Non-vitamin K antagonist oral anticoagulants in atrial fibrillation accompanying mitral stenosis: the concept for a trial.

Patients at thromboembolic risk with non-valvular atrial fibrillation (AF) can now be managed either with a vitamin K antagonist (VKA) or with a fixed dose of a non-VKA oral anticoagulant (NOAC), while patients with valvular AF have been restricted to VKAs on the basis of a potentially higher risk and different mechanism of thrombosis, and the lack of sufficient data on the efficacy of NOACs. The terms 'non-valvular AF' and 'valvular AF' have not been however consistently defined. 'Valvular' AF has included any valvular disorder, including valve replacement and repair. In AF with rheumatic mitral disease, observational studies strongly suggest that VKA treatment is valuable. These patients have not been included in NOAC trials, but there is also no stringent argument to have excluded them. This is at sharp variance from patients with mechanical valves, also excluded from the pivotal Phase III trial comparing warfarin with NOACs, but in whom a single Phase II trial of dabigatran etexilate against VKA treatment was stopped prematurely because of increased rates of thromboembolism as well as increased bleeding associated with dabigatran. Until more data are available, such patients should be therefore managed with VKAs. We here propose an open-label randomized trial of one of the NOACs against the best of treatment available in regions of the world in which rheumatic heart disease is still highly prevalent, aiming at showing the superiority of the NOAC used against current standard treatment

Time-trends and treatment gaps in the antithrombotic management of patients with atrial fibrillation after percutaneous coronary intervention: Insights from the CHUM AF-STENT Registry.

BACKGROUND: The management of atrial fibrillation and flutter (AF) patients undergoing percutaneous coronary intervention (PCI) has undergone a rapid recent evolution. In 2016, the Canadian Cardiovascular Society (CCS) published expert recommendations to help guide clinicians in balancing bleeding and thrombotic risks in these patients. HYPOTHESIS: Antithrombotic regimen prescriptions for AF patients undergoing PCI evolved after the publication of the 2016 CCS AF guidelines. METHODS: A prospective cohort of AF patients undergoing PCI with placement of a coronary stent from a single tertiary academic center was analyzed for the recommended antithrombotic regimen at discharge. Prescribing behavior was compared between three time periods (Cohort A [2010-2011]; Cohort B [2014-2015]; Cohort C [2017]) using the χ2 test. In addition, antithrombotic management in Cohorts B and C were compared to guideline-recommended therapy. RESULTS: A total of 459 patients with AF undergoing PCI were identified. Clinical and procedural characteristics were similar between cohorts, with the exception of an increase in drug-eluting stent (DES) use over time (P < .01). Overall, the rate of oral anticoagulation (OAC) increased over time (P < .01), associated with an increase in nonvitamin K OAC prescription (P < .01) and a concomitant decrease in vitamin K antagonist prescription (P < .01). Despite this, the overall rate of anticoagulation remains below what would be predicted with perfect guideline compliance (75% vs 94%, P < .01). CONCLUSION: There has been a dramatic shift in clinical practice for AF patients requiring PCI, with increases in prescription of OAC even in the context of an increase in the use of DES. However, room for further practice optimization still exists

Simplified Cost Models For Underground Mine Evaluation: A Handbook for Quick Prefeasibility Cost Estimates

This handbook provides simplified cost models for evaluating underground mines. Regression analysis is used to generate capital and operating cost equations for each model in the form Y = AXB, where Y is the cost estimated and X is the assumed production capacity in tonnes per day. A and B are constants determined by the regression analysis. Equations are developed for operating costs in five subcategories: equipment operation, supplies, hourly labor, administration, and sundries. Subcategories for capital costs are: equipment purchase, preproduction underground excavation, surface facilities, engineering & management, contingency, and working capital. Cost models are developed for eight underground mining methods

901–37 Computer Implementation of Wavelet Decomposition of Signal Averaged Electrocardiograms

Simple spectral analysis of signal averaged electrocardiograms (SAECG) has been the subject of numerous studies. However, the approaches reported so far appear inferior to the gold-standard time-domain analysis of SAECG. At the same time, the limitations of the time-domain analysis are well known and suggest that a more complex spectral analysis of SAECG will be of clinical importance. One of the possibilities for a more complex spectral analysis of SAECG is the so called Wavelet Analysis (WA) which is a time-scale technique suitable for the detection of small transient signals even if they are hidden in large waves. It is obtained by expanding the signal on a set of functions resulting from translation (time) and dilatation (scale) of a socalled “analysing wavelet”. WA provides a bidimensional representation of the signal in function of time and scale.In order to apply WA to SAECG, a special software package written in Borland Pascal has been developed. The WA of the signal s(t) is computed according to the formula Sg(a,b)=∫-∞+∞(1/√a)g(t)s(t)dt, where parameter a corresponds to the dilatation and parameter b to the time shift. The package uses the Morlet wavelet g(t)=exp(iωt) exp(-t2/2) for ω&gt;=5.3. Empirically, 54 scales were chosen, defined by the scale parameter a=40×2-m, with m ranging from 0.95 to 3.6 with an increment of 0.05. The middle frequencies of the corresponding wavelets range from 250 to 40Hz. The package processes SAECG files in the standard ART format. To synthesise the information contained within all three wavelet transforms, a wavelet vector magnitude is obtained from the wavelets of three averaged X, Y, Z leads and computed as WM=(WX2+WY2+WZ2)1/2.The package has been employed in several studies which showed that (a) WA of SAECG is highly reproducible and (b) selected parameters of WA are superior to the time-domain analysis of SAECG when used for identification of survivors of acute myocardial infarction who are at high risk of sudden death and/or ventricular tachycardia. This comparison of WA and time domain analysis of SAECG used receiver operator and positive predictive characteristics which showed highly significant differences

Effects of Rivaroxaban on Biomarkers of Coagulation and Inflammation: A Post Hoc Analysis of the X-VeRT Trial.

Introduction  This X-VeRT (eXplore the efficacy and safety of once-daily oral riVaroxaban for the prevention of caRdiovascular events in patients with nonvalvular aTrial fibrillation scheduled for cardioversion) substudy evaluated the effects of treatment with rivaroxaban or a vitamin-K antagonist (VKA) on levels of biomarkers of coagulation (D-dimer, thrombin-antithrombin III complex [TAT] and prothrombin fragment [F1.2]) and inflammation (high sensitivity C-reactive protein [hs-CRP] and high-sensitivity interleukin-6 [hs-IL-6]) in patients with atrial fibrillation (AF) who were scheduled for cardioversion and had not received adequate anticoagulation at baseline (defined as, in the 21 days before randomization: no oral anticoagulant; international normalized ratio <2.0 with VKA treatment; or <80% compliance with non-VKA oral anticoagulant treatment). Methods  Samples for biomarker analysis were taken at baseline ( n  = 958) and treatment completion (42 days after cardioversion; n  = 918). The influence of clinical characteristics on baseline biomarker levels and the effect of treatment on changes in biomarker levels were evaluated using linear and logistic models. Results  Baseline levels of some biomarkers were significantly associated with type of AF (D-dimer and hs-IL-6) and with history of congestive heart failure (hs-CRP, D-dimer, and hs-IL-6). Rivaroxaban and VKA treatments were associated with reductions from baseline in levels of D-dimer (-32.3 and -37.6%, respectively), TAT (-28.0 and -23.1%, respectively), hs-CRP (-12.5 and -17.9%, respectively), and hs-IL-6 (-9.2 and -9.8%, respectively). F1.2 levels were reduced from baseline in patients receiving a VKA (-53.0%) but not in those receiving rivaroxaban (2.7%). Conclusion  Anticoagulation with rivaroxaban reduced levels of key inflammation and coagulation biomarkers to a similar extent as VKAs, with the exception of F1.2. Further investigation to confirm the value of these biomarkers in patients with AF is merited

Left atrial appendage closure: A new technique for clinical practice

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801-4 Prognostic Implications of QT and QU Interval Measures in Acute Myocardial Infarction

Prolongation of the QT interval corrected using Bazett's formula (QTc) has been reported as a marker for increased risk of arrhythmic events after acute myocardial infarction (AMI). However, the QU interval changes have not been examined. At the same time, QU interval may be of clinical significance, especially in the light of recent experimental evidence linking the U wave with the subpopulation of the so-called M cells within myocardial wall. To evaluate prognostic significance of QT and QU interval measures in AMI, we studied 512 survivors of acute phase of their first myocardial infarction. Patients with conduction defects and drugs likely to affect QT measures were noT included into the analysis. The following intervals were estimated in all the measurable leads on a standard predischarge 12-lead ECG (25 mm/sec paper speed) using a digitizing pad—mean RR, mean and max QT, and mean QU. All QT and QU intervals were subsequently corrected for heart rate using Bazett's formula. At one year follow-up, 23 patients (Group I. 19 male. mean age 58.7±8.9 years) suffered arrhythmic events (VT/VF or sudden cardiac death). This subset of patients was compared with arrhythmia-free group of 489 subjects (Group II, 385 male, mean age 56.1±9.2 years). Statistical analysis was performed using unpaired t-test and ANOVA, results are expressed as mean±SD.GroupQT meanQTc meanQT maxQTc maxQU meanQUc meanI358.7±31.5426.6±30.7396.5±38.5472.8±40.3459.5±58.7535.2±41.3II387.3±44.1423.9±24421.7±51.5467.9±79.1552.0±73.9585.7±55.1p&lt;0.002NS0.02NS0.0010.01The significant difference in QU and QUc, but not in QT intervals persisted even after elimination of the effect of heart rate (ANOVA: p&lt;0.007 and 0.011, respectively).ConclusionThe differences in the QT but not QU interval measures in the 2 groups can be explained by differing heart rates. Shorter QU interval seemed to identify patients at risk of arrhythmic events after AMI. The pathophysiological basis for this finding is not clear, but could be related to differences in the subpopulation of M cells within myocardial wall

ESC CardioMed

Reprinted with permission from: Eur Heart J. 2018; 19: 959–961Reprinted with permission from: Eur Heart J. 2018; 19: 959–96