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Background A minority of acute coronary syndrome (ACS) cases are associated with ventricular arrhythmias (VA) and/or cardiac arrest (CA). We investigated the effect of VA/CA at the time of ACS on long‐term outcomes. Methods and Results We analyzed routine clinical data from 5 National Health Service trusts in the United Kingdom, collected between 2010 and 2017 by the National Institute for Health Research Health Informatics Collaborative. A total of 13 444 patients with ACS, 376 (2.8%) of whom had concurrent VA, survived to hospital discharge and were followed up for a median of 3.42 years. Patients with VA or CA at index presentation had significantly increased risks of subsequent VA during follow‐up (VA group: adjusted hazard ratio [HR], 4.15 [95% CI, 2.42–7.09]; CA group: adjusted HR, 2.60 [95% CI, 1.23–5.48]). Patients who suffered a CA in the context of ACS and survived to discharge also had a 36% increase in long‐term mortality (adjusted HR, 1.36 [95% CI, 1.04–1.78]), although the concurrent diagnosis of VA alone during ACS did not affect all‐cause mortality (adjusted HR, 1.03 [95% CI, 0.80–1.33]). Conclusions Patients who develop VA or CA during ACS who survive to discharge have increased risks of subsequent VA, whereas those who have CA during ACS also have an increase in long‐term mortality. These individuals may represent a subgroup at greater risk of subsequent arrhythmic events as a result of intrinsically lower thresholds for developing VA.

Implications of elevated troponin on time-to-surgery in non-ST elevation myocardial infarction(NIHR Health Informatics Collaborative:TROP-CABG study). Benedetto et al. BACKGROUND: The optimal timing of coronary artery bypass grafting (CABG) in patients with non-ST elevation myocardial infarction (NSTEMI) and the utility of pre-operative troponin levels in decision-making remains unclear. We investigated (a) the association between peak pre-operative troponin and survival post-CABG in a large cohort of NSTEMI patients and (b) the interaction between troponin and time-to-surgery. METHODS AND RESULTS: Our cohort consisted of 1746 patients (1684 NSTEMI; 62 unstable angina) (mean age 69 ± 11 years,21% female) with recorded troponins that had CABG at five United Kingdom centers between 2010 and 2017. Time-segmented Cox regression was used to investigate the interaction of peak troponin and time-to-surgery on early (within 30 days) and late (beyond 30 days) survival. Average interval from peak troponin to surgery was 9 ± 15 days, with 1466 (84.0%) patients having CABG during the same admission. Sixty patients died within 30-days and another 211 died after a mean follow-up of 4 ± 2 years (30-day survival 0.97 ± 0.004 and 5-year survival 0.83 ± 0.01). Peak troponin was a strong predictor of early survival (adjusted P = 0.002) with a significant interaction with time-to-surgery (P interaction = 0.007). For peak troponin levels100 times the upper limit of normal, there was no improvement in early survival with longer time-to-surgery. However, in patients with higher troponins, early survival increased progressively with a longer time-to-surgery, till day 10. Peak troponin did not influence survival beyond 30 days (adjusted P = 0.64). CONCLUSIONS: Peak troponin in NSTEMI patients undergoing CABG was a significant predictor of early mortality, strongly influenced the time-to-surgery and may prove to be a clinically useful biomarker in the management of these patients.

Background Patients presenting to primary care with chest pain are often not given a cause. Patients with such unattributed chest pain have an increased risk of future cardiovascular disease (CVD) compared to patients with diagnosed non-coronary chest pain. It is unknown whether risk factors for CVD determined in the general population are the same for the population with unattributed or non-coronary chest pain. Purpose To determine if key risk factors for a coronary event in patients with unattributed chest pain are similar to those for patients with non-coronary chest pain and previously identified in the general population. Methods The study used primary care information from the Clinical Practice Research Datalink Aurum linked to hospital inpatient and mortality data. Patients aged ≥18 years with an incident record of unattributed or non-coronary chest pain in 2002–2018 and no diagnosis of CVD were included. We included as potential risk factors those established for CVD in the general population and non-coronary explanations for chest pain. Flexible parametric models estimated hazard ratios (95% confidence intervals (CI)) between factors and incident coronary event (defined as myocardial infarction, angina, coronary heart disease, percutaneous intervention, and coronary artery bypass graft surgery). Results There were 375,240 patients with unattributed chest pain (53% female: mean age 49; 47% male: mean age 47) and 245,329 patients with non-coronary chest pain (58% female: mean age 47; 42% male: mean age 44). Median duration of follow-up was 5 years. In the unattributed chest pain group, there were 111 (95% CI: 109, 112) and 140 (138, 142) coronary events per 10,000 person-years in females and males, respectively. Lower rates of coronary event were observed in the non-coronary chest pain group (females: 73 (72, 75); males: 96 (94, 98)). Within females (Figure), in both chest pain groups the strongest risk factors were type I and type II diabetes, atrial fibrillation, and hypertension whereas no associations were observed for migraine and chronic kidney disease. Whilst alternative explanations for non-coronary chest pain also increased the risk of coronary events, associations were less strong than for established general population risk factors. Similar findings were found in males although family history of coronary event was a stronger risk factor in the non-coronary chest pain group compared to the unattributed chest pain group. Conclusions The pool of factors found to increase the risk of coronary events in patients presenting with recorded unattributed or non-coronary chest pain are similar but not identical to those identified for the general population. Further research is needed to develop prognostic models to identify patients at the most risk of a coronary event as models developed in the general population are unlikely to be applicable given the increased underlying risk of coronary events in these populations. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Study funded by the British Heart Foundation, reference PG/19/46/34307. KJ also supported by matched funding awarded to the NIHR Applied Research Collaboration (West Midlands). Risk factors for coronary event

Background: Targeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR). Methods: In this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18–74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions. Findings: We included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65–74 years), adults in the youngest age group (18–24 years) had the highest OR (4·22 [95% CI 3·86–4·62]) and greatest absolute risk (37% vs 24%) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06–5·22) and absolute risk (42% vs 18%) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23–6·59) and absolute risk (22% vs 5%) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18–1·27), for men versus women was 1·12 (1·08–1·16), and for Black individuals versus White individuals was 1·13 (1·04–1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period. Interpretation: A radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18–24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care. Funding: The British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research. © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

Estimating the effect of a change in a particular risk factor and a chronic disease requires information on the risk factor from two time points; the enrolment and the first follow-up. When using observational data to study the effect of such an exposure (change in risk factor) extra complications arise, namely (i) when is time zero? and (ii) which information on confounders should we account for in this type of analysis? From enrolment or the 1st follow-up? Or from both?. The combination of these questions has proven to be very challenging. Researchers have applied different methodologies with mixed success, because the different choices made when answering these questions induce systematic bias. Here we review these methodologies and highlight the sources of bias in each type of analysis. We discuss the advantages and the limitations of each method ending by making our recommendations on the analysis plan.

Background Previous trials suggest lower long-term mortality after invasive rather than non-invasive management among patients with non-ST elevation myocardial infarction (NSTEMI), but these excluded very elderly patients. Methods We estimated the effect of invasive versus non-invasive management within 3 days of peak troponin on survival in NSTEMI patients aged ≥80 years, using routine clinical data collected during 2010–2017 (NIHR Health Informatics Collaborative). Propensity scores based on pre-treatment variables were derived using logistic regression; patients with high probabilities of non-invasive or invasive management were excluded. Patients who died within 3 days without receiving invasive management were assigned to the invasive or non-invasive management groups based on their propensity scores, to mitigate immortal time bias. We estimated mortality hazard ratios comparing invasive with non-invasive management, and also compared rates of hospital admission for heart failure. Findings Of 1976 patients with NSTEMI, 101 died within 3 days of their peak troponin, whilst 375 were excluded because of extreme propensity scores. The remaining 1500 patients (56% non-invasive management) had a median age 86 (IQR 82-89) years. During median follow-up of 3.0 (IQR 1.2-4.8) years, there were 613 (41%) deaths. Using inverse probability weighting, adjusted cumulative 5-year mortality was 36% and 55% in the invasive and non-invasive management groups, respectively. The mortality hazard ratio comparing invasive with non-invasive management was 0.64 (95% CI 0.52-0.79) after multivariable adjustment for clinical characteristics and propensity score and inclusion of patients who died within three days. Invasive management was associated with lower incidence of hospital admissions for heart failure (adjusted rate ratio compared with non-invasive management 0.67, 95% CI 0.48–0.93).

Introduction For non-ST-segment elevation acute coronary syndrome (NSTEACS) there is a gap between the use of class 1 guideline recommended therapies and clinical practice. The GRACE risk score is recommended in international guidelines for the risk stratification of NSTEACS, but its impact on adherence to guideline-indicated treatments and reducing adverse clinical outcomes is unknown. The objective of the UKGRIS trial is to assess the effectiveness of the GRACE risk score tool and associated treatment recommendations on the use of guideline-indicated care and clinical outcomes. Methods and Analysis The UK GRACE Risk Score Intervention Study (UKGRIS), a parallel-group cluster randomised registry-based controlled trial, will allocate hospitals in a 1:1 ratio to manage NSTEACS by standard care or according to the GRACE risk score and associated international guidelines. UKGRIS will recruit a minimum of 3000 patients from at least 30 English National Health Service hospitals and collect healthcare data from national electronic health records. The co-primary endpoints are the use of guideline-indicated therapies, and the composite of cardiovascular death, non-fatal myocardial infarction, new onset heart failure hospitalisation or cardiovascular readmission at 12 months. Secondary endpoints include duration of inpatient hospital stay over 12 months, EQ-5D-5L responses and utilities, unscheduled revascularisation and the components of the composite endpoint over 12 months follow-up. Ethics and Dissemination The study has ethical approval (North East - Tyne & Wear South Research Ethics Committee ref: 4/NE/1180). Findings will be announced at relevant conferences and published in peer-reviewed journals in line with the funder’s open access policy. Registration ISRCTN29731761, registered 12th January 2017.

BACKGROUND & AIMS: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. METHODS: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. RESULTS: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p

BACKGROUND: Genetic variation at chromosome 9p21 is a recognized risk factor for coronary heart disease (CHD). However, its effect on disease progression and subsequent events is unclear, raising questions about its value for stratification of residual risk.METHODS: A variant at chromosome 9p21 (rs1333049) was tested for association with subsequent events during follow-up in 103 357 Europeans with established CHD at baseline from the GENIUS-CHD (Genetics of Subsequent Coronary Heart Disease) Consortium (73.1% male, mean age 62.9 years). The primary outcome, subsequent CHD death or myocardial infarction (CHD death/myocardial infarction), occurred in 13 040 of the 93 115 participants with available outcome data. Effect estimates were compared with case/control risk obtained from the CARDIoGRAMplusC4D consortium (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) including 47 222 CHD cases and 122 264 controls free of CHD.RESULTS: Meta-analyses revealed no significant association between chromosome 9p21 and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline (GENIUSCHD odds ratio, 1.02; 95% CI, 0.99-1.05). This contrasted with a strong association in CARDIoGRAMPlusC4D odds ratio 1.20; 95% CI, 1.18-1.22; P for interaction < 0.001 compared with the GENIUS-CHD estimate. Similarly, no clear associations were identified for additional subsequent outcomes, including all-cause death, although we found a modest positive association between chromosome 9p21 and subsequent revascularization (odds ratio, 1.07; 95% CI, 1.04-1.09).CONCLUSIONS: In contrast to studies comparing individuals with CHD to disease-free controls, we found no clear association between genetic variation at chromosome 9p21 and risk of subsequent acute CHD events when all individuals had CHD at baseline. However, the association with subsequent revascularization may support the postulated mechanism of chromosome 9p21 for promoting atheroma development.