Management of atherosclerotic plaque in left internal mammary artery graft five years after angiographic patency: A case report

BACKGROUND: The left internal mammary artery (LIMA) has demonstrated excellent long-term patency rates when used as a bypass conduit with complications usually occurring in the early postoperative period. The rapid development of de-novo atherosclerosis in a previously non-diseased LIMA, subsequently leading to an acute coronary syndrome (ACS) is rarely encountered. CASE SUMMARY: A 67-year-old man with history of triple coronary artery bypass graft (8 years ago) presented to our hospital with an ACS. He had undergone angiography 5 years ago to investigate episodic chest pain and imaging of the LIMA at the time did not demonstrate the atherosclerotic process. Emergent angiography demonstrated a severe diffuse stenosis in the proximal to mid segment of the LIMA, with embolization of a moderate sized thrombus to the distal skip segment. The LIMA stenosis was characterised by overlying haziness, consistent with acute plaque rupture, associated with residual luminal thrombus. The patient was managed with antithrombotic therapy to reduce the thrombus burden until repeat angiography after 72 h. At repeat angiography, the thrombus burden was substantially reduced at the distal skip segment as well as at the proximal to mid LIMA with the demonstration of multiple plaque cavities. This lesion was predilated and a 2.75 mm × 33 mm everolimus-eluting stent was implanted to a final diameter of 3.0 mm. The patient made a good clinical recovery and was discharged after 6 d. CONCLUSION: This case highlights the rapid and late development of atherosclerosis in a graft 5 years after documented patency and the importance for consideration of expectant thrombus management

Boosting the HONG network

This paper gives a brief description of a hierarchical architecture (HONG) that has been described in Atukorale and Suganthan (Neurocomputing 35 (2000) 165). The learning algorithm it uses is a mixed unsupervised/supervised method with most of the learning being unsupervised. The architecture generates multiple classifications for every data pattern presented, and combines them to obtain the final classification. The main objective of this paper is to show how boosting can be used to improve the performance of the HONG classifier

Benchmarking Optimization-Based Energy Disaggregation Algorithms

Energy disaggregation (ED), with minimal infrastructure, can create energy awareness and thus promote energy efficiency by providing appliance-level consumption information. However, ED is highly ill-posed and gets complicated with increase in number and type of devices, similarity between devices, measurement errors, etc. To design, test, and benchmark ED algorithms, the availability of open-access energy consumption datasets is crucial. Most datasets in the literature suit data-intensive pattern-based ED algorithms. Recently, optimization-based ED algorithms that only require information regarding the operational states of the devices are being developed. However, the lack of standard datasets and appropriate evaluation metrics is hindering the development of reproducible state-of-the-art optimization-based ED algorithms. Therefore, in this paper, we propose a dataset with multiple instances that are representative of the different challenges posed by ED in practice. Performance indicators to empirically evaluate different optimization-based ED algorithms are summarized. In addition, baseline simulation results of the state-of-the-art optimization-based ED algorithms are presented. The developed dataset, summarization of different metrics, and baseline results are expected to provide a platform for researchers to develop novel optimization-based frameworks, in general, and evolutionary computation-based frameworks in particular to solve ED

Benchmarking Optimization-Based Energy Disaggregation Algorithms

Energy disaggregation (ED), with minimal infrastructure, can create energy awareness and thus promote energy efficiency by providing appliance-level consumption information. However, ED is highly ill-posed and gets complicated with increase in number and type of devices, similarity between devices, measurement errors, etc. To design, test, and benchmark ED algorithms, the availability of open-access energy consumption datasets is crucial. Most datasets in the literature suit data-intensive pattern-based ED algorithms. Recently, optimization-based ED algorithms that only require information regarding the operational states of the devices are being developed. However, the lack of standard datasets and appropriate evaluation metrics is hindering the development of reproducible state-of-the-art optimization-based ED algorithms. Therefore, in this paper, we propose a dataset with multiple instances that are representative of the different challenges posed by ED in practice. Performance indicators to empirically evaluate different optimization-based ED algorithms are summarized. In addition, baseline simulation results of the state-of-the-art optimization-based ED algorithms are presented. The developed dataset, summarization of different metrics, and baseline results are expected to provide a platform for researchers to develop novel optimization-based frameworks, in general, and evolutionary computation-based frameworks in particular to solve ED

The Syntax score predicts peri-procedural myocardial necrosis during percutaneous coronary intervention.

BACKGROUND: Peri-procedural myocardial injury (PPI) during percutaneous coronary intervention (PCI) is common and associated with a poor outcome. No reliable angiographic or clinical predictors of PPI exist. We evaluated the ability of the SYNTAX score (SXscore), Gensini score, American Heart Association/American College of Cardiology (AHA/ACC) and Society for Cardiovascular Angiography and Intervention (SCAI) classifications to predict PPI. METHODS: Consecutive patients were included from two existing databases of PCI. Patients with coronary bypass grafts or instent restenosis were excluded. PPI was defined as troponin I elevation (>1.0 microg/L) at 6-24 h post-PCI. Delayed enhancement magnetic resonance imaging distinguished PPI territory in patients undergoing multi-vessel PCI. Quantitative coronary angiography was performed blinded to PPI. In total, 100 patients underwent PCI to 122 vessels. PPI occurred in 20/100 (20.0%) patients. RESULTS: Mean patient SXscore was higher in patients with PPI (20.6 vs. 12.4, p = 0.0001), however Gensini score was not significantly different (34.2 vs. 27.3, p = 0.15). Mean vessel SXscore was higher in vessels associated with PPI (12.1 vs. 7.6, p = 0.002), but not different for vessel Gensini score (16.2 vs. 13.6, p = 0.42). No vessels with AHA type A or B1 lesions were associated with PPI. Higher AHA scores (B2 and C) were associated with PPI (chi2 for trend 11.6, p = 0.0007). SCAI scores were not predictive of PPI (chi2 for trend 3.6, p = 0.06). By ROC analysis, a patient SXscore of > or = 17 predicted PPI with a sensitivity of 75.0% and specificity of 70.0%. CONCLUSION: Higher SXscores are predictive of myocardial injury, whilst AHA type A and B1 lesions have a high negative predictive value for PPI

Myocardial injury following coronary artery surgery versus angioplasty (MICASA): a randomised trial using biochemical markers and cardiac magnetic resonance imaging.

AIMS: To compare the frequency and extent of Troponin I and late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) defined injury following PCI compared with CABG in patients with multivessel and/or left main coronary artery disease (CAD), and interpret these finding in light of the new ESC/ACCF/AHA/WHF Task Force definitions for necrosis and infarction. METHODS AND RESULTS: Prospective, registered, single centre randomised controlled trial. Eighty patients with 3 vessel CAD (≥ 50% stenoses), or 2 vessel CAD including a type C lesion in the LAD, and/or left main disease were enrolled. Mean SYNTAX and EuroSCOREs were similar for both groups. Forty patients underwent PCI with drug eluting stents and 39 underwent CABG (one died prior to CABG). In the PCI group 6/38 (15.8%) patients had LGE, compared with 9/32 (28.1%) CABG patients (p = 0.25). Using the new Task Force definitions, necrosis occurred in 30/40 (75%) PCI patients and 35/35 (100%) CABG patients (p = 0.001), whilst infarction occurred in 30/40 (75%) PCI patients and 9/32 (28.1%) CABG patients (p = 0.0001). CONCLUSIONS: Periprocedural necrosis according to the Task Force definition was significantly lower in the PCI group, and universal in the CABG group. The incidence and extent of CMR defined infarction following PCI did not differ compared with CABG. This demonstrates that PCI can achieve revascularisation in complex patients without increased procedural myocardial damage