Towards fair and clinically relevant polygenic predictions.

Lennon et al. recently proposed a clinical polygenic score (PGS) pipeline as part of the Electronic Medical Records and Genomics (eMERGE) network initiative. In this spotlight article we discuss the broader context for the use of PGS in preventive medicine and highlight key limitations and challenges facing their inclusion in prediction models.

Adopting electric school buses in the United States: Health and climate benefits.

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

Implementing personalized pathways for cancer follow-up care in the United States: Proceedings from an American Cancer Society-American Society of Clinical Oncology summit.

A new approach to cancer follow-up care is necessary to meet the needs of cancer survivors while dealing with increasing volume and provider shortages, knowledge gaps, and costs to both health care systems and patients. An approach that triages patients to personalized follow-up care pathways, depending on the type(s) and level(s) of resources needed for patients' long-term care, is in use in the United Kingdom and other countries and has been shown to meet patients' needs, more efficiently use the health care system, and reduce costs. Recognizing that testing and implementing a similar personalized approach to cancer follow-up care in the United States will require a multipronged strategy, the American Cancer Society and the American Society of Clinical Oncology convened a summit in January 2018 to identify the needed steps to move this work from concept to implementation. The summit identified 4 key strategies going forward: 1) developing a candidate model (or models) of care delivery; 2) building the case for implementation by conducting studies modeling the effects of personalized pathways of follow-up care on patient outcomes, workforce and health care resources, and utilization and costs; 3) creating consensus-based guidelines to guide the delivery of personalized care pathways; and 4) identifying and filling research gaps to develop and implement needed care changes. While these national strategies are pursued, oncology and primary care providers can lay the groundwork for implementation by assessing their patients' risk of recurrence and the chronic and late effects of cancer as well as other health care needs and resources available for care and by considering triaging patients accordingly, referring patients to appropriate specialized survivorship clinics as these are developed, helping to support patients who are capable of self-managing their health, setting expectations with patients from diagnosis onward for the need for follow-up in primary care and/or a survivorship clinic, and improving coordination of care between oncology and primary care.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics.

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

Cohort bias in predictive risk assessments of future criminal justice system involvement.

Risk assessment instruments (RAIs) are widely used to aid high-stakes decision-making in criminal justice settings and other areas such as health care and child welfare. These tools, whether using machine learning or simpler algorithms, typically assume a time-invariant relationship between predictors and outcome. Because societies are themselves changing and not just individuals, this assumption may be violated in many behavioral settings, generating what we call cohort bias. Analyzing criminal histories in a cohort-sequential longitudinal study of children, we demonstrate that regardless of model type or predictor sets, a tool trained to predict the likelihood of arrest between the ages of 17 and 24 y on older birth cohorts systematically overpredicts the likelihood of arrest for younger birth cohorts over the period 1995 to 2020. Cohort bias is found for both relative and absolute risks, and it persists for all racial groups and within groups at highest risk for arrest. The results imply that cohort bias is an underappreciated mechanism generating inequality in contacts with the criminal legal system that is distinct from racial bias. Cohort bias is a challenge not only for predictive instruments with respect to crime and justice, but also for RAIs more broadly.

Childhood Non-HDL Cholesterol and LDL Cholesterol and Adult Atherosclerotic Cardiovascular Events.

BACKGROUND: Although low-density lipoprotein cholesterol (LDL-C) remains the primary cholesterol target in clinical practice in children and adults, non-high-density lipoprotein cholesterol (non-HDL-C) has been suggested as a more accurate measure of atherosclerotic cardiovascular disease (ASCVD) risk. We examined the associations of childhood non-HDL-C and LDL-C levels with adult ASCVD events and determined whether non-HDL-C has better utility than LDL-C in predicting adult ASCVD events. METHODS: This prospective cohort study included 21 126 participants from the i3C Consortium (International Childhood Cardiovascular Cohorts). Proportional hazards regressions were used to estimate the risk for incident fatal and fatal/nonfatal ASCVD events associated with childhood non-HDL-C and LDL-C levels (age- and sex-specific z scores; concordant/discordant categories defined by guideline-recommended cutoffs), adjusted for sex, Black race, cohort, age at and calendar year of child measurement, body mass index, and systolic blood pressure. Predictive utility was determined by the C index. RESULTS: After an average follow-up of 35 years, 153 fatal ASCVD events occurred in 21 126 participants (mean age at childhood visits, 11.9 years), and 352 fatal/nonfatal ASCVD events occurred in a subset of 11 296 participants who could be evaluated for this outcome. Childhood non-HDL-C and LDL-C levels were each associated with higher risk of fatal and fatal/nonfatal ASCVD events (hazard ratio ranged from 1.27 [95% CI, 1.14-1.41] to 1.35 [95% CI, 1.13-1.60] per unit increase in the risk factor z score). Non-HDL-C had better discriminative utility than LDL-C (difference in C index, 0.0054 [95% CI, 0.0006-0.0102] and 0.0038 [95% CI, 0.0008-0.0068] for fatal and fatal/nonfatal events, respectively). The discordant group with elevated non-HDL-C and normal LDL-C had a higher risk of ASCVD events compared with the concordant group with normal non-HDL-C and LDL-C (fatal events: hazard ratio, 1.90 [95% CI, 0.98-3.70]; fatal/nonfatal events: hazard ratio, 1.94 [95% CI, 1.23-3.06]). CONCLUSIONS: Childhood non-HDL-C and LDL-C levels are associated with ASCVD events in midlife. Non-HDL-C is better than LDL-C in predicting adult ASCVD events, particularly among individuals who had normal LDL-C but elevated non-HDL-C. These findings suggest that both non-HDL-C and LDL-C are useful in identifying children at higher risk of ASCVD events, but non-HDL-C may provide added prognostic information when it is discordantly higher than the corresponding LDL-C and has the practical advantage of being determined without a fasting sample.

Development and Validation of the American Heart Association's PREVENT Equations.

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Cardiovascular Management of Patients Undergoing Hematopoietic Stem Cell Transplantation: From Pretransplantation to Survivorship: A Scientific Statement From the American Heart Association.

Hematopoietic stem cell transplantation can cure various disorders but poses cardiovascular risks, especially for elderly patients and those with cardiovascular diseases. Cardiovascular evaluations are crucial in pretransplantation assessments, but guidelines are lacking. This American Heart Association scientific statement summarizes the data on transplantation-related complications and provides guidance for the cardiovascular management throughout transplantation. Hematopoietic stem cell transplantation consists of 4 phases: pretransplantation workup, conditioning therapy and infusion, immediate posttransplantation period, and long-term survivorship. Complications can occur during each phase, with long-term survivors facing increased risks for late effects such as cardiovascular disease, secondary malignancies, and endocrinopathies. In adults, arrhythmias such as atrial fibrillation and flutter are the most frequent acute cardiovascular complication. Acute heart failure has an incidence ranging from 0.4% to 2.2%. In pediatric patients, left ventricular systolic dysfunction and pericardial effusion are the most common cardiovascular complications. Factors influencing the incidence and risk of complications include pretransplantation therapies, transplantation type (autologous versus allogeneic), conditioning regimen, comorbid conditions, and patient age. The pretransplantation cardiovascular evaluation consists of 4 steps: (1) initial risk stratification, (2) exclusion of high-risk cardiovascular disease, (3) assessment of cardiac reserve, and (4) optimization of cardiovascular reserve. Clinical risk scores could be useful tools for the risk stratification of adult patients. Long-term cardiovascular management of hematopoietic stem cell transplantation survivors includes optimizing risk factors, monitoring, and maintaining a low threshold for evaluating cardiovascular causes of symptoms. Future research should prioritize refining risk stratification and creating evidence-based guidelines and strategies to optimize outcomes in this growing patient population.

Neurodevelopmental Outcomes for Individuals With Congenital Heart Disease: Updates in Neuroprotection, Risk-Stratification, Evaluation, and Management: A Scientific Statement From the American Heart Association.

Over the past decade, new research has advanced scientific knowledge of neurodevelopmental trajectories, factors that increase neurodevelopmental risk, and neuroprotective strategies for individuals with congenital heart disease. In addition, best practices for evaluation and management of developmental delays and disorders in this high-risk patient population have been formulated based on literature review and expert consensus. This American Heart Association scientific statement serves as an update to the 2012 statement on the evaluation and management of neurodevelopmental outcomes in children with congenital heart disease. It includes revised risk categories for developmental delay or disorder and an updated list of factors that increase neurodevelopmental risk in individuals with congenital heart disease according to current evidence, including genetic predisposition, fetal and perinatal factors, surgical and perioperative factors, socioeconomic disadvantage, and parental psychological distress. It also includes an updated algorithm for referral, evaluation, and management of individuals at high risk. Risk stratification of individuals with congenital heart disease with the updated categories and risk factors will identify a large and growing population of survivors at high risk for developmental delay or disorder and associated impacts across the life span. Critical next steps must include efforts to prevent and mitigate developmental delays and disorders. The goal of this scientific statement is to inform health care professionals caring for patients with congenital heart disease and other key stakeholders about the current state of knowledge of neurodevelopmental outcomes for individuals with congenital heart disease and best practices for neuroprotection, risk stratification, evaluation, and management.

Cardiogenic Shock in Older Adults: A Focus on Age-Associated Risks and Approach to Management: A Scientific Statement From the American Heart Association.

Cardiogenic shock continues to portend poor outcomes, conferring short-term mortality rates of 30% to 50% despite recent scientific advances. Age is a nonmodifiable risk factor for mortality in patients with cardiogenic shock and is often considered in the decision-making process for eligibility for various therapies. Older adults have been largely excluded from analyses of therapeutic options in patients with cardiogenic shock. As a result, despite the association of advanced age with worse outcomes, focused strategies in the assessment and management of cardiogenic shock in this high-risk and growing population are lacking. Individual programs oftentimes develop upper age limits for various interventional strategies for their patients, including heart transplantation and durable left ventricular assist devices. However, age as a lone parameter should not be used to guide individual patient management decisions in cardiogenic shock. In the assessment of risk in older adults with cardiogenic shock, a comprehensive, interdisciplinary approach is central to developing best practices. In this American Heart Association scientific statement, we aim to summarize our contemporary understanding of the epidemiology, risk assessment, and in-hospital approach to management of cardiogenic shock, with a unique focus on older adults.

Systematic comparison of family history and polygenic risk across 24 common diseases.

Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs. We explore the dynamic for three types of family history across 24 common diseases: first- and second-degree family history and parental causes of death. Covering a large proportion of the burden of non-communicable diseases in adults, we show that family history and PRS are independent and not interchangeable measures, but instead provide complementary information on inherited disease susceptibility. The PRSs explained on average 10% of the effect of first-degree family history, and first-degree family history 3% of PRSs, and PRS effects were independent of both early- and late-onset family history. The PRS stratified the risk similarly in individuals with and without family history. In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history. This study provides a catalogue of risk estimates for both family history of disease and PRSs and highlights opportunities for a more comprehensive way of assessing inherited disease risk across common diseases.

A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology.

The emergence of multidrug-resistant bacteria is a critical global crisis that poses a serious threat to public health, particularly with the rise of multidrug-resistant Staphylococcus aureus. Accurate assessment of drug resistance is essential for appropriate treatment and prevention of transmission of these deadly pathogens. Early detection of drug resistance in patients is critical for providing timely treatment and reducing the spread of multidrug-resistant bacteria. This study aims to develop a novel risk assessment framework for S. aureus that can accurately determine the resistance to multiple antibiotics. The comprehensive 7-year study involved ˃20 000 isolates with susceptibility testing profiles of six antibiotics. By incorporating mass spectrometry and machine learning, the study was able to predict the susceptibility to four different antibiotics with high accuracy. To validate the accuracy of our models, we externally tested on an independent cohort and achieved impressive results with an area under the receiver operating characteristic curve of 0. 94, 0.90, 0.86 and 0.91, and an area under the precision-recall curve of 0.93, 0.87, 0.87 and 0.81, respectively, for oxacillin, clindamycin, erythromycin and trimethoprim-sulfamethoxazole. In addition, the framework evaluated the level of multidrug resistance of the isolates by using the predicted drug resistance probabilities, interpreting them in the context of a multidrug resistance risk score and analyzing the performance contribution of different sample groups. The results of this study provide an efficient method for early antibiotic decision-making and a better understanding of the multidrug resistance risk of S. aureus.

Prediction of Venous Thromboembolism in Diverse Populations Using Machine Learning and Structured Electronic Health Records.

BACKGROUND: Venous thromboembolism (VTE) is a major cause of morbidity and mortality worldwide. Current risk assessment tools, such as the Caprini and Padua scores and Wells criteria, have limitations in their applicability and accuracy. This study aimed to develop machine learning models using structured electronic health record data to predict diagnosis and 1-year risk of VTE. METHODS: We trained and validated models on data from 159 001 participants in the Mount Sinai Data Warehouse. We then externally tested them on 401 723 participants in the UK Biobank and 123 039 participants in All of Us. All data sets contain populations of diverse ancestries and clinical histories. We used these data sets to develop small, medium, and large models with increasing features on a range of optimizing portability to maximizing performance. We make trained models publicly available in click-and-run format at https://doi.org/10.17632/tkwzysr4y6.6. RESULTS: In the holdout and external test sets, respectively, models achieved areas under the receiver operating characteristic curve of 0.80 to 0.83 and 0.72 to 0.82 for VTE diagnosis prediction and 0.76 to 0.78 and 0.64 to 0.69 for 1-year risk prediction, significantly outperforming the Padua score. Models also demonstrated robust performance across different VTE types and patient subsets, including ethnicity, age, and surgical and hospitalization status. Models identified both established and novel clinical features contributing to VTE risk, offering valuable insights into its underlying pathophysiology. CONCLUSIONS: Machine learning models using structured electronic health record data can significantly improve VTE diagnosis and 1-year risk prediction in diverse populations. Model probability scores exist on a continuum, affecting mortality risk in both healthy individuals and VTE cases. Integrating these models into electronic health record systems to generate real-time predictions may enhance VTE risk assessment, early detection, and preventative measures, ultimately reducing the morbidity and mortality associated with VTE.

Cancer Incidence After Diagnosis of Abdominal Aortic Aneurysm-Brief Report.

BACKGROUND: Epidemiological and mechanistic data support a potential causal link between cardiovascular disease (CVD) and cancer. Abdominal aortic aneurysms (AAAs) represent a common form of CVD with at least partially distinct genetic and biologic pathogenesis from other forms of CVD. The risk of cancer and how this risk differs compared with other forms of CVD, is unknown among AAA patients. We conducted a retrospective cohort study using the IBM MarketScan Research Database to test whether individuals with AAA have a higher cancer risk independent of traditional shared risk factors. METHODS: All individuals ≥18 years of age with ≥36 months of continuous coverage between 2008 and 2020 were enrolled. Those with potential Mendelian etiologies of AAA, aortic aneurysm with nonspecific anatomic location, or a cancer diagnosis before the start of follow-up were excluded. A subgroup analysis was performed of individuals having the Health Risk Assessment records including tobacco use and body mass index. The following groups of individuals were compared: (1) with AAA, (2) with non-AAA CVD, and (3) without any CVD. RESULTS: The propensity score-matched cohort included 58 993 individuals with AAA, 117 986 with non-AAA CVD, and 58 993 without CVD. The 5-year cumulative incidence of cancer was 13.1% (12.8%-13.5%) in participants with AAA, 10.1% (9.9%-10.3%) in participants with non-AAA CVD, and 9.6% (9.3%-9.9%) in participants without CVD. Multivariable-adjusted Cox proportional hazards regression models found that patients with AAA exhibited a higher cancer risk than either those with non-AAA CVD (hazard ratio, 1.28 [95% CI, 1.23-1.32]; P<0.001) or those without CVD (hazard ratio, 1.32 [95% CI, 1.26-1.38]; P<0.001). Results remained consistent after excluding common smoking-related cancers and when adjusting for tobacco use and body mass index. CONCLUSIONS: Patients with AAA may have a unique risk of cancer requiring further mechanistic study and investigation of the role of enhanced cancer screening.

Circulating tumour cells predict recurrences and survival in head and neck squamous cell carcinoma patients.

Patients with head and neck squamous cell carcinoma (HNSCC) are at a high risk of developing recurrence and secondary cancers. This study evaluates the prognostic and surveillance utilities of circulating tumour cells (CTCs) in HNSCC. A total of 154 HNSCC patients were recruited and followed up for 4.5 years. Blood samples were collected at baseline and follow-up. CTCs were isolated using a spiral microfluid device. Recurrence and death due to cancer were assessed during the follow-up period. In patients with HNSCC, the presence of CTCs at baseline was a predictor of recurrence (OR = 8.40, p < 0.0001) and death (OR= ∞, p < 0.0001). Patients with CTCs at baseline had poor survival outcomes (p < 0.0001). Additionally, our study found that patients with CTCs in a follow-up appointment were 2.5 times more likely to experience recurrence or death from HNSCC (p < 0.05) prior to their next clinical visit. Our study highlights the prognostic and monitoring utilities of CTCs' in HNSCC patients. Early identification of CTCs facilitates precise risk assessment, guiding treatment choices and ultimately enhancing patient outcomes.

Active antibiotic resistome in soils unraveled by single-cell isotope probing and targeted metagenomics.

Antimicrobial resistance (AMR) in soils represents a serious risk to human health through the food chain and human-nature contact. However, the active antibiotic-resistant bacteria (ARB) residing in soils that primarily drive AMR dissemination are poorly explored. Here, single-cell Raman-D2O coupled with targeted metagenomics is developed as a culture-independent approach to phenotypically and genotypically profiling active ARB against clinical antibiotics in a wide range of soils. This method quantifies the prevalence (contamination degree) and activity (spread potential) of soil ARB and reveals a clear elevation with increasing anthropogenic activities such as farming and the creation of pollution, thereby constituting a factor that is critical for the assessment of AMR risks. Further targeted sorting and metagenomic sequencing of the most active soil ARB uncover several uncultured genera and a pathogenic strain. Furthermore, the underlying resistance genes, virulence factor genes, and associated mobile genetic elements (including plasmids, insertion sequences, and prophages) are fully deciphered at the single-cell level. This study advances our understanding of the soil active AMR repertoire by linking the resistant phenome to the genome. It will aid in the risk assessment of environmental AMR and guide the combat under the One Health framework.

New-onset atrial fibrillation and chronic coronary syndrome in the CLARIFY registry.

BACKGROUND AND AIMS: Data on new-onset atrial fibrillation (NOAF) in patients with chronic coronary syndromes (CCS) are scarce. This study aims to describe the incidence, predictors, and impact on cardiovascular (CV) outcomes of NOAF in CCS patients. METHODS: Data from the international (45 countries) CLARIFY registry (prospeCtive observational LongitudinAl RegIstry oF patients with stable coronary arterY disease) were used. Among 29 001 CCS outpatients without previously reported AF at baseline, patients with at least one episode of AF/flutter diagnosed during 5-year follow-up were compared with patients in sinus rhythm throughout the study. RESULTS: The incidence rate of NOAF was 1.12 [95% confidence interval (CI) 1.06-1.18] per 100 patient-years (cumulative incidence at 5 years: 5.0%). Independent predictors of NOAF were increasing age, increasing body mass index, low estimated glomerular filtration rate, Caucasian ethnicity, alcohol intake, and low left ventricular ejection fraction, while high triglycerides were associated with lower incidence. New-onset atrial fibrillation was associated with a substantial increase in the risk of adverse outcomes, with adjusted hazard ratios of 2.01 (95% CI 1.61-2.52) for the composite of CV death, non-fatal myocardial infarction, or non-fatal stroke, 2.61 (95% CI 2.04-3.34) for CV death, 1.64 (95% CI 1.07-2.50) for non-fatal myocardial infarction, 2.27 (95% CI 1.85-2.78) for all-cause death, 8.44 (95% CI 7.05-10.10) for hospitalization for heart failure, and 4.46 (95% CI 2.85-6.99) for major bleeding. CONCLUSIONS: Among CCS patients, NOAF is common and is strongly associated with worse outcomes. Whether more intensive preventive measures and more systematic screening for AF would improve prognosis in this population deserves further investigation.

Polygenic risk score adds to a clinical risk score in the prediction of cardiovascular disease in a clinical setting.

BACKGROUND AND AIMS: A cardiovascular disease polygenic risk score (CVD-PRS) can stratify individuals into different categories of cardiovascular risk, but whether the addition of a CVD-PRS to clinical risk scores improves the identification of individuals at increased risk in a real-world clinical setting is unknown. METHODS: The Genetics and the Vascular Health Check Study (GENVASC) was embedded within the UK National Health Service Health Check (NHSHC) programme which invites individuals between 40-74 years of age without known CVD to attend an assessment in a UK general practice where CVD risk factors are measured and a CVD risk score (QRISK2) is calculated. Between 2012-2020, 44,141 individuals (55.7% females, 15.8% non-white) who attended an NHSHC in 147 participating practices across two counties in England were recruited and followed. When 195 individuals (cases) had suffered a major CVD event (CVD death, myocardial infarction or acute coronary syndrome, coronary revascularisation, stroke), 396 propensity-matched controls with a similar risk profile were identified, and a nested case-control genetic study undertaken to see if the addition of a CVD-PRS to QRISK2 in the form of an integrated risk tool (IRT) combined with QRISK2 would have identified more individuals at the time of their NHSHC as at high risk (QRISK2 10-year CVD risk of ≥10%), compared with QRISK2 alone. RESULTS: The distribution of the standardised CVD-PRS was significantly different in cases compared with controls (cases mean score .32; controls, -.18, P = 8.28×10-9). QRISK2 identified 61.5% (95% confidence interval [CI]: 54.3%-68.4%) of individuals who subsequently developed a major CVD event as being at high risk at their NHSHC, while the combination of QRISK2 and IRT identified 68.7% (95% CI: 61.7%-75.2%), a relative increase of 11.7% (P = 1×10-4). The odds ratio (OR) of being up-classified was 2.41 (95% CI: 1.03-5.64, P = .031) for cases compared with controls. In individuals aged 40-54 years, QRISK2 identified 26.0% (95% CI: 16.5%-37.6%) of those who developed a major CVD event, while the combination of QRISK2 and IRT identified 38.4% (95% CI: 27.2%-50.5%), indicating a stronger relative increase of 47.7% in the younger age group (P = .001). The combination of QRISK2 and IRT increased the proportion of additional cases identified similarly in women as in men, and in non-white ethnicities compared with white ethnicity. The findings were similar when the CVD-PRS was added to the atherosclerotic cardiovascular disease pooled cohort equations (ASCVD-PCE) or SCORE2 clinical scores. CONCLUSIONS: In a clinical setting, the addition of genetic information to clinical risk assessment significantly improved the identification of individuals who went on to have a major CVD event as being at high risk, especially among younger individuals. The findings provide important real-world evidence of the potential value of implementing a CVD-PRS into health systems.

Health Care Personnel Exposure Risk Assessment and Management During a Mpox Outbreak in Chicago, Illinois, 17 May to 8 July 2022.

This report summarizes risk assessment interviews and follow-up with health care personnel (HCP) after exposure to patients with mpox disease during 17 May to 8 July 2022. HCP-case interactions were assessed using a standard questionnaire to categorize the risk associated with patient encounters. We assessed 150 interactions among 142 HCP and 30 cases. Four (2.7%) interactions were defined as high risk, 5 (3.3%) intermediate, 107 (71.3%) low, and 31 (20.7%) no risk. High and intermediate exposures were offered postexposure prophylaxis; 4 accepted. No documented mpox transmission after exposure was identified. These findings suggest transmission risk in health care settings during routine patient care is low.

Fruit Flies: Challenges and Opportunities to Stem the Tide of Global Invasions.

Global trade in fresh fruit and vegetables, intensification of human mobility, and climate change facilitate fruit fly (Diptera: Tephritidae) invasions. Life-history traits, environmental stress response, dispersal stress, and novel genetic admixtures contribute to their establishment and spread. Tephritids are among the most frequently intercepted taxa at ports of entry. In some countries, supported by the rules-based trade framework, a remarkable amount of biosecurity effort is being arrayed against the range expansion of tephritids. Despite this effort, fruit flies continue to arrive in new jurisdictions, sometimes triggering expensive eradication responses. Surprisingly, scant attention has been paid to biosecurity in the recent discourse about new multilateral trade agreements. Much of the available literature on managing tephritid invasions is focused on a limited number of charismatic (historically high-profile) species, and the generality of many patterns remains speculative.