A neural system dynamics modeling platform and its applications in randomized controlled trial data analysis

Initial trials comparing stenting with balloon angioplasty demonstrated improved angiographic and clinical outcomes with the former.1–3 The main clinical problem with bare metal stents (BMS) became the development of in-stent restenosis.4–6 Early data suggested that drug-eluting stents (DES) could mitigate, if not abolish, this problem.7–9 Since the approval of DES, these devices have become the predominant stents used in percutaneous coronary interventions, regardless of indication. As of September 2007, the Cypher sirolimus-eluting stent (SES) (Cordis Johnson & Johnson, Miami Lakes, Fla) had been deployed in >3 million patients worldwide,10 and the millionth Taxus paclitaxel-eluting stent (PES) (Boston Scientific, Natick, Mass) was implanted as of January 2005.11 Over the past 2 years, numerous reports of very late stent thrombosis (ST) with first-generation DES have surfaced. This highly morbid complication and data suggesting that death and myocardial infarction (MI) may be more common with DES12,13 have altered the focus of trials and registries working to determine optimal DES use. There is a hope that second-generation DES will be less prone to ST as a result of differences in drug, stent design, and polymer. Medtronic, Inc (Minneapolis, Minn) presented safety and efficacy data to a public meeting of the US Food and Drug Administration (FDA) Circulatory System Devices Panel (CSDP) in October 2007 on its Endeavor zotarolimus-eluting stent (ZES), seeking approval for the indication of treating de novo native coronary lesions ≤27 mm with reference vessel diameters of 2.5 to 3.5 mm. The FDA asked the CSDP to determine whether the data presented demonstrated a reasonable level of safety and effectiveness, with clinical benefits clearly outweighing short- and long-term risks of ZES use. Important efficacy end points included ischemia-driven target lesion revascularization (TLR) or target vessel revascularization (TVR); safety end points included death, MI, and ST. The …

The objective of this study was to clarify the incidence and predictors of early and late target lesion revascularization (TLR) after everolimus-eluting stent (EES) implantation in actual clinical practice. Several clinical studies have reported the incidence and predictors of TLR after EES implantation. However, detailed features of early and late TLR are unknown. We analyzed the clinical data of patients who underwent EES implantation between January 2010 and December 2011 at 22 institutions in Japan (Tokyo-MD PCI study). Patients who underwent ischemia-driven TLR (ID-TLR) were grouped according to the number of years elapsed since stent placement, and incidence and correlations between clinical factors were analyzed. Statistical analysis was performed for 1,899 patients and 2,305 lesions. The mean age was 70.0 ± 9.9 years, and the median follow-up period was 1,281 days (IQR: 762-1,440 days). The incidence of ID-TLR was 2.7% at 1 year and 5.4% at 4 years. After 2 years, the ID-TLR rates plateaued. The independent predictors of ID-TLR occurring within 2 years were hemodialysis, triple vessel disease, restenotic lesion, and ostial lesions. The independent predictors of ID-TLR between 2 and 4 years were diabetes mellitus and peripheral artery disease. The ID-TLR rates leveled off after 2 years. Furthermore, the predictors of ID-TLR that occurred within 2 years of EES implantation differed from those that occurred later than 2 years. © 2017 Wiley Periodicals, Inc.

168 Impact of Connecticut’s Good Samaritan Laws in Preventing Opioid Overdose Deaths – An Applied System Dynamics Approach

Everolimus-eluting bioresorbable vascular scaffolds versus everolimus-eluting metallic stents: a meta-analysis of randomised controlled trials

Everolimus-eluting stent (EES) is effective for treating in-stent restenosis (ISR). However, the long-term incidence of target lesion revascularization (TLR) is unknown. Further, the role of post-intervention minimal stent area (MSA) measured by intravascular ultrasound (IVUS) in TLR is unknown in this setting. Overall, 223 ISR lesions (192 patients) that were treated with EES between 2010 and 2016 were analyzed retrospectively. Lesions were divided into two groups according to the post-intervention MSA [ ≤ 5.3 mm: 72 lesions (67 patients), and > 5.3 mm: 151 lesions (138 patients)]. The cut-off point was determined on the basis of receiver operating characteristic curve analysis. The cumulative 5-year incidence of TLR was significantly higher in the group with MSA of 5.3 mm or less than in the group with MSA more than 5.3 mm (15.8 and 7.2%, P = 0.01). After adjusting for confounders, the excess risk of the group with MSA of 5.3 mm or less relative to the group with MSA more than 5.3 mm for TLR remained significant [hazard ratio: 3.07, 95% confidence interval (CI): 1.17-8.51, P = 0.02]. Using multivariate logistic regression analysis, we identified female sex (odds ratio: 2.39, 95% CI: 1.06-5.49, P = 0.04) and stent size of 3.0 mm or less (odds ratio: 13.43, 95% CI: 6.23-32.38, P < 0.0001) as independent predictors of MSA of 5.3 mm or less. EES implantation for ISR was associated with an acceptable rate of TLR through long-term follow-up. Postintervention MSA of 5.3 mm or less was associated independently with a higher risk for TLR.

Although drug-eluting stents and intensive secondary prevention have contributed to improved outcomes after percutaneous coronary intervention (PCI), repeat revascularization remains relatively common in contemporary practice. We used data from the multicenter Evaluation of Drug-Eluting Stents and Ischemic Events registry to evaluate the relative frequency and timing of staged revascularization, target lesion revascularization (TLR), and other nontarget revascularization during the first year after contemporary PCI. Patients with staged revascularization, TLR, and other unplanned procedures (elsewhere in the target vessel or in other coronary arteries) were evaluated in time-dependent models using Kaplan-Meier life-table estimation. Predictors of TLR and unplanned revascularization at nontarget sites were identified using logistic regression. Between July 2004 to June 2007, 10 144 patients undergoing PCI were enrolled at 55 US hospitals, of whom 86% were treated with at least 1 drug-eluting stent. Twelve percent required repeat revascularization within the first year (3% staged; 9% unplanned). More than 75% of staged revascularizations were performed <30 days after index PCI, although there was significant variation in this practice across hospitals (range, 0%-54%). TLR occurred in 4.5% of patients, with higher hazard rates between 2 to 9 months after PCI, whereas the risk of unplanned non-TLR (4.4% cumulative incidence) was constant over time. Among unselected patients undergoing PCI in the drug-eluting stent era, the incidence of repeat revascularization at 1 year is ≈12%. Among unplanned procedures, only half are performed for TLR. To achieve further improvements in PCI outcomes, future efforts should concentrate as much on identifying ischemia-producing lesions and intensifying secondary prevention therapies as on the prevention of restenosis.

BackgroundBifurcation lesions account for 20% of all percutaneous coronary interventions and represent a complex subset which are associated with lower procedural success and higher rates of restenosis. The ideal bifurcation technique, however, remains elusive.Methods and ResultsExtensive search of the literature was performed to pull data from randomized clinical trials that met predetermined inclusion criteria. Conventional meta‐analysis produced pooled relative risk (RR) and 95% CI of 2‐stent technique versus provisional stent on prespecified outcomes. Both frequentist and Bayesian network meta‐analyses were performed to compare bifurcation techniques. A total of 8318 patients were included from 29 randomized clinical trials. Conventional meta‐analysis showed no significant differences in all‐cause mortality, cardiac death, major adverse cardiac events, myocardial infarction, stent thrombosis, target lesion revascularization, and target vessel revascularization between 2‐stent techniques and provisional stenting. Frequentist network meta‐analysis revealed that double kissing crush was associated with lower cardiac death (RR, 0.57; 95% CI, 0.38–0.84), major adverse cardiac events (RR, 0.50; 95% CI, 0.39–0.64), myocardial infarction (RR, 0.60; 95% CI, 0.39–0.90), stent thrombosis (RR, 0.50; 95% CI, 0.28–0.88), target lesion revascularization, and target vessel revascularization when compared with provisional stenting. Double kissing crush was also superior to other 2‐stent techniques, including T‐stent or T and protrusion, dedicated bifurcation stent, and culotte.ConclusionsDouble kissing crush was associated with lower risk of cardiac death, major adverse cardiac events, myocardial infarction, stent thrombosis, target lesion revascularization, and target vessel revascularization compared with provisional stenting and was superior to other 2‐stent techniques. Superiority of 2‐stent strategy over provisional stenting was observed in subgroup meta‐analysis stratified to side branch lesion length ≥10 mm.

Sealing of Coronary Perforations With a Second-Generation Covered Stent Graft - Results From the PAST-PERF Registry

Paclitaxel-Coated Balloon Versus Uncoated Balloon Angioplasty for Coronary In-Stent Restenosis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

To assess the long-term outcomes of patients treated with sirolimus-eluting Stentys stent in a real-life setting. Few data regarding the safety and effectiveness of self-apposing sirolimus-eluting Stentys stent are available. 278 patients (30% stable coronary artery disease, 70% acute coronary syndromes, and 54% on unprotected left main) treated with sirolimus eluting Stentys stent were retrospectively included in the self-aPposing, bAlloon-delivered, siRolimus-eluting stent for the Treatment of the coronary Artery disease multicenter registry. Major adverse cardiovascular events (MACE, a composite of cardiac death, myocardial infarction, target lesion revascularization, stent thrombosis) were the primary end-point, single components of MACE were the secondary ones. After 13 months (interquartile range 5-32), MACE was 14%. Stent thrombosis occurred in 3.9% of the patients (2.5% definite stent thrombosis and 1.4% probable stent thrombosis), 66% of them presenting with ST-segment elevation myocardial infarction (STEMI) at admission. Cardiovascular death, target lesion revascularization and myocardial infarction was 4.7%, 8.3%, and 7.2%, respectively. At multivariate analysis, risk of MACE was increased by diabetes (hazard ratios 4.76; P = 0.002) but was not affected by the indication leading to sirolimus-eluting Stentys stent implantation (marked vessel tapering vs. coronary ecstasies, hazard ratios 0.74, P = 0.71). Sirolimus-eluting Stentys stent may represent a potential solution for specific coronary anatomies such as bifurcation, ectasic, or tapered vessels. Risk of stent thrombosis appears related to clinical presentation with STEMI and to anatomic features, stressing the importance of the use of intracoronary imaging for self-expandable stents implantation.

Highlights From the Circulation Family of Journals.

Complex processes resulting from interaction of multiple elements can rarely be understood by analytical scientific approaches alone; additional, mathematical models of system dynamics are required. This insight, which disciplines like physics have embraced for a long time already, is gradually gaining importance in the study of cognitive processes by functional neuroimaging. In this field, causal mechanisms in neural systems are described in terms of effective connectivity. Recently, dynamic causal modelling (DCM) was introduced as a generic method to estimate effective connectivity from neuroimaging data in a Bayesian fashion. One of the key advantages of DCM over previous methods is that it distinguishes between neural state equations and modality-specific forward models that translate neural activity into a measured signal. Another strength is its natural relation to Bayesian model selection (BMS) procedures. In this article, we review the conceptual and mathematical basis of DCM and its implementation for functional magnetic resonance imaging data and event-related potentials. After introducing the application of BMS in the context of DCM, we conclude with an outlook to future extensions of DCM. These extensions are guided by the long-term goal of using dynamic system models for pharmacological and clinical applications, particularly with regard to synaptic plasticity.

Biodegradable polymer biolimus-eluting stents (BP-BES) are third-generation drug-eluting stents (DES) composed of biodegradable polymers that may improve prognosis after percutaneous coronary intervention (PCI). After five years of follow-up, BP-BES showed conflicting results compared to durable polymer drug-eluting stents (DP-DES). We performed a meta-analysis of the outcomes of studies on BP-BES and DP-DES after percutaneous coronary intervention (PCI) at five years of follow-up. Eligible studies were retrieved from PubMed, Embase and the Cochrane Library and reported the results of all-cause mortality, myocardial infarction (MI), target lesion revascularization (TLR), target vessel revascularization (TVR) and stent thrombosis (ST) at five years of follow-up. Five studies of a total of 4687 patients were included in the meta-analysis. At five years of follow-up, BP-BES was associated with lower rates of major adverse cardiac events (MACE) (OR = 0.83, 95%CI = [0.71, 0.97]), TLR (OR = 0.77, 95%CI = [0.62, 0.96]) and ST (OR = 0.60, 95%CI = [0.43 to 0.84]), whereas no significant differences in mortality, MI, or TVR rates were detected. Our results demonstrated that at five years of follow-up, BP-BES can significantly reduce the risk of MACE, TLR and ST, which indicate that safety and efficacy were increased after PCI.

This paper describes a multi-level system dynamics (SD) / discrete event simulation (DES) approach for assessing planning and scheduling problems within an aviation training continuum. The aviation training continuum is a complex system, consisting of multiple aviation schools interacting through interschool student and instructor flows that are affected by external triggers such as resource availability and the weather. SD was used to model the overall training continuum at a macro level to ascertain relationships between system entities. SD also assisted in developing a shared understanding of the training continuum, which involves constructing the definitions of the training requirements, resources and policy objectives. An end-to-end model of the continuum is easy to relate to, while dynamic visualisation of system behaviour provides a method for exploration of the model. DES was used for micro level exploration of an individual school within the training continuum to capture the physical aspects of the system including resource capacity requirements, bottlenecks and student waiting times. It was also used to model stochastic events such as weather and student availability. DES has the advantage of being able to represent system variability and accurately reflect the limitations imposed on a system by resource constraints. Through sharing results between the models, we demonstrate a multi-level approach to the analysis of the overall continuum. The SD model provides the school’s targeted demand to the DES model. The detailed DES model is able to assess schedules in the presence of resource constraints and variability and provide the expected capacity of a school to the high level SD model, subjected to constraints such as instructor availability or budgeted number of training systems. The SD model allows stakeholders to assess how policy and planning affect the continuum, both in the short and the long term. The development of this approach permits moving the analysis of the continuum between SD and DES models as appropriate for given system entities, scales and tasks. The resultant model outcomes are propagated between the continuum and the detailed DES model, iteratively generating an assessment of the entire set of plans and schedule across the continuum. Combining data and information between SD and DES models and techniques assures relevance to the stakeholder needs and effective problem scoping and scaling that can also evolve with dynamic architecture and policy requirements. An example case study shows the combined use of the two models and how they are used to evaluate a typical scenario where increased demand is placed on the training continuum. The multi-level approach provides a high level indication of training requirements to the model of the new training school, where the detailed model indicates the resources required to achieve those particular student levels.

Many problematic outcomes in agricultural and food systems have important dynamic dimensions and arise due to underlying system structure. Thus, understanding the linkages between system structure and dynamic behavior often is important for the design and implementation of interventions to achieve sustained improvements. System Dynamics (SD) modeling represents system structure using stock-flow-feedback structures expressed as systems of differential equations solved by numerical integration methods. SD methods also encompass a broader methodological approach that emphasizes model structural development and data inputs to replicate one of a limited number of problematic behavioral modes, anticipates dynamic complexity and focuses on feedback processes arising from endogenous system elements. A variety of data sources may be used in SD model development, and parametric sensitivity analysis with SD models can determine priority information needs in feedback-rich systems when data are lacking. Although numerous applications of SD modeling to agriculture exist, the approach is underutilized as a useful tool for research, instruction and programmatic development. This presentation highlights key elements of SD modeling using two examples from animal agriculture at different scales. A dynamic version of the Cornell Net Carbohydrate and Protein System (CNCPS) that represents outcomes for an individual dairy cow is formulated as an SD model, and illustrates the benefits of the SD approach in animal nutrition research and for farm-level nutritional management decisions. At a very different scale, an SD model of the Brazilian dairy supply chain (farms, processing and consumers) illustrates the country-level impacts of efforts to improve cow productivity and how impacts differ if productivity improvement occurs on small farms rather than large farms. The presentation concludes with recommendations to increase awareness and training is SD methods to enhance its appropriate use in research and instruction.