. The aim of this study was to externally validate the QRiskLifetime incident CVD risk prediction tool. METHODS: Independent external validation of QRiskLifetime using Clinical Practice Research Datalink data, examining discrimination and calibration in the whole population and stratified by age, and reclassification compared to QRISK3. Since lifetime CVD risk is unobservable, performance was evaluated at 10-years' follow-up, and lifetime performance inferred in terms of performance for in the different age-groups from which lifetime predictions are derived. RESULTS: One million, two hundreds sixty thousand and three hundreds twenty nine women and 1,223,265 men were included in the analysis. Discrimination was excellent in the whole population (Harrell's-C = 0.844 in women, 0.808 in men), but moderate to poor stratified by age-group (Harrell's C in people aged 30-44 0.714 for both men and women, in people aged 75-84 0.578 in women and 0.556 in men). Ten-year CVD risk was under-predicted in the whole population, and in all age-groups except women aged 45-64, with worse under-prediction in older age-groups. Compared to those at highest QRISK3 estimated 10-year risk, those with highest lifetime risk were younger (mean age: women 50.5 vs. 71.3 years; men 46.3 vs. 63.8 years) and had lower systolic blood pressure and prevalence of treated hypertension, but had more family history of premature CVD, and were more commonly minority ethnic. Over 10-years, the estimated number needed to treat (NNT) with a statin to prevent one CVD event in people with QRISK3 ≥ 10% was 34 in women and 37 in men, compared to 99 and 100 for those at highest lifetime risk. CONCLUSIONS: QRiskLifetime underpredicts 10-year CVD risk in nearly all age-groups, so is likely to also underpredict lifetime risk. Treatment based on lifetime risk has considerably lower medium-term benefit than treatment based on 10-year risk.

Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe.

Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma.Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients ('diagnosed' and 'hospitalized') based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions.Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6-8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7-6.8) to 18.5% (95% CI 18.2-18.8) in the diagnosed cohort and 5.2% (95% CI 4.0-6.8) to 20.5% (95% CI 18.6-22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8-2.4) to 16.9% (95% CI 13.8-20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15-30% of hospitalized COVID-19 asthma patients.Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients.[Box: see text]Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392 .

Predictive performance of a competing risk cardiovascular prediction tool CRISK compared to QRISK3 in older people and those with comorbidity: population cohort study.

BACKGROUND: Recommended cardiovascular disease (CVD) prediction tools do not account for competing mortality risk and over-predict incident CVD in older and multimorbid people. The aim of this study was to derive and validate a competing risk model (CRISK) to predict incident CVD and compare its performance to that of QRISK3 in UK primary care. METHODS: We used UK linked primary care data from the Clinical Practice Research Datalink (CPRD) GOLD to identify people aged 25-84 years with no previous CVD or statin treatment split into derivation and validation cohorts. In the derivation cohort, we derived models using the same covariates as QRISK3 with Fine-Gray competing risk modelling alone (CRISK) and with Charlson Comorbidity score (CRISK-CCI) as an additional predictor of non-CVD death. In a separate validation cohort, we examined discrimination and calibration compared to QRISK3. Reclassification analysis examined the number of patients recommended for treatment and the estimated number needed to treat (NNT) to prevent a new CVD event. RESULTS: The derivation and validation cohorts included 989,732 and 494,865 women and 946,784 and 473,392 men respectively. Overall discrimination of CRISK and CRISK-CCI were excellent and similar to QRISK3 (for women, C-statistic = 0.863/0.864/0.863 respectively; for men 0.833/0.819/0.832 respectively). CRISK and CRISK-CCI calibration overall and in younger people was excellent. CRISK over-predicted in older and multimorbid people although performed better than QRISK3, whilst CRISK-CCI performed the best. The proportion of people reclassified by CRISK-CCI varied by QRISK3 risk score category, with 0.7-9.7% of women and 2.8-25.2% of men reclassified as higher risk and 21.0-69.1% of women and 27.1-57.4% of men reclassified as lower risk. Overall, CRISK-CCI recommended fewer people for treatment and had a lower estimated NNT at 10% risk threshold. Patients reclassified as higher risk were younger, had lower SBP and higher BMI, and were more likely to smoke. CONCLUSIONS: CRISK and CRISK-CCI performed better than QRISK3. CRISK-CCI recommends fewer people for treatment and has a lower NNT to prevent a new CVD event compared to QRISK3. Competing risk models should be recommended for CVD primary prevention treatment recommendations.

Patient outcomes following AKI and AKD: a population-based cohort study.

BACKGROUND: Acute kidney injury (AKI) is common and associated with adverse outcomes as well as important healthcare costs. However, evidence examining the epidemiology of acute kidney disease (AKD)-recently defined as AKI persisting between 7 and 90 days-remains limited. The aims of this study were to establish the rates of early AKI recovery, progression to AKD and non-recovery; examine risk factors associated with non-recovery and investigate the association between recovery timing and adverse outcomes, in a population-based cohort. METHODS: All adult residents of Tayside & Fife, Scotland, UK, with at least one episode of community or hospital-managed AKI using KDIGO creatinine-based definition during the period 1 January 2010 to 31 December 2018 were identified. Logistic regression was used to examine factors associated with non-recovery, and Cox modelling was used to establish associations between AKI recovery timing and risks of mortality and development of de novo CKD. RESULTS: Over 9 years, 56,906 patients with at least one AKI episode were identified with 18,773 (33%) of these progressing to AKD. Of those progressing to AKD, 5059 (27%) had still not recovered at day 90 post AKI diagnosis. Risk factors for AKD included: increasing AKI severity, pre-existing cancer or chronic heart failure and recent use of loop diuretics. Compared with early AKI recovery, progression to AKD was associated with increased hazard of 1-year mortality and de novo CKD (HR = 1.20, 95% CI 1.13 to 1.26 and HR = 2.21, 95% CI 1.91 to 2.57 respectively). CONCLUSIONS: These findings highlight the importance of early AKI recognition and management to avoid progression to AKD and long-term adverse outcomes.

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network.

BACKGROUND: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. METHODS: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. RESULTS: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. CONCLUSIONS: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.

Inhibition of cytoplasmic cap methylation identifies 5' TOP mRNAs as recapping targets and reveals recapping sites downstream of native 5' ends.

Cap homeostasis is the cyclical process of decapping and recapping that maintains the translation and stability of a subset of the transcriptome. Previous work showed levels of some recapping targets decline following transient expression of an inactive form of RNMT (ΔN-RNMT), likely due to degradation of mRNAs with improperly methylated caps. The current study examined transcriptome-wide changes following inhibition of cytoplasmic cap methylation. This identified mRNAs with 5'-terminal oligopyrimidine (TOP) sequences as the largest single class of recapping targets. Cap end mapping of several TOP mRNAs identified recapping events at native 5' ends and downstream of the TOP sequence of EIF3K and EIF3D. This provides the first direct evidence for downstream recapping. Inhibition of cytoplasmic cap methylation was also associated with mRNA abundance increases for a number of transcription, splicing, and 3' processing factors. Previous work suggested a role for alternative polyadenylation in target selection, but this proved not to be the case. However, inhibition of cytoplasmic cap methylation resulted in a shift of upstream polyadenylation sites to annotated 3' ends. Together, these results solidify cap homeostasis as a fundamental process of gene expression control and show cytoplasmic recapping can impact regulatory elements present at the ends of mRNA molecules.

But, Do I Need a College Degree?: Understanding Perceptions of College and Career Readiness among Students Enrolled in a Career and Technical High School.

Career and technical education (CTE) and college preparation curriculum in high school are often treated as mutually exclusive options rather than integrated, symbiotic tracks. However, increasingly career fields require some postsecondary education, and access to four-year college degrees are important for long-term earnings and mobility. In this two-year case study, we examined how 16 juniors enrolled in a CTE high school described and perceived their college and career aspirations. Our findings revealed that participants saw vocational and academic goals as mutually beneficial but experienced them through distinctive pathways, a disconnect amplified by a lack of resources in our sample site. While mechanisms to promote college-going existed, they were often only available to subsets of students and of limited utility. From this research, we suggest that the education system should expand dual enrollment opportunities, provide mentorship of diverse career possibilities, and begin integration between college and career planning earlier in students' schooling. Moreover, we examine the possibilities demonstrated by this case study for K-16 pathways and how postsecondary institutions can meaningfully engage with CTE schools to support this integration.