9 research outputs found

    Efficacy of two different self-expanding nitinol stents for atherosclerotic femoropopliteal arterial disease (SENS-FP trial): study protocol for a randomized controlled trial

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    BACKGROUND: There have been few randomized control trials comparing the incidence of stent fracture and primary patency among different self-expanding nitinol stents to date. The SMART™ CONTROL stent (Cordis Corp, Miami Lakes, Florida, United States) has a peak-to-valley bridge and inline interconnection, whereas the COMPLETE™-SE stent (Medtronic Vascular, Santa Rosa, California, United States) crowns have been configured to minimize crown-to-crown interaction, increasing the stent's flexibility without compromising radial strength. Further, the 2011 ESC (European society of cardiology) guidelines recommend that dual antiplatelet therapy with aspirin and a thienopyridine such as clopidogrel should be administered for at least one month after infrainguinal bare metal stent implantation. Cilostazol has been reported to reduce intimal hyperplasia and subsequent repeat revascularization. To date, there has been no randomized study comparing the safety and efficacy of two different antiplatelet regimens, clopidogrel and cilostazol, following successful femoropopliteal stenting. METHODS/DESIGN: The primary purpose of our study is to examine the incidence of stent fracture and primary patency between two different major representative self-expanding nitinol stents (SMART™ CONTROL versus COMPLETE™-SE) in stenotic or occlusive femoropopliteal arterial lesion. The secondary purpose is to examine whether there is any difference in efficacy and safety between aspirin plus clopidogrel versus aspirin plus cilostazol for one month following stent implantation in femoropopliteal lesions. This is a prospective, randomized, multicenter trial to assess the efficacy of the COMPLETE™-SE versus SMART™ CONTROL stent for provisional stenting after balloon angioplasty in femoropopliteal arterial lesions. The study design is a 2x2 randomization design and a total of 346 patients will be enrolled. The primary endpoint of this study is the rate of binary restenosis in the treated segment at 12 months after intervention as determined by catheter angiography or duplex ultrasound. DISCUSSION: This trial will provide powerful insight into whether the design of the COMPLETE™-SE stent is more fracture-resistant or effective in preventing restenosis compared with the SMART™ CONTROL stent. Also, it will determine the efficacy and safety of aspirin plus clopidogrel versus aspirin plus cilostazol in patients undergoing stent implantation in femoropopliteal lesions. TRIAL REGISTRATION: Registered on 2 April 2012 with the National Institutes of Health Clinical Trials Registry (ClinicalTrials.gov identifier# NCT01570803)

    25th annual computational neuroscience meeting: CNS-2016

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    The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

    Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

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    Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
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