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Background— The residual Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery (SYNTAX) Score is an objective measure of the degree and complexity of residual stenosis after percutaneous coronary intervention (PCI). Methods and Results— In the randomized PCI cohort of the SYNTAX Trial (n=903), the baseline and residual SYNTAX Scores were calculated. Subjects with a residual SYNTAX Score of 0 were defined as having undergone complete revascularization (CR), and a residual SYNTAX Score >0 as incomplete revascularization (ICR). Five-year clinical outcomes were stratified by CR and ICR (tertiles of the residual SYNTAX Score: >0–4, >4–8, and >8). In the PCI cohort, the mean baseline and residual SYNTAX Scores were 28.4±11.5 and 4.5±6.9, respectively. The mean Δ SYNTAX Score (representative of the burden of disease removed by PCI) was 23.8±10.9. The residual SYNTAX Score was distributed as follows: CR, 0 (n=386, 42.7%); ICR, >0 to 4 (n=184, 20.4%), >4 to 8 (n=167, 18.5%), >8 (n=153, 16.9%). A progressively higher residual SYNTAX Score was shown to be a surrogate marker of increasing clinical comorbidity and anatomic complexity. Subjects with CR or residual SYNTAX Scores ≤8 had comparable 5-year mortality (CR, 8.5%; residual SYNTAX Score >0–4, 8.7%; >4–8, 11.4%; P =0.60). A residual SYNTAX Score >8 was associated with 35.3% all-cause mortality at 5-years ( P <0.001). Stratified analyses in the predefined medical treated diabetic and left main subgroups yielded similar results. Conclusions— The residual SYNTAX Score was shown to be a powerful indicator of 5-year mortality in the SYNTAX Trial. The residual SYNTAX Score may aid in determining a reasonable level of revascularization. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00114972.

OBJECTIVES: Estimate the causes and risk of death, specifically seizure related, in children followed from onset of epilepsy and to contrast the risk of seizure-related death with other common causes of death in the population. METHODS: Mortality experiences from 4 pediatric cohorts of newly diagnosed patients were combined. Causes of death were classified as seizure related (including sudden unexpected death [SUDEP]), natural causes, nonnatural causes, and unknown. RESULTS: Of 2239 subjects followed up for &gt;30 000 person-years, 79 died. Ten subjects with lethal neurometabolic conditions were ultimately excluded. The overall death rate (per 100 000 person-years) was 228; 743 in complicated epilepsy (with associated neurodisability or underlying brain condition) and 36 in uncomplicated epilepsy. Thirteen deaths were seizure-related (10 SUDEP, 3 other), accounting for 19% of all deaths. Seizure-related death rates were 43 overall, 122 for complicated epilepsy, and 14 for uncomplicated epilepsy. Death rates from other natural causes were 159, 561, and 9, respectively. Of 48 deaths from other natural causes, 37 were due to pneumonia or other respiratory complications. CONCLUSIONS: Most excess death in young people with epilepsy is not seizure-related. Mortality is significantly higher compared with the general population in children with complicated epilepsy but not uncomplicated epilepsy. The SUDEP rate was similar to or higher than sudden infant death syndrome rates. In uncomplicated epilepsy, sudden and seizure-related death rates were similar to or higher than rates for other common causes of death in young people (eg, accidents, suicides, homicides). Relating the risk of death in epilepsy to familiar risks may facilitate discussions of seizure-related mortality with patients and families.

Genetic College Many genomic elements in humans are associated with behavior, including educational attainment. In a genome-wide association study including more than 100,000 samples, Rietveld et al. (p. 1467 , published online 30 May; see the Perspective by Flint and Munafò ) looked for genes related to educational attainment in Caucasians. Small genetic effects at three loci appeared to impact educational attainment.

Background Tools for the prediction of atrial fibrillation ( AF ) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results Individual‐level data from 3 large cohorts in the U nited S tates (Atherosclerosis Risk in Communities [ ARIC ] study, the Cardiovascular Health Study [ CHS ], and the Framingham Heart Study [ FHS ]), including 18 556 men and women aged 46 to 94 years (19% A frican A mericans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study ( AGES ) and the Rotterdam Study ( RS ). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI , 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI , 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI , −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable ( AGES C‐statistic, 0.664; 95% CI , 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI , 0.664 to 0.747) and calibration was adequate. Conclusion A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the U nited S tates and E urope.

ABSTRACTVenous thromboembolism (VTE) is a common, heritable disease resulting in high rates of hospitalization and mortality. Yet few associations between VTE and genetic variants, all in the coagulation pathway, have been established. To identify additional genetic determinants of VTE, we conducted a two‐stage genome‐wide association study (GWAS) among individuals of European ancestry in the extended cohorts for heart and aging research in genomic epidemiology (CHARGE) VTE consortium. The discovery GWAS comprised 1,618 incident VTE cases out of 44,499 participants from six community‐based studies. Genotypes for genome‐wide single‐nucleotide polymorphisms (SNPs) were imputed to approximately 2.5 million SNPs in HapMap and association with VTE assessed using study‐design appropriate regression methods. Meta‐analysis of these results identified two known loci, in F5 and ABO. Top 1,047 tag SNPs (P ≤ 0.0016) from the discovery GWAS were tested for association in an additional 3,231 cases and 3,536 controls from three case‐control studies. In the combined data from these two stages, additional genome‐wide significant associations were observed on 4q35 at F11 (top SNP rs4253399, intronic to F11) and on 4q28 at FGG (rs6536024, 9.7 kb from FGG; P < 5.0 × 10−13 for both). The associations at the FGG locus were not completely explained by previously reported variants. Loci at or near SUSD1 and OTUD7A showed borderline yet novel associations (P < 5.0 × 10−6) and constitute new candidate genes. In conclusion, this large GWAS replicated key genetic associations in F5 and ABO, and confirmed the importance of F11 and FGG loci for VTE. Future studies are warranted to better characterize the associations with F11 and FGG and to replicate the new candidate associations.

Stimulated by a recent controversy regarding pressure drops predicted in a giant aneurysm with a proximal stenosis, the present study sought to assess variability in the prediction of pressures and flow by a wide variety of research groups. In phase I, lumen geometry, flow rates, and fluid properties were specified, leaving each research group to choose their solver, discretization, and solution strategies. Variability was assessed by having each group interpolate their results onto a standardized mesh and centerline. For phase II, a physical model of the geometry was constructed, from which pressure and flow rates were measured. Groups repeated their simulations using a geometry reconstructed from a micro-computed tomography (CT) scan of the physical model with the measured flow rates and fluid properties. Phase I results from 25 groups demonstrated remarkable consistency in the pressure patterns, with the majority predicting peak systolic pressure drops within 8% of each other. Aneurysm sac flow patterns were more variable with only a few groups reporting peak systolic flow instabilities owing to their use of high temporal resolutions. Variability for phase II was comparable, and the median predicted pressure drops were within a few millimeters of mercury of the measured values but only after accounting for submillimeter errors in the reconstruction of the life-sized flow model from micro-CT. In summary, pressure can be predicted with consistency by CFD across a wide range of solvers and solution strategies, but this may not hold true for specific flow patterns or derived quantities. Future challenges are needed and should focus on hemodynamic quantities thought to be of clinical interest.