Interleukin‐1 Blockade Inhibits the Acute Inflammatory Response in Patients With ST‐Segment–Elevation Myocardial Infarction

Background ST‐segment–elevation myocardial infarction is associated with an intense acute inflammatory response and risk of heart failure. We tested whether interleukin‐1 blockade with anakinra significantly reduced the area under the curve for hsCRP (high sensitivity C‐reactive protein) levels during the first 14 days in patients with ST‐segment–elevation myocardial infarction (VCUART3 [Virginia Commonwealth University Anakinra Remodeling Trial 3]). Methods and Results We conducted a randomized, placebo‐controlled, double‐blind, clinical trial in 99 patients with ST‐segment–elevation myocardial infarction in which patients were assigned to 2 weeks treatment with anakinra once daily (N=33), anakinra twice daily (N=31), or placebo (N=35). hsCRP area under the curve was significantly lower in patients receiving anakinra versus placebo (median, 67 [interquartile range, 39–120] versus 214 [interquartile range, 131–394] mg·day/L; P\u3c0.001), without significant differences between the anakinra arms. No significant differences were found between anakinra and placebo groups in the interval changes in left ventricular end‐systolic volume (median, 1.4 [interquartile range, −9.8 to 9.8] versus −3.9 [interquartile range, −15.4 to 1.4] mL; P=0.21) or left ventricular ejection fraction (median, 3.9% [interquartile range, −1.6% to 10.2%] versus 2.7% [interquartile range, −1.8% to 9.3%]; P=0.61) at 12 months. The incidence of death or new‐onset heart failure or of death and hospitalization for heart failure was significantly lower with anakinra versus placebo (9.4% versus 25.7% [P=0.046] and 0% versus 11.4% [P=0.011], respectively), without difference between the anakinra arms. The incidence of serious infection was not different between anakinra and placebo groups (14% versus 14%; P=0.98). Injection site reactions occurred more frequently in patients receiving anakinra (22%) versus placebo (3%; P=0.016). Conclusions In patients presenting with ST‐segment–elevation myocardial infarction, interleukin‐1 blockade with anakinra significantly reduces the systemic inflammatory response compared with placebo. Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT01950299

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

BACKGROUND: Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. METHODS: We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. RESULTS: The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. CONCLUSIONS: Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation

Determination of Baroreflex Sensitivity during the Modified Oxford Maneuver by Trigonometric Regressive Spectral Analysis

BACKGROUND: Differences in spontaneous and drug-induced baroreflex sensitivity (BRS) have been attributed to its different operating ranges. The current study attempted to compare BRS estimates during cardiovascular steady-state and pharmacologically stimulation using an innovative algorithm for dynamic determination of baroreflex gain. METHODOLOGY/PRINCIPAL FINDINGS: Forty-five volunteers underwent the modified Oxford maneuver in supine and 60° tilted position with blood pressure and heart rate being continuously recorded. Drug-induced BRS-estimates were calculated from data obtained by bolus injections of nitroprusside and phenylephrine. Spontaneous indices were derived from data obtained during rest (stationary) and under pharmacological stimulation (non-stationary) using the algorithm of trigonometric regressive spectral analysis (TRS). Spontaneous and drug-induced BRS values were significantly correlated and display directionally similar changes under different situations. Using the Bland-Altman method, systematic differences between spontaneous and drug-induced estimates were found and revealed that the discrepancy can be as large as the gain itself. Fixed bias was not evident with ordinary least products regression. The correlation and agreement between the estimates increased significantly when BRS was calculated by TRS in non-stationary mode during the drug injection period. TRS-BRS significantly increased during phenylephrine and decreased under nitroprusside. CONCLUSIONS/SIGNIFICANCE: The TRS analysis provides a reliable, non-invasive assessment of human BRS not only under static steady state conditions, but also during pharmacological perturbation of the cardiovascular system

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.CNPq Brazilian Foundation for Scientific and Technological DevelopmentCNPq - Brazilian Foundation for Scientific and Technological Development [150653/2008-5

Drug-Eluting Stents in Patients with Chronic Kidney Disease: A Prospective Registry Study

BACKGROUND: Chronic kidney disease (CKD) is strongly associated with adverse outcomes after percutaneous coronary intervention (PCI). There are limited data on the effectiveness of drug-eluting stents (DES) in patients with CKD. METHODOLOGY/PRINCIPAL FINDINGS: Of 3,752 consecutive patients enrolled in the Guthrie PCI Registry between 2001 and 2006, 436 patients with CKD - defined as a creatinine clearance <60 mL/min - were included in this study. Patients who received DES were compared to those who received bare metal stents (BMS). Patients were followed for a mean duration of 3 years after the index PCI to determine the prognostic impact of stent type. Study end-points were all-cause death, myocardial infarction (MI), target vessel revascularization (TVR), stent thrombosis (ST) and the composite of major adverse cardiovascular events (MACE), defined as death, MI or TVR. Patients receiving DES in our study, by virtue of physician selection, had more stable coronary artery disease and had lower baseline risk of thrombotic or restenotic events. Kaplan-Meier estimates of proportions of patients reaching the end-points were significantly lower for DES vs. BMS for all-cause death (p = 0.0008), TVR (p = 0.029) and MACE (p = 0.0015), but not MI (p = 0.945) or ST (p = 0.88). Multivariable analysis with propensity adjustment demonstrated that DES implantation was an independent predictor of lower rates of all-cause death (hazard ratio [HR] 0.48, 95% confidence interval [CI] 0.25-0.92), TVR (HR 0.50, 95% CI 0.27-0.94) and MACE (HR 0.62, 95% CI 0.41-0.94). CONCLUSIONS: In a contemporary PCI registry, selective use of DES in patients with CKD was safe and effective in the long term, with lower risk of all-cause death, TVR and MACE and similar risk of MI and ST as compared with BMS. The mortality benefit may be a result of selection bias and residual confounding, or represent a true finding; a hypothesis that warrants clarification by randomized clinical trials

Cocoa, Hazelnuts, Sterols and Soluble Fiber Cream Reduces Lipids and Inflammation Biomarkers in Hypertensive Patients: A Randomized Controlled Trial

Cocoa, mixed with other food ingredients, intake can have beneficial effects on cardiovascular disease (CVD) biomarkers. We compared the effects of 4 cocoa cream products on some of these biomarkers.In this multi-centered, randomized, controlled, double-blind, parallel trial, volunteers (n = 113; age range: 43-65 years) who were pre-hypertensive, stage-1 hypertensive and hypercholesterolemic received one of 4 cocoa cream products (13 g/unit; 1 g cocoa/unit, 6 units/d; 465 Kcal/d) added to a low saturated fat diet for 4 weeks. The groups were: A) (n = 28), cocoa cream considered as control; B) (n = 28), cocoa+hazelnut cream (30 g/d hazelnuts); C) (n = 30), cocoa+hazelnuts+phytosterols (2 g/d); and D) (n = 27), cocoa+hazelnuts+phytosterols+soluble fiber (20 g/d) the patented "LMN product". Primary outcome measures were BP, LDL-c, apolipoprotein B-100 (Apo B), ApoB/ApoA ratio, oxidized LDL (oxLDL) and high-sensitive C-reactive protein (hsCRP) determined at baseline and post-cocoa cream product intake. Statistical analysis used was ANCOVA or mixed models (in case of repeated measurements), with baseline observation included as a covariate. After 4 weeks, compared to product A, product C reduced LDL-c by 11.2%, Apo B by 8.1% and ApoB/ApoA ratio by 7.8% (P = 0.01). LMN decreased LDL-c by 9.2%, Apo B-100 by 8.5%, ApoB/ApoA ratio by 10.5%, hsCRP by 33.4% and oxLDL by 5.9% (P = 0.01). Surprisingly, even "control" product A reduced systolic BP (-7.89 mmHg; 95%CI: -11.45 to -4.3) and diastolic BP (-5.54 mmHg; 95%CI: -7.79 to -3.29). The BP reductions were similar with the other 3 products. Limitations of the study are that the trial period was relatively short and that a better "BP control" product would have been preferable.The creams (particularly the LMN) have anti-inflammatory and antioxidant effects in addition to lowering LDL-c, Apo B and ApoB/ApoA ratio. Thus, the soluble fiber effects amplified with sterols (as contained in the cocoa creams) provide new dietary therapeutic perspectives.Clinicaltrials.gov NCT00511420

The Communicability of Graphical Alternatives to Tabular Displays of Statistical Simulation Studies

Simulation studies are often used to assess the frequency properties and optimality of statistical methods. They are typically reported in tables, which may contain hundreds of figures to be contrasted over multiple dimensions. To assess the degree to which these tables are fit for purpose, we performed a randomised cross-over experiment in which statisticians were asked to extract information from (i) such a table sourced from the literature and (ii) a graphical adaptation designed by the authors, and were timed and assessed for accuracy. We developed hierarchical models accounting for differences between individuals of different experience levels (under- and post-graduate), within experience levels, and between different table-graph pairs. In our experiment, information could be extracted quicker and, for less experienced participants, more accurately from graphical presentations than tabular displays. We also performed a literature review to assess the prevalence of hard-to-interpret design features in tables of simulation studies in three popular statistics journals, finding that many are presented innumerately. We recommend simulation studies be presented in graphical form

A Prospective Study of Aspirin Use and the Risk of Gastrointestinal Bleeding in Men

Data regarding the influence of dose and duration of aspirin use on risk of gastrointestinal bleeding are conflicting.We conducted a prospective cohort study of 32,989 men enrolled in the Health Professionals Follow-up Study (HPFS) in 1994 who provided biennial aspirin data. We estimated relative risk of major gastrointestinal bleeding requiring hospitalization or a blood transfusion.During 14 years of follow-up, 707 men reported an episode of major gastrointestinal bleeding over 377,231 person-years. After adjusting for risk factors, regular aspirin use (≥2 times/week) had a multivariate relative risk (RR) of gastrointestinal bleeding of 1.32 (95% confidence interval [CI], 1.12-1.55) compared to non-regular use. The association was particularly evident for upper gastrointestinal bleeding (multivariate RR, 1.49; 95% CI, 1.16-1.92). Compared to men who denied any aspirin use, multivariate RRs of upper gastrointestinal bleeding were 1.05 (95% CI 0.71-1.52) for men who used 0.5-1.5 standard tablets/week, 1.31 (95% CI 0.88-1.95) for 2-5 aspirin/week, 1.63 (95% CI, 1.15-2.32) for 6-14 aspirin/week and 2.40 (95% CI, 1.10-5.22) for >14 aspirin/week (P(trend)<0.001). The relative risk also appeared to be dose-dependent among short-term users <5 years; P(trend)<.001) and long-term users (≥5 years; P(trend) = 0.015). In contrast, after controlling for dose, increasing duration of use did not appear to be associated with risk (P(trend) = 0.749).Regular aspirin use increases the risk of gastrointestinal bleeding, especially from the upper tract. However, risk of bleeding appears to be more strongly related to dose than to duration of use. Risk of bleeding should be minimized by using the lowest effective dose among short-term and long-term aspirin users

Expansion of the Multi-Link Frontier™ Coronary Bifurcation Stent: Micro-Computed Tomographic Assessment in Human Autopsy and Porcine Heart Samples

BACKGROUND: Treatment of coronary bifurcation lesions remains challenging, beyond the introduction of drug eluting stents. Dedicated stent systems are available to improve the technical approach to the treatment of these lesions. However dedicated stent systems have so far not reduced the incidence of stent restenosis. The aim of this study was to assess the expansion of the Multi-Link (ML) Frontier™ stent in human and porcine coronary arteries to provide the cardiologist with useful in-vitro information for stent implantation and selection. METHODOLOGY/PRINCIPAL FINDINGS: Nine ML Frontier™ stents were implanted in seven human autopsy heart samples with known coronary artery disease and five ML Frontier™ stents were implanted in five porcine hearts. Proximal, distal and side branch diameters (PD, DD, SBD, respectively), corresponding opening areas (PA, DA, SBA) and the mean stent length (L) were assessed by micro-computed tomography (micro-CT). PD and PA were significantly smaller in human autopsy heart samples than in porcine heart samples (3.54±0.47 mm vs. 4.04±0.22 mm, p = 0.048; 10.00±2.42 mm(2) vs. 12.84±1.38 mm(2), p = 0.034, respectively) and than those given by the manufacturer (3.54±0.47 mm vs. 4.03 mm, p = 0.014). L was smaller in human autopsy heart samples than in porcine heart samples, although data did not reach significance (16.66±1.30 mm vs. 17.30±0.51 mm, p = 0.32), and significantly smaller than that given by the manufacturer (16.66±1.30 mm vs. 18 mm, p = 0.015). CONCLUSIONS/SIGNIFICANCE: Micro-CT is a feasible tool for exact surveying of dedicated stent systems and could make a contribution to the development of these devices. The proximal diameter and proximal area of the stent system were considerably smaller in human autopsy heart samples than in porcine heart samples and than those given by the manufacturer. Special consideration should be given to the stent deployment procedure (and to the follow-up) of dedicated stent systems, considering final intravascular ultrasound or optical coherence tomography to visualize (and if necessary optimize) stent expansion

Regression with Empirical Variable Selection: Description of a New Method and Application to Ecological Datasets

Despite recent papers on problems associated with full-model and stepwise regression, their use is still common throughout ecological and environmental disciplines. Alternative approaches, including generating multiple models and comparing them post-hoc using techniques such as Akaike's Information Criterion (AIC), are becoming more popular. However, these are problematic when there are numerous independent variables and interpretation is often difficult when competing models contain many different variables and combinations of variables. Here, we detail a new approach, REVS (Regression with Empirical Variable Selection), which uses all-subsets regression to quantify empirical support for every independent variable. A series of models is created; the first containing the variable with most empirical support, the second containing the first variable and the next most-supported, and so on. The comparatively small number of resultant models (n = the number of predictor variables) means that post-hoc comparison is comparatively quick and easy. When tested on a real dataset – habitat and offspring quality in the great tit (Parus major) – the optimal REVS model explained more variance (higher R2), was more parsimonious (lower AIC), and had greater significance (lower P values), than full, stepwise or all-subsets models; it also had higher predictive accuracy based on split-sample validation. Testing REVS on ten further datasets suggested that this is typical, with R2 values being higher than full or stepwise models (mean improvement = 31% and 7%, respectively). Results are ecologically intuitive as even when there are several competing models, they share a set of “core” variables and differ only in presence/absence of one or two additional variables. We conclude that REVS is useful for analysing complex datasets, including those in ecology and environmental disciplines