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Clinical studies are generally required to characterize the accuracy of new diagnostic tests. In some cases, historical data are available from a predicate device, which is directly relevant to the new test. If this data can be appropriately incorporated into the new test study design, there is an opportunity to reduce the sample size and trial duration for the new test. One approach to achieve this is the Bayesian power prior method, which allows for the historical information to be down-weighted via a power parameter. We propose a dynamic method to calculate the power parameter based on first comparing the data between the historical and new data sources using a one-sided comparison, and second mapping the comparison probability through a scaled-Weibull discount function to tune the effective sample size borrowed. This pragmatic and conservative approach is embedded in an adaptive trial framework allowing for the trial to stop early for success. An example is presented for a new test developed to detect Methicillin-resistant Staphylococcus aureus present in the nasal carriage.

Background: The SPYRAL HTN-OFF MED Pivotal trial demonstrated that RDN was efficacious compared to a sham control. The underlying model was an extension of the analysis of covariance (ANCOVA) model, adjusted for baseline blood pressure (BP), and allowed borrowing of information from the previously reported feasibility study using a novel Bayesian method. Fundamental to the estimation of a treatment effect for efficacy are a multitude of statistical modelling assumptions, including the role of outliers, linearity of the association between baseline BP and outcome, and parallelism of the treatment effect difference over the baseline BP range. In this report, we examine the validity of these assumptions to verify the robustness of the treatment effect measured., Methods: We examined the requisite modelling assumptions of the ANCOVA model fitted to the SPYRAL HTN-OFF MED Pivotal trial using Bayesian methods. To address outliers, we fit a robust regression model (with heavy tailed errors) to the data with diffuse weakly informative prior distributions on the parameters. To address linearity, we replaced the linear baseline term by a natural spline term with 4 degrees of freedom. To address parallelism, we refit the ANCOVA model with an interaction term for treatment arm and baseline BP., Results: ANCOVA models were fitted to the trial data (pooled across the feasibility and pivotal cohorts) using Bayesian methodology with diffuse (non-informative) prior distributions. The modelling assumptions inherent to the ANCOVA models were shown to be broadly satisfied. A robust ANCOVA model yielded a posterior treatment effect of -4.1 mmHg (95% credible interval: -6.3 to -1.9) indicating the influence of outlier values was small. There was moderate evidence of an interaction term effect between baseline BP and treatment, but no evidence of gross violation of linearity in baseline BP., Conclusion: The posterior treatment effect estimate is shown to be robust to underlying model assumptions, thus further supporting the evidence of RDN to be an efficacious treatment for resistant hypertension., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests.Mr. Fahy, Dr. Brar, and Ms. DeBruin are employees and shareholders of Medtronic, Dr. Hickey was a former employee of Medtronic. Prof. Pocock reports consultant fees from Medtronic outside the submitted work. Dr. Weber reports personal fees from Medtronic, Ablative Solutions, ReCor, and Boston Scientific, all outside the submitted work. Prof. Böhm reports personal fees from Amgen, Bayer, Servier, Medtronic, Boehringer Ingelheim, Vifor, Bristol Myers Squibb, and Astra Zeneca, all outside the submitted work. Prof. Mahfoud is supported by Deutsche Gesellschaft für Kardiologie (DGK), and Deutsche Forschungsgemeinschaft (SFB TRR219) and has received scientific support and speaker honoraria from Bayer, Boehringer Ingelheim, Medtronic and ReCor Medical. Dr. Kandzari reports institutional research/grant support from Medtronic and Ablative Solution; and personal consulting honoraria from Medtronic., (© 2021 Published by Elsevier Inc.)

Aims: Multiple endpoints with varying clinical relevance are available to establish the efficacy of device-based treatments. Given the variance among blood pressure measures and medication changes in hypertension trials, we performed a win ratio analysis of outcomes in a sham-controlled, randomised trial of renal denervation (RDN) in patients with uncontrolled hypertension despite commonly prescribed antihypertensive medications. We propose a novel prioritised endpoint framework for determining the treatment benefit of RDN compared with sham control., Methods and Results: We analysed the SPYRAL HTN-ON MED pilot study data using a prioritised hierarchical endpoint comprised of 24-hour mean ambulatory systolic blood pressure (SBP), office SBP, and medication burden. A generalised pairwise comparisons methodology (win ratio) was extended to examine this endpoint. Clinically relevant thresholds of 5 and 10 mmHg were used for comparisons of ambulatory and office SBP, respectively, and therefore to define treatment "winners" and "losers". For a total number of 1,596 unmatched pairs, the RDN subject was the winner in 1,050 pairs, the RDN subject was the loser in 378 pairs, and 168 pairs were tied. The win ratio in favour of RDN was 2.78 (95% confidence interval [CI]: 1.58 to 5.48; p<0.001) and corresponding net benefit statistic was 0.42 (95% CI: 0.20 to 0.63). Sensitivity analyses performed with differing blood pressure thresholds and according to drug adherence testing demonstrated consistent results., Conclusions: The win ratio method addresses prior limitations by enabling inclusion of more patient-oriented results while prioritising those endpoints considered most clinically important. Applying these methods to the SPYRAL HTN-ON MED pilot study (ClinicalTrials.gov Identifier: NCT02439775), RDN was determined to be superior regarding a hierarchical endpoint and a "winner" compared with sham control patients.

Aims: Indexed effective orifice area (EOAi) charts are used to determine the likelihood of prosthesis-patient mismatch (PPM) after aortic valve replacement (AVR). The aim of this study is to validate whether these EOAi charts, based on echocardiographic normal reference values, can accurately predict PPM., Methods and Results: In the PERIcardial SurGical AOrtic Valve ReplacemeNt (PERIGON) Pivotal Trial, 986 patients with aortic valve stenosis/regurgitation underwent AVR with an Avalus valve. Patients were randomly split (50:50) into training and test sets. The mean measured EOAs for each valve size from the training set were used to create an Avalus EOAi chart. This chart was subsequently used to predict PPM in the test set and measures of diagnostic accuracy (sensitivity, specificity, and negative and positive predictive value) were assessed. PPM was defined by an EOAi ≤0.85 cm2/m2, and severe PPM was defined as EOAi ≤0.65 cm2/m2. The reference values obtained from the training set ranged from 1.27 cm2 for size 19 mm up to 1.81 cm2 for size 27 mm. The test set had an incidence of 66% of PPM and 24% of severe PPM. The EOAi chart inaccurately predicted PPM in 30% of patients and severe PPM in 22% of patients. For the prediction of PPM, the sensitivity was 87% and the specificity 37%. For the prediction of severe PPM, the sensitivity was 13% and the specificity 98%., Conclusion: The use of echocardiographic normal reference values for EOAi charts to predict PPM is unreliable due to the large proportion of misclassifications., (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: We aimed to estimate the rate of renal artery adverse events following renal denervation with the most commonly applied radiofrequency catheter system based on a comprehensive review of published reports., Methods and Results: We reviewed 50 published renal denervation (RDN) trials reporting on procedural safety including 5,769 subjects with 10,249 patient-years of follow-up. Twenty-six patients with renal artery stenosis or dissection (0.45%) were identified of whom 24 (0.41%) required renal artery stenting. The primary meta-analysis of all reports indicated a 0.20% pooled annual incidence rate of stent implantation (95% CI: 0.12 to 0.29% per year). Additional sensitivity analyses yielded consistent pooled estimates (range: 0.17 to 0.42% per year). Median time from RDN procedure to all renal intervention was 5.5 months (range: 0 to 33 months); 79% of all events occurred within one year of the procedure. A separate review of 14 clinical trials reporting on prospective follow-up imaging using either magnetic resonance imaging, computed tomography or angiography following RDN in 511 total subjects identified just 1 new significant stenosis (0.20%) after a median of 11 months post procedure (one to 36 months)., Conclusions: Renal artery reintervention following renal denervation with the most commonly applied RF renal denervation system (Symplicity) is rare. Most events were identified within one year.

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Background: The SPYRAL HTN clinical trial program was initiated with two 80-patient pilot studies, SPYRAL HTN-OFF MED and SPYRAL HTN-ON MED, which provided biological proof of principle that renal denervation has a blood pressure-lowering effect versus sham controls for subjects with uncontrolled hypertension in the absence or presence of antihypertensive medications, respectively., Trial Design: Two multicenter, prospective, randomized, sham-controlled trials have been designed to evaluate the safety and efficacy of catheter-based renal denervation for the reduction of blood pressure in subjects with hypertension in the absence (SPYRAL HTN-OFF MED Pivotal) or presence (SPYRAL HTN-ON MED Expansion) of antihypertensive medications. The primary efficacy endpoint is baseline-adjusted change from baseline in 24-h ambulatory systolic blood pressure. The primary safety endpoint is incidence of major adverse events at 1 month after randomization (or 6 months in cases of new renal artery stenosis). Both trials utilize a Bayesian design to allow for prespecified interim analyses to take place, and thus, the final sample sizes are dependent on whether enrollment is stopped at the first or second interim analysis. SPYRAL HTN-OFF MED Pivotal will enroll up to 300 subjects and SPYRAL HTN-ON MED Expansion will enroll up to 221 subjects. A novel Bayesian power prior approach will leverage historical information from the pilot studies, with a degree of discounting determined by the level of agreement with data from the prospectively powered studies., Conclusions: The Bayesian paradigm represents a novel and promising approach in device-based hypertension trials., Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02439749 (SPYRAL HTN-OFF MED Pivotal) and NCT02439775 (SPYRAL HTN-ON MED Expansion).

Background Blood pressure (BP) guidelines for patients with aortic stenosis or a history of aortic stenosis treated with aortic valve replacement (AVR) match those in the general population, but this extrapolation may not be warranted. Methods and Results Among patients enrolled in the Medtronic intermediate, high, and extreme risk trials, we included those with a transcatheter AVR (n=1794) or surgical AVR (n=1103) who were alive at 30 days. The associations between early (average of discharge and 30 day post-AVR) systolic BP (SBP) and diastolic BP (DBP) measurements and clinical outcomes between 30 days and 1 year were evaluated. Among 2897 patients, after adjustment, spline curves demonstrated an association between lower SBP (<120 mm Hg, representing 21% of patients) and DBP (<60 mm Hg, representing 30% of patients) and increased all-cause and cardiovascular mortality and repeat hospitalization. These relationships were unchanged when patients with moderate-to-severe aortic regurgitation post-AVR were excluded. After adjustment, compared with DBP 60 to <80 mm Hg, DBP 30 to <60 mm Hg was associated with increased all-cause (adjusted hazard ratio 1.62, 95% CI 1.23-2.14) and cardiovascular mortality (adjusted hazard ratio 2.13, 95% CI 1.52-3.00), but DBP 80 to <100 mm Hg was not. Similarly, after adjustment, compared with SBP 120 to <150 mm Hg, SBP 90 to <120 mm Hg was associated with increased all-cause (adjusted hazard ratio 1.63, 95% CI 1.21-2.21) and cardiovascular mortality (adjusted hazard ratio 1.81, 95% CI 1.25-2.61), but SBP 150 to <180 mm Hg was not. Conclusions Lower BP in the first month after transcatheter AVR or surgical AVR is common and associated with increased mortality and repeat hospitalization. Clarifying optimal BP targets in these patients ought to be a priority and may improve patient outcomes. Clinical Trial Registration Information URL: http://www.clinicaltrials.gov. Unique identifiers: NCT01586910, NCT01240902.

Objective: The objective of this multicentre study was to compare short-term and midterm outcomes between sternotomy and minimally invasive approaches for mitral valve surgery., Methods: Data for all mitral valve procedures with or without concomitant tricuspid atrial fibrillation surgery were analysed from three UK hospitals between January 2008 and December 2016. To account for selection bias between minimally invasive approach and sternotomy, one-to-one propensity score calliper matching without replacement was performed. The main outcome measure was midterm reintervention free survival that was summarised by the Kaplan-Meier estimator and compared between treatment arms using the stratified log-rank test., Results: A total of 2404 procedures (1757 sternotomy and 647 minimally invasive) were performed during the study period. Propensity score matching resulted in 639 matched pairs with improved balance postmatching in all 31 covariates (absolute standardised mean differences <10%). Despite longer procedural times patients who underwent minimally invasive surgery had a lower need for transfusion (20.5%vs14.4%, p=0.005) and reduced median postoperative length of stay (7 vs 6 days, p<0.001). There were no statistically significant differences in the rates of in-hospital mortality or postoperative stroke. Reintervention-free survival at 8 years was estimated as 86.1% in the minimally invasive group and 84.1% in the sternotomy group (p=0.40)., Conclusions: Minimally invasive surgery is associated with excellent short-term outcomes and comparable midterm outcomes for patients undergoing mitral valve surgery. A minimally invasive approach should be considered for all patients who require mitral valve intervention and should be the standard against which transcatheter mitral techniques are compared., Competing Interests: Competing interests: GLH is currently an employee of Medtronic Ltd; however, all work for this study was performed while he was employed at the University of Liverpool. SH has acted as a consultant for Edwards Lifesciences and Atricure BLV. JZ has acted as a proctor and received speaking fees from Edwards Lifesciences, Abbott and Cryolife., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Multivariable regression models are used to establish the relationship between a dependent variable (i.e. an outcome of interest) and more than 1 independent variable. Multivariable regression can be used for a variety of different purposes in research studies. The 3 most common types of multivariable regression are linear regression, logistic regression and Cox proportional hazards regression. A detailed understanding of multivariable regression is essential for correct interpretation of studies that utilize these statistical tools. This statistical primer discusses some common considerations and pitfalls for researchers to be aware of when undertaking multivariable regression.

Regression modelling is an important statistical tool frequently utilized by cardiothoracic surgeons. However, these models-including linear, logistic and Cox proportional hazards regression-rely on certain assumptions. If these assumptions are violated, then a very cautious interpretation of the fitted model should be taken. Here, we discuss several assumptions and report diagnostics that can be used to detect departures from these assumptions. Most of the diagnostics discussed are based on residuals: a measure of the difference between the observed and model fitted values. Reliable and generalizable results depend on correctly developed statistical models, and proper diagnostics should play an integral part in the model development.

When designing a clinical study, a fundamental aspect is the sample size. In this article, we describe the rationale for sample size calculations, when it should be calculated and describe the components necessary to calculate it. For simple studies, standard formulae can be used; however, for more advanced studies, it is generally necessary to use specialized statistical software programs and consult a biostatistician. Sample size calculations for non-randomized studies are also discussed and two clinical examples are used for illustration.

Survival analysis incorporates various statistical methods specific to data on time until an event of interest. While the event is often death, giving rise to the phrase 'survival analysis', the event might also be, for example, a reoperation. As such, it is sometimes referred to as 'time-to-event analysis'. Censoring sets survival analysis apart from other analyses: at the end of the follow-up period, not all subjects have experienced the event of interest, and some subjects may drop out of the study prior to completion. Survival data for a group of subjects is usually visualized by the Kaplan-Meier estimator, representing the probability of a subject remaining free of the event during follow-up. There are several methods to compare survival between the study groups, for example, treatment arms, including the log-rank test and the Cox proportional hazards model. The log-rank test is an unadjusted non-parametric method, whereas the Cox proportional hazards model allows comparison while adjusting for multiple covariates. A principal assumption of the Cox proportional hazards model is that the relative hazard stays constant over time-the so-called proportionality. Specific methods exist for comparison of survival with the general population. This article describes the fundamental concepts every cardiothoracic surgeon should be aware of when analysing survival data and are illustrated with a clinical example.

Background: Joint modelling of longitudinal and time-to-event outcomes has received considerable attention over recent years. Commensurate with this has been a rise in statistical software options for fitting these models. However, these tools have generally been limited to a single longitudinal outcome. Here, we describe the classical joint model to the case of multiple longitudinal outcomes, propose a practical algorithm for fitting the models, and demonstrate how to fit the models using a new package for the statistical software platform R, joineRML., Results: A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process. The models are fitted using a Monte Carlo Expectation-Maximisation algorithm, and inferences are based on approximate standard errors from the empirical profile information matrix, which are contrasted to an alternative bootstrap estimation approach. We illustrate the model and software on a real data example for patients with primary biliary cirrhosis with three repeatedly measured biomarkers., Conclusions: An open-source software package capable of fitting multivariate joint models is available. The underlying algorithm and source code makes use of several methods to increase computational speed.

Longitudinal data arise when repeated measurements are taken on the same individuals over time. Inference about between-group differences of within-subject change is usually of interest. This statistical primer for cardiothoracic and vascular surgeons aims to provide a short and practical introduction of biostatistical methods on how to analyse repeated-measures data. Several methodological approaches for analysing repeated measures will be introduced, ranging from simple approaches to advanced regression modelling. Design considerations of studies involving repeated measures are discussed, and the methods are illustrated with a data set measuring coronary sinus potassium in dogs after occlusion. Cardiothoracic and vascular surgeons should be aware of the myriad approaches available to them for analysing repeated-measures data, including the relative merits and disadvantages of each. It is important to present effective graphical displays of the data and to avoid arbitrary cross-sectional statistical comparisons.

Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy.

A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods.

Objectives: Surgery for acute type A aortic dissection (ATAD) carries a high risk of operative mortality. We examined the surgeon volume-outcome relation with respect to in-hospital mortality for patients presenting with this pathology in the United Kingdom., Method: Between April 2007 and March 2013, 1550 ATAD procedures were identified from the National Institute for Cardiovascular Outcomes Research database. A total of 249 responsible consultant cardiac surgeons from the United Kingdom recorded 1 or more of these procedures in their surgical activity over this period. We describe the patient population and mortality rates, focusing on the relationship between surgeon volume and in-hospital mortality., Results: The mean annual volume of procedures per surgeon during the 6-year period ranged from 1 to 6.6. The overall in-hospital mortality rate was 18.3% (283/1550). A mortality improvement at the 95% level was observed with a risk-adjusted mean annual volume >4.5. Surgeons with a mean annual volume <4 over the study period had significantly higher in-hospital mortality rates in comparison with surgeons with a mean annual volume ≥4 (19.3% vs 12.6%; P = .015)., Conclusions: Patients with ATAD who are operated on by lower-volume surgeons experience higher levels of in-hospital mortality. Directing these patients to higher-volume surgeons may be a strategy to reduce in-hospital mortality., (Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)

Importance: Postmarket evidence generation for medical devices is important yet limited for prosthetic aortic valve devices in the United Kingdom., Objective: To identify prosthetic aortic valve models that display unexpected patterns of mortality or reintervention using routinely collected national registry data and record linkage., Design, Setting, and Participants: This observational study used data from all National Health Service and private hospitals in England and Wales that submit data to the National Adult Cardiac Surgery Audit (NACSA). All patients undergoing first-time elective and urgent aortic valve replacement surgery (with or without coronary artery bypass grafting) with a biological (n = 15 series) or mechanical (n = 10 series) prosthetic valve from 5 primary suppliers, and satisfying prespecified data quality criteria (n = 43 782 biological; n = 11 084 mechanical) between 1998 and 2013 were included. Valves were classified into series of related models. Outcome tracking was performed using multifaceted record linkage. The median follow-up was 4.1 years (maximum, 15.3 years). Cox proportional hazards regression with random effects (frailty models) were used to model valve effects on the outcomes, with and without adjustment for preoperative and intraoperative covariates., Main Outcomes and Measures: Time to all-cause mortality or aortic valve reintervention (surgical or transcatheter). There were 13 104 deaths and 723 reinterventions during follow-up., Results: Of 79 345 isolated aortic valve replacement procedures with or without coronary artery bypass grafting, 54 866 were analyzed. Biological valve implantation rates increased from 59% in 1998 and 1999 to 86% in 2012 and 2013. Two series of valves associated with significantly increased hazard of death or reintervention were identified (first series: frailty, 1.18; 95% prediction interval [PI], 1.06-1.32 and second series: frailty, 1.19; 95% PI, 1.09-1.31). These results were robust to covariate adjustment and sensitivity analyses. There were 3 prosthetic valves with a significant reduction in hazard (valve 1: frailty, 0.88; 95% PI, 0.80-0.96; valve 2: frailty, 0.88; 95% PI, 0.80-0.96; and valve 3: frailty, 0.88; 95% PI, 0.78-0.98)., Conclusions and Relevance: Meaningful evidence from the analysis of routinely collected registry data can inform postmarket surveillance of medical devices. Although the findings are associated with a number of caveats, 2 specific biological aortic valve series identified in this study may warrant further investigation.

Background: Available methods for the joint modelling of longitudinal and time-to-event outcomes have typically only allowed for a single longitudinal outcome and a solitary event time. In practice, clinical studies are likely to record multiple longitudinal outcomes. Incorporating all sources of data will improve the predictive capability of any model and lead to more informative inferences for the purpose of medical decision-making., Methods: We reviewed current methodologies of joint modelling for time-to-event data and multivariate longitudinal data including the distributional and modelling assumptions, the association structures, estimation approaches, software tools for implementation and clinical applications of the methodologies., Results: We found that a large number of different models have recently been proposed. Most considered jointly modelling linear mixed models with proportional hazard models, with correlation between multiple longitudinal outcomes accounted for through multivariate normally distributed random effects. So-called current value and random effects parameterisations are commonly used to link the models. Despite developments, software is still lacking, which has translated into limited uptake by medical researchers., Conclusion: Although, in an era of personalized medicine, the value of multivariate joint modelling has been established, researchers are currently limited in their ability to fit these models routinely. We make a series of recommendations for future research needs.

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting., (Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)

Objectives:  To estimate the potential impact of universal screening for primary prevention of cardiovascular disease (National Health Service Health Checks) on disease burden and socioeconomic inequalities in health in England, and to compare universal screening with alternative feasible strategies., Design:  Microsimulation study of a close-to-reality synthetic population. Five scenarios were considered: baseline scenario, assuming that current trends in risk factors will continue in the future; universal screening; screening concentrated only in the most deprived areas; structural population-wide intervention; and combination of population-wide intervention and concentrated screening., Setting:  Synthetic population with similar characteristics to the community dwelling population of England., Participants:  Synthetic people with traits informed by the health survey for England., Main Outcome Measure:  Cardiovascular disease cases and deaths prevented or postponed by 2030, stratified by fifths of socioeconomic status using the index of multiple deprivation., Results:  Compared with the baseline scenario, universal screening may prevent or postpone approximately 19 000 cases (interquartile range 11 000-28 000) and 3000 deaths (-1000-6000); concentrated screening 17 000 cases (9000-26 000) and 2000 deaths (-1000-5000); population-wide intervention 67 000 cases (57 000-77 000) and 8000 deaths (4000-11 000); and the combination of the population-wide intervention and concentrated screening 82 000 cases (73 000-93 000) and 9000 deaths (6000-13 000). The most equitable strategy would be the combination of the population-wide intervention and concentrated screening, followed by concentrated screening alone and the population-wide intervention. Universal screening had the least apparent impact on socioeconomic inequalities in health., Conclusions:  When primary prevention strategies for reducing cardiovascular disease burden and inequalities are compared, universal screening seems less effective than alternative strategies, which incorporate population-wide approaches. Further research is needed to identify the best mix of population-wide and risk targeted CVD strategies to maximise cost effectiveness and minimise inequalities., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Background: To facilitate patient choice and the risk adjustment of consultant outcomes in aortic operations, reliable predictive tools are required. Our objective was to develop a risk prediction model for in-hospital mortality after operation on the proximal aorta., Methods: Data for 8641 consecutive UK patients undergoing proximal aortic operation from the National Institute for Cardiovascular Outcomes Research database from April 2007 to March 2013 were analyzed. Multivariable logistic regression was used to identify independent predictors of in-hospital mortality. Model calibration and discrimination were assessed., Results: In-hospital mortality was 4.6% in elective operations and 16.5% in nonelective operations. In the elective model, previous cardiac operation (adjusted odds ratio [OR] 4.1, 95% confidence interval [CI]: 3.0 to 4.7) and ejection fraction greater than 30% (adjusted OR 2.3, 95% CI: 1.7 to 3.1) were the strongest predictors of mortality (p < 0.001). The area under the receiver operating characteristic (AUROC) curve was 0.805 (95% CI: 0.802 to 0.807) with a bias-corrected value of 0.795. Model calibration was acceptable (p = 0.427) on the basis of the Hosmer-Lemeshow goodness-of-fit test. In the nonelective model, salvage operations (adjusted OR 9.9, 95% CI: 6.5 to 15.2) and previous cardiac operation (adjusted OF 3.9, 95% CI: 3.0 to 5.0) were the strongest predictors of mortality (p < 0.001). The AUROC curve was 0.761 (95% CI: 0.761 to 0.765) with a bias-corrected value of 0.756, and model calibration was also found to be acceptable (p = 0.616)., Conclusions: We propose the use of these risk models to improve patient choice and to enhance patients' awareness of risks and risk-adjust aortic operation outcomes for case-mix., (Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Objectives: To determine if the use of cardiopulmonary bypass is associated with all-cause in-hospital and mid-term survival for patients undergoing left internal mammary artery (LIMA) to left anterior descending (LAD) coronary artery bypass grafting (CABG) for single coronary vessel disease., Methods: Data from the National Adult Cardiac Surgery Audit registry for all elective and urgent isolated CABG procedures performed between April 2003 and March 2013 in first-time cardiac surgery patients were extracted. Experienced surgeons (those with ≥300 records) were classified by their technique preference (as 'off-pump preference', 'mixed practice', 'on-pump preference') based on their entire isolated CABG data. In-hospital mortality and time to death were analysed using logistic and Cox proportional hazards regression models, respectively., Results: From a total of 3402 records, 65.5% were performed off-pump. There were 16 (0.47%) in-hospital deaths: 6 (0.51%) in the on-pump group and 10 (0.45%) in the off-pump group. The risk-adjusted odds ratio of in-hospital mortality in the direction of on-pump was 1.09 [95% confidence interval (CI): 0.39-3.04; P = 0.86]. The overall 5-year survival in the on- and off-pump groups was 93.1 and 93.4%, respectively. The adjusted hazard ratio (HR) for mortality in the direction of on-pump CABG was 1.15 (95% CI: 0.89-1.49; P = 0.28). Comparing off-pump cases performed by experienced CABG surgeons with a preference for the off-pump technique with on-pump cases performed by surgeons with a preference for the on-pump technique indicated a significant difference (HR for on-pump = 1.72; 95% CI: 1.19-2.47; P = 0.004)., Conclusions: Elective and urgent first-time CABG for isolated LAD disease is associated with excellent mid-term survival in the England and Wales population, conferring a 5-year survival rate of 93.1 and 93.4% in the on-pump and off-pump groups, respectively. There was no difference in risk-adjusted survival between the on-pump and off-pump techniques when analysing all procedures; however, supportive analysis demonstrated that off-pump surgery performed by experienced surgeons with a preference for the off-pump technique in their CABG caseload is associated with improved mid-term survival when compared with on-pump surgery performed by surgeons with a preference for the on-pump technique., (© The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Objectives: The first transcatheter aortic valve implantation (TAVI) in England and Wales was performed in 2007. This study presents the subsequent national activity and outcomes for both TAVI and aortic valve replacement (AVR)., Methods: Data for all AVR and TAVI procedures between January 2006 and December 2012 in England and Wales were included. The number of procedures, patient characteristics, in-hospital and 30-day mortality, postoperative length of stay (PLOS) and survival were analysed separately for: isolated AVR; AVR + coronary artery bypass graft (CABG) surgery; AVR + other surgery and TAVI., Results: The number of TAVIs increased from 66 in 2007 (0.8% of all implants) to 1186 in 2012 (10.9% of all implants). AVR activity also increased over the study period. TAVI patients were older and had a higher mean logistic EuroSCORE than all AVR groups. The 30-day mortality rates were 2.1% for isolated AVR, 3.9% for AVR + CABG, 7.7% for AVR + other surgery and 6.2% for TAVI. In-hospital mortality has significantly improved for all groups. The 5-year survival rates were 82.6% for isolated AVR, 81.7% for AVR + CABG, 74.5% for AVR + other surgery and 46.1% for TAVI. The median PLOS after TAVI was similar to that of isolated AVR but shorter than that of the other AVR groups., Conclusions: Since the introduction of TAVI, there has been an increase in both TAVI and AVR activity. TAVIs now represent over 10% of all aortic valve implants. There are distinct differences between procedural groups with respect to patient risk factors. Outcomes for all procedural groups have improved, but long-term TAVI results are required before its role in the treatment of aortic stenosis can be fully defined., (© The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Objective: Minimally invasive aortic valve replacement (MIAVR) has been demonstrated as a safe and effective option but remains underused. We aimed to evaluate outcomes of isolated MIAVR compared with conventional aortic valve replacement (CAVR)., Methods: Data from The National Institute for Cardiovascular Outcomes Research (NICOR) were analyzed at seven volunteer centers (2006-2012). Primary outcomes were in-hospital mortality and midterm survival. Secondary outcomes were postoperative length of stay as well as cumulative bypass and cross-clamp times. Propensity modeling with matched cohort analysis was used., Results: Of 307 consecutive MIAVR patients, 151 (49%) were performed during the last 2 years of study with a continued increase in numbers. The 307 MIAVR patients were matched on a 1:1 ratio. In the matched CAVR group, there was no statistically significant difference in in-hospital mortality [MIAVR, 4/307,(1.3%); 95% confidence interval (CI), 0.4%-3.4% vs CAVR, 6/307 (2.0%); 95% CI, 0.8%-4.3%; P = 0.752]. One-year survival rates in the MIAVR and CAVR groups were 94.4% and 94.6%, respectively. There was no statistically significant difference in midterm survival (P = 0.677; hazard ratio, 0.90; 95% CI, 0.56-1.46). Median postoperative length of stay was lower in the MIAVR patients by 1 day (P = 0.009). The mean cumulative bypass time (94.8 vs 91.3 minutes; P = 0.333) and cross-clamp time (74.6 vs 68.4 minutes; P = 0.006) were longer in the MIAVR group; however, this was significant only in the cross-clamp time comparison., Conclusions: Minimally invasive aortic valve replacement is a safe alternative to CAVR with respect to operative and 1-year mortality and is associated with a shorter postoperative stay. Further studies are required in high-risk (logistic EuroSCORE > 10) patients to define the role of MIAVR.

Objectives: Social deprivation impacts on healthcare outcomes but is not included in the majority of cardiac surgery risk prediction models. The objective was to investigate geographical variations in social deprivation of patients undergoing cardiac surgery and identify whether social deprivation is an independent predictor of outcomes., Methods: National Adult Cardiac Surgery Audit data for coronary artery bypass graft (CABG), or valve surgery performed in England between April 2003 and March 2013, were analysed. Base hospitals in England were divided into geographical regions. Social deprivation was measured by quintile groups of the index of multiple deprivation (IMD) score with the first quintile group (Q1) being the least, and the last quintile group (Q5) the most deprived group. In-hospital mortality and midterm survival were analysed using mixed effects logistic, and stratified Cox proportional hazards regression models respectively., Results: 240,221 operations were analysed. There was substantial regional variation in social deprivation with the proportion of patients in IMD Q5 ranging from 34.5% in the North East to 6.5% in the East of England. Following adjustment for preoperative risk factors, patients undergoing all cardiac surgery in IMD Q5 were found to have an increased risk of in-hospital mortality relative to IMD Q1 (OR=1.13; 95%CI 1.03 to 1.24), as were patients undergoing isolated CABG (OR=1.19; 95%CI 1.03 to 1.37). For midterm survival, patients in IMD Q5 had an increased hazard in all groups (HRs ranged between 1.10 (valve+CABG) and 1.26 (isolated CABG)). For isolated CABG, the median postoperative length of stay was 6 and 7 days, respectively, for IMD Q1-Q4 and Q5., Conclusions: Significant regional variation exists in the social deprivation of patients undergoing cardiac surgery in England. Social deprivation is associated with an increased risk of in-hospital mortality and reduced midterm survival. These findings have implications for health service provision, risk prediction models and analyses of surgical outcomes., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Objectives: Biological valves are the most commonly implanted prostheses for aortic valve replacement (AVR) surgery in the UK. The aim of this study was to compare performance of porcine and bovine pericardial valves implanted in AVR surgery with respect to survival and reintervention-free survival in a retrospective observational study., Methods: Prospectively collected clinical data for all first-time elective and urgent AVRs with or without concomitant coronary artery bypass graft (CABG) surgery performed in England and Wales between April 2003 and March 2013 were extracted from the National Institute for Cardiovascular Outcomes Research database. Patient life status was tracked from the Office for National Statistics. Time-to-event analyses were performed using log-rank tests and Cox proportional hazards regression modelling with random effects/grouped frailty for responsible cardiac surgeons., Results: A total of 38,040 patients were included (64.9% bovine pericardial; 35.1% porcine). Patient characteristics were similar between the groups. The median follow-up was 3.6 years. There was no statistically significant difference in survival (P = 0.767) (the 10-year survival rates were 49.0 and 50.3% in the bovine pericardial and porcine groups, respectively) or reintervention-free survival. The adjusted hazard ratio for porcine valves was 0.98 (95% confidence interval 0.93-1.03). Sensitivity analysis in small valve sizes showed no difference in reintervention-free survival. After adjustment, there was some evidence of a protective effect for porcine valves in relatively younger patients (P = 0.075)., Conclusions: There were no differences in reintervention-free survival between bovine pericardial and porcine valves used in first-time AVR ± CABG up to a maximum of 10 years., (© The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

The parasite Fasciola hepatica is a major cause of economic loss to the agricultural community worldwide as a result of morbidity and mortality in livestock, including cattle. Cattle are the principle reservoir of verocytotoxigenic Escherichia coli O157 (VTEC O157), an important cause of disease in humans. To date there has been little empirical research on the interaction between F. hepatica and VTEC O157. It is hypothesised that F. hepatica, which is known to suppress type 1 immune responses and induce an anti-inflammatory or regulatory immune environment in the host, may promote colonisation of the bovine intestine with VTEC O157. Here we assess whether it is statistically feasible to augment a prospective study to quantify the prevalence of VTEC O157 in cattle in Great Britain with a pilot study to test this hypothesis. We simulate data under the framework of a mixed-effects logistic regression model in order to calculate the power to detect an association effect size (odds ratio) of 2. In order to reduce the resources required for such a study, we exploit the fact that the test results for VTEC O157 will be known in advance of testing for F. hepatica by restricting analysis to farms with a VTEC O157 sample prevalence of >0% and <100%. From a total of 270 farms (mean 27 cows per farm) that will be tested for VTEC O157, power of 87% can be achieved, whereby testing of F. hepatica would only be necessary for an expected 50 farms, thus considerably reducing costs. Pre-study sample size calculations are an important part of any study design. The framework developed here is applicable to the study of other co-infections., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

Toxoplasma gondii is a highly prevalent intracellular protozoan parasite that causes severe disease in congenitally infected or immunocompromised hosts. T. gondii is capable of invading immune cells and it has been suggested that the parasite harnesses the migratory pathways of these cells to spread through the body. Although in vitro evidence suggests that the parasite further enhances its spread by inducing a hypermotility phenotype in parasitized immune cells, in vivo evidence for this phenomenon is scarce. Here we use a physiologically relevant oral model of T. gondii infection, in conjunction with two-photon laser scanning microscopy, to address this issue. We found that a small proportion of natural killer (NK) cells in mesenteric lymph nodes contained parasites. Compared with uninfected 'bystander' NK cells, these infected NK cells showed faster, more directed and more persistent migratory behavior. Consistent with this, infected NK cells showed impaired spreading and clustering of the integrin, LFA-1, when exposed to plated ligands. Our results provide the first evidence for a hypermigratory phenotype in T. gondii-infected NK cells in vivo, providing an anatomical context for understanding how the parasite manipulates immune cell motility to spread through the host.

Background: Serum total cholesterol is one of the major targets for cardiovascular disease prevention. Statins are effective for cholesterol control in individual patients. At the population level, however, their contribution to total cholesterol decline remains unclear. The aim of this study was to quantify the contribution of statins to the observed fall in population mean cholesterol levels in England over the past two decades, and explore any differences between socioeconomic groups., Methods and Findings: This is a modelling study based on data from the Health Survey for England. We analysed changes in observed mean total cholesterol levels in the adult England population between 1991-92 (baseline) and 2011-12. We then compared the observed changes with a counterfactual 'no statins' scenario, where the impact of statins on population total cholesterol was estimated and removed. We estimated uncertainty intervals (UI) using Monte Carlo simulation, where confidence intervals (CI) were impractical. In 2011-12, 13.2% (95% CI: 12.5-14.0%) of the English adult population used statins at least once per week, compared with 1991-92 when the proportion was just 0.5% (95% CI: 0.3-1.0%). Between 1991-92 and 2011-12, mean total cholesterol declined from 5.86 mmol/L (95% CI: 5.82-5.90) to 5.17 mmol/L (95% CI: 5.14-5.20). For 2011-12, mean total cholesterol was lower in more deprived groups. In our 'no statins' scenario we predicted a mean total cholesterol of 5.36 mmol/L (95% CI: 5.33-5.40) for 2011-12. Statins were responsible for approximately 33.7% (95% UI: 28.9-38.8%) of the total cholesterol reduction since 1991-92. The statin contribution to cholesterol reduction was greater among the more deprived groups of women, while showing little socio-economic gradient among men., Conclusions: Our model suggests that statins explained around a third of the substantial falls in total cholesterol observed in England since 1991. Approximately two thirds of the cholesterol decrease can reasonably be attributed non-pharmacological determinants.

Background: Cardiopulmonary exercise testing (CPET) is increasingly used in the preoperative assessment of patients undergoing major surgery. The objective of this study was to investigate whether CPET can identify patients at risk of reduced survival after abdominal aortic aneurysm (AAA) repair., Methods: Prospectively collected data from consecutive patients who underwent CPET before elective open or endovascular AAA repair  (EVAR) at two tertiary vascular centres between January 2007 and October 2012 were analysed. A symptom-limited maximal CPET was performed on each patient. Multivariable Cox proportional hazards regression modelling was used to identify risk factors associated with reduced survival., Results: The study included 506 patients with a mean age of 73.4 (range 44-90). The majority (82.6%) were men and most (64.6%) underwent EVAR. The in-hospital mortality was 2.6%. The median follow-up was 26 months. The 3-year survival for patients with zero or one sub-threshold CPET value ([Formula: see text] at AT<10.2 ml kg(-1) min(-1), peak [Formula: see text]<15 ml kg(-1) min(-1) or [Formula: see text] at AT>42) was 86.4% compared with 59.9% for patients with three sub-threshold CPET values. Risk factors independently associated with survival were female sex [hazard ratio (HR)=0.44, 95% confidence interval (CI) 0.22-0.85, P=0.015], diabetes (HR=1.95, 95% CI 1.04-3.69, P=0.039), preoperative statins (HR=0.58, 95% CI 0.38-0.90, P=0.016), haemoglobin g dl(-1) (HR=0.84, 95% CI 0.74-0.95, P=0.006), peak [Formula: see text]<15 ml kg(-1) min(-1) (HR=1.63, 95% CI 1.01-2.63, P=0.046), and [Formula: see text] at AT>42 (HR=1.68, 95% CI 1.00-2.80, P=0.049)., Conclusions: CPET variables are independent predictors of reduced survival after elective AAA repair and can identify a cohort of patients with reduced survival at 3 years post-procedure. CPET is a potentially useful adjunct for clinical decision-making in patients with AAA., (© The Author 2014. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Objectives: To explore the relationship between in-hospital mortality following adult cardiac surgery and the time since primary clinical qualification for the responsible consultant cardiac surgeon (a proxy for experience)., Design: Retrospective analysis of prospectively collected national registry data over a 10-year period using mixed-effects multiple logistic regression modelling. Surgeon experience was defined as the time between the date of surgery and award of primary clinical qualification., Setting: UK National Health Service hospitals performing cardiac surgery between January 2003 and December 2012., Participants: All patients undergoing coronary artery bypass grafts and/or valve surgery under the care of a consultant cardiac surgeon., Main Outcome Measures: All-cause in-hospital mortality., Results: A total of 292,973 operations performed by 273 consultant surgeons (with lengths of service from 11.2 to 42.0 years) were included. Crude mortality increased approximately linearly until 33 years service, before decreasing. After adjusting for case-mix and year of surgery, there remained a statistically significant (p=0.002) association between length of service and in-hospital mortality (odds ratio 1.013; 95% CI 1.005-1.021 for each year of 'experience')., Conclusions: Consultant cardiac surgeons take on increasingly complex surgery as they gain experience. With this progression, the incidence of adverse outcomes is expected to increase, as is demonstrated in this study. After adjusting for case-mix using the EuroSCORE, we observed an increased risk of mortality in patients operated on by longer serving surgeons. This finding may reflect under-adjustment for risk, unmeasured confounding or a real association. Further research into outcomes over the time course of surgeon's careers is required., (© The Royal Society of Medicine.)

Objective/background: A number of contemporary risk prediction models for mortality following elective abdominal aortic aneurysm (AAA) repair have been developed. Before a model is used either in clinical practice or to risk-adjust surgical outcome data it is important that its performance is assessed in external validation studies., Methods: The British Aneurysm Repair (BAR) score, Medicare, and Vascular Governance North West (VGNW) models were validated using an independent prospectively collected sample of multicentre clinical audit data. Consecutive, data on 1,124 patients undergoing elective AAA repair at 17 hospitals in the north-west of England and Wales between April 2011 and March 2013 were analysed. The outcome measure was in-hospital mortality. Model calibration (observed to expected ratio with chi-square test, calibration plots, calibration intercept and slope) and discrimination (area under receiver operating characteristic curve [AUC]) were assessed in the overall cohort and procedural subgroups., Results: The mean age of the population was 74.4 years (SD 7.7); 193 (17.2%) patients were women and the majority of patients (759, 67.5%) underwent endovascular aneurysm repair. All three models demonstrated good calibration in the overall cohort and procedural subgroups. Overall discrimination was excellent for the BAR score (AUC 0.83, 95% confidence interval [CI] 0.76-0.89), and acceptable for the Medicare and VGNW models, with AUCs of 0.78 (95% CI 0.70-0.86) and 0.75 (95% CI 0.65-0.84) respectively. Only the BAR score demonstrated good discrimination in procedural subgroups., Conclusion: All three models demonstrated good calibration and discrimination for the prediction of in-hospital mortality following elective AAA repair and are potentially useful. The BAR score has a number of advantages, which include being developed on the most contemporaneous data, excellent overall discrimination, and good performance in procedural subgroups. Regular model validations and recalibration will be essential., (Copyright © 2014 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.)

Objective: Current guidelines recommend that most patients aged ≥65 years should undergo mitral valve replacement (MVR) using a biological prosthesis. The objectives of this study were to assess whether these guidelines are being followed in UK practice, and to investigate whether the guidelines are appropriate based on in-hospital mortality and mid-term survival., Methods: Data from the National Institute for Cardiovascular Outcomes Research Adult Cardiac Surgery Audit database from all National Health Service (NHS) hospitals and some private hospitals performing adult cardiac surgery in the UK between April 2001 and March 2011 were analysed. The overall cohort included 3862 patients aged ≥65 years who underwent first-time MVR. Propensity score matching and regression adjustment were used to compare outcomes between prosthesis groups., Results: The mean age was 73.0 years (SD 4.9) with 50% of patients having surgery with a mechanical prosthesis. This proportion decreased over the study period and with increasing patient age with marked variation between hospitals. In the propensity-matched cohort, in-hospital mortality in the biological group was 6.9%, and in the mechanical group it was 5.9% giving an unadjusted OR of 1.17 (95% CI 0.84 to 1.63). There was no significant difference in mid-term survival between the matched groups with an unadjusted HR for biological prosthesis of 1.08 (95% CI 0.93 to 1.24). Similar results were found when using regression adjustment on unmatched data., Conclusions: Current guidelines concerning age and mitral valve prosthesis choice are not being followed for patients aged ≥65 years. With regards to in-hospital and mid-term mortality, this study demonstrates that there is no difference between prosthesis types.