Recovery of distal coronary flow reserve in LAD and LCx after Y-Graft intervention assessed by transthoracic echocardiography

<p>Abstract</p> <p>Background</p> <p>Y- graft (Y-G) is a graft formed by the Left Internal Mammary Artery (LIMA) connected to the Left Anterior Descending Artery (LAD) and by a free Right Internal Mammary Artery (RIMA) connected to LIMA and to a Marginal artery of Left Circumflex Artery (LCx). Aim of the work was to study the flow of this graft during a six months follow-up to assess whether the graft was able to meet the request of all the left coronary circulation, and to assess whether it could be done by evaluation of coronary flow reserve (CFR).</p> <p>Methods</p> <p>In 13 consecutive patients submitted to Y-G (13 men), CFR was measured in distal LAD and in distal LCx from 1 week after , every two months, up to six months after operation (a total of 8 tests for each patient) by means of transthoracic echocardiography (TTE) and Adenosine infusion (140 mcg/kg/min for 3-6 min). A Sequoia 256, Acuson-Siemens, was used. Contrast was used when necessary (Levovist 300 mg/ml solution at a rate of 0,5-1 ml/min). Max coronary flow diastolic velocity post-/pre-test ≥2 was considered normal CFR.</p> <p>Results</p> <p>Coronary arteriography revealed patency of both branches of Y-G after six months. Accuracy of TTE was 100% for LAD and 85% for LCx. Feasibility was 100% for LAD and 85% for LCx. CFR improved from baseline in LAD (2.21 ± 0.5 to 2.6 ± 0.5, p = 0.03) and in LCx (1.7 ± 1 to 2.12 ± 1, p = 0.05). CFR was under normal at baseline in 30% of patients <it>vs </it>8% after six months in LAD (p = 0.027), and in 69% of patients <it>vs </it>30% after six months in LCx (p = 0.066).</p> <p>Conclusion</p> <p>CFR in Y-G is sometimes reduced in both left territories postoperatively but it improves at six months follow-up. A follow-up can be done non-invasively by TTE and CFR evaluation.</p

Distal left circumflex coronary artery flow reserve recorded by transthoracic Doppler echocardiography: a comparison with Doppler-wire

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European position paper on the management of patients with patent foramen ovale. General approach and left circulation thromboembolism

The presence of a patent foramen ovale (PFO) is implicated in the pathogenesis of a number of medical conditions; however, the subject remains controversial and no official statements have been published. This interdisciplinary paper, prepared with involvement of eight European scientific societies, aims to review the available trial evidence and to define the principles needed to guide decision making in patients with PFO. In order to guarantee a strict process, position statements were developed with the use of a modified grading of recommendations assessment, development, and evaluation (GRADE) methodology. A critical qualitative and quantitative evaluation of diagnostic and therapeutic procedures was performed, including assessment of the risk/benefit ratio. The level of evidence and the strength of the position statements of particular management options were weighed and graded according to predefined scales. Despite being based often on limited and non-randomised data, while waiting for more conclusive evidence, it was possible to conclude on a number of position statements regarding a rational general approach to PFO management and to specific considerations regarding left circulation thromboembolism. For some therapeutic aspects, it was possible to express stricter position statements based on randomised trials. This position paper provides the first largely shared, interdisciplinary approach for a rational PFO management based on the best available evidence

Letter by Pristipino et al Regarding Article, "Potentially Large yet Uncertain Benefits: A Meta-analysis of Patent Foramen Ovale Closure Trials

[No abstract available

Predictive clustering learning algorithms for stroke patients discharge planning

Stroke patients discharge planning is a complex task that could be carried out by the use of a suitable decision support system. Such a platform should be based on unsupervised machine learning algorithms to reach the best results. More specifically, in this kind of prediction task clustering learning algorithms seem to perform better than the other unsupervised models. These algorithms are able to independently subdivide the treated clinical cases into groups, and they can serve to discover interesting correlations among the clinical variables taken into account and to improve the prediction accuracy of the treatment outcome. This work aims to compare the prediction accuracy of a particular clustering learning algorithm, the Growing Neural Gas, with the prediction accuracy of other supervised and unsupervised algorithms used in stroke patients discharge planning. This machine learning model is also able to accurately identify the input space topology. In other words it is characterized by the ability to independently select a subset of attributes to be taken into consideration in order to correctly perform any predictive task