30 research outputs found

    Prehospital 12-Lead Electrocardiogram within 60 Minutes Differentiates Proximal versus Nonproximal Left Anterior Descending Artery Myocardial Infarction

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    <p>Introduction: Acute anterior myocardial infarctions caused by proximal left anterior descending (LAD) artery occlusions are associated with a higher morbidity and mortality. Early identification of high-risk patients via the 12-lead electrocardiogram (ECG) could assist physicians and emergency response teams in providing early and aggressive care for patients with anterior ST-elevation myocardial infarctions (STEMI). Approximately 25% of US hospitals have primary percutaneous coronary intervention (PCI) capability for the treatment of acute myocardial infarctions. Given the paucity of</p> <p>hospitals capable of PCI, early identification of more severe myocardial infarction may prompt</p> <p>emergency medical service routing of these patients to PCI-capable hospitals. We sought to determine if the 12 lead ECG is capable of predicting proximal LAD artery occlusions.</p> <p>Methods: In a retrospective, post-hoc analysis of the Pre-Hospital Administration of Thrombolytic Therapy with Urgent Culprit Artery Revascularization pilot trial, we compared the ECG findings of</p> <p>proximal and nonproximal LAD occlusions for patients who had undergone an ECG within 180 minutes of symptom onset.</p> <p>Results: In this study, 72 patients had anterior STEMIs, with ECGs performed within 180 minutes of symptom onset. In patients who had undergone ECGs within 60 minutes (n¼35), the mean sum of ST elevation (STE) in leads V1 through V6 plus ST depression (STD) in leads II, III, and aVF was 19.2 mm for proximal LAD occlusions and 11.7 mm for nonproximal LAD occlusions (P¼0.007). A sum STE in V1 through V6 plus STD in II, III, and aVF of at least 17.5 mm had a sensitivity of 52.3%, specificity of 92.9%, positive predictive value of 91.7%, and negative predictive value of 56.5% for proximal LAD occlusions. When the ECG was performed more than 60 minutes after symptom onset (n¼37), there was no significant difference in ST-segment deviation between the 2 groups.</p> <p>Conclusion: The sum STE (V1-V6) and STD (II, III, aVF) on a 12-lead ECG can be used to predict proximal LAD occlusions if performed within the first hour of symptom onset. This should be considered a high-risk finding and may prompt prehospital direction of such patients to PCI-capable hospitals. [West J Emerg Med. 2011;12(4):408–413.]</p

    Mapping the absence : A theological critique of posthumanist influences in marketing and consumer research

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    In this study, we critically examine the ongoing adoption of various posthumanist influences into the fields of marketing and consumer research from a theological perspective. By conducting a theological-historical assessment, we propose that it is not posthuman notions of human/technology relations, nor their broader context in the emerging non-representational paradigms, that mark radically new disruptions in the continuing restructuring of the disciplines of marketing and consumer research. Instead, we argue that what is taking place is an implicit adherence to a contemporary form of age-old Christian dogma. As a radical conjecture, we thus propose that an identification of certain similarities between Christian dogma and the grounds for various posthumanist frameworks suggest that posthuman thought may well herald the global dissemination of a far more elusive, authoritarian, and hegemonic system than that which posthumanists typically claim to have abandoned. Consequently, we elaborate on implications to developments in marketing thought.Peer reviewe

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
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