1,720,999 research outputs found
Applications of artificial intelligence and machine learning in heart failure
No full text: Machine learning (ML) is a sub-field of artificial intelligence that uses computer algorithms to extract patterns from raw data, acquire knowledge without human input, and apply this knowledge for various tasks. Traditional statistical methods that classify or regress data have limited capacity to handle large datasets that have a low signal-to-noise ratio. In contrast to traditional models, ML relies on fewer assumptions, can handle larger and more complex datasets, and does not require predictors or interactions to be pre-specified, allowing for novel relationships to be detected. In this review, we discuss the rationale for the use and applications of ML in heart failure, including disease classification, early diagnosis, early detection of decompensation, risk stratification, optimal titration of medical therapy, effective patient selection for devices, and clinical trial recruitment. We discuss how ML can be used to expedite implementation and close healthcare gaps in learning healthcare systems. We review the limitations of ML, including opaque logic and unreliable model performance in the setting of data errors or data shift. Whilst ML has great potential to improve clinical care and research in HF, the applications must be externally validated in prospective studies for broad uptake to occur
Predictors, treatments, and outcomes of do-not-resuscitate status in acute myocardial infarction patients (from a nationwide inpatient cohort study)
No full textLittle is known about how frequently do-not-resuscitate (DNR) orders are placed in patients with acute myocardial infarction (AMI), the types of patients in which they are placed, treatment strategies or clinical outcomes of such patients. Using the United States (US) National Inpatient Sample (NIS) database from 2015 to 2018, we identified 2,767,549 admissions that were admitted to US hospitals and during the hospitalization received a principle diagnosis of AMI, of which 339,270 (12.3%) patients had a DNR order (instigated both preadmission and during in-hospital stay). Patients with a DNR status were older (median age 83 vs 65, p < 0.001), more likely to be female (53.4% vs 39.3%, p < 0.001) and White (81.0% vs 73.3%, p < 0.001). Predictors of DNR status included comorbidities such as heart failure (OR: 1.47, 95% CI: 1.45 to 1.48), dementia (OR: 2.53, 95% CI: 2.50 to 2.55), and cancer. Patients with a DNR order were less likely to undergo invasive management or be discharged home (13.5% vs 52.8%), with only 1/3 receiving palliative consultation. In hospital mortality (32.7% vs 4.6%, p < 0.001) and MACCE (37.1% vs 8.8%, p < 0.001) were higher in the DNR group. Factors independently associated with in-hospital mortality among patients with a DNR order included a STEMI presentation (OR: 2.90, 95% CI: 2.84 to 2.96) and being of Black (OR: 1.29, 95% CI: 1.26 to 1.33), Hispanic (OR: 1.36, 95% CI: 1.32 to 1.41) or Asian/Pacific Islander (OR: 1.56, 95% CI:1.49-race. In conclusion, AMI patients with a DNR status were older, multimorbid, less likely to receive invasive management, with only one third of patients with DNR status referred for palliative care. (c) 2021 Elsevier Inc. All rights reserved. (Am J Cardiol 2021;159:8-18
In HF with mitral regurgitation, adding transcatheter mitral valve repair to medical therapy improved renal outcomes at 2 y
Full text linkThe Expansion of Medical Assistance in Dying in the COVID-19 Pandemic Era and Beyond: Implications for Vulnerable Canadians
Full text linkThis is the Version of Record (VOR) of an article originally published in the CJGIM on May 30, 2022 (https://cjgim.ca/index.php/csim/article/view/586). It is distributed under the Creative Commons License CC-BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/). No changes were made to the original publication.In 2015, the Canadian parliament passed a law permitting adults to request Medical Assistance in Dying (MAiD) when they have a grievous, irremediable medical condition that causes unbearable suffering and their natural death is reasonably foreseeable. Following a constitutional challenge, a Quebec lower court, ruled in the Truchon vs. Canada AG case that the restriction to a reasonably foreseeable death is an unjustifiable impingement on the right to life, liberty, and security of the person and the right to equality. In response, the government expanded the MAiD law in March 2021 through Bill C-7 to include those who are not approach- ing their natural death. Bill C-7 is a potentially harmful approach to justice for vulnerable groups such as the elderly, disabled, or those with chronic illnesses. The COVID-19 pandemic has highlighted serious problems with how we care for the vulnerable members of our society. In this article, we explore what has gone wrong and what has raised serious concerns, while proposing potential options to consider when developing new laws, systems, and processes to improve societal equity.HGCV received research funding from the Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada
Urban–rural disparities in diabetes-related mortality in the USA 1999–2019
No full textAIMS/HYPOTHESIS: Our study aimed to examine the trends in diabetes-related mortality in urban and rural areas in the USA over the past two decades. METHODS: We examined the trends in diabetes-related mortality (as the underlying or a contributing cause of death) in urban and rural areas in the USA between 1999 and 2019, using the CDC WONDER Multiple Cause of Death database. We estimated the 20 year trends of the age-adjusted mortality rate (AAMR) per 100,000 population in urban vs rural counties. RESULTS: The AAMR of diabetes was higher in rural than urban areas across all subgroups. In urban areas, there was a significant decrease in the AAMR of diabetes as the underlying (−16.7%) and contributing (−13.5%) cause of death (p(trend)<0.001), which was not observed in rural areas (+2.6%, +8.9%, respectively). AAMRs of diabetes decreased more significantly in female compared with male individuals, both in rural and urban areas. Among people younger than 55 years old, there was a temporal increase in diabetes-related AAMR (+13.8% to +65.2%). While the diabetes-related AAMRs of American Indian patients decreased in all areas (−19.8% to −40.5%, all p(trend)<0.001), diabetes-related AAMRs of Black and White patients decreased significantly in urban (−26.6% to −28.3% and −10.7% to −15.4%, respectively, all p(trend)<0.001) but not rural areas (−6.5% to +1.8%, +2.4% to +10.6%, respectively, p(trend) NS, NS, NS and <0.001). CONCLUSIONS/INTERPRETATION: The temporal decrease in diabetes-related mortality in the USA has been observed only in urban areas, and mainly among female and older patients. A synchronised effort is needed to improve cardiovascular health indices and healthcare access in rural areas and to decrease diabetes-related mortality. GRAPHICAL ABSTRACT: [Image: see text
Predicting Risk of Cardiotoxic Effects in Breast Cancer: Are We There Yet?
No full textPeople with breast cancer are at increased risk of cardiovascular disease, myocardial injury, and heart failure (HF) due to underlying risk factors, a proinflammatory milieu, and cancer therapy–related cardiovascular toxic effects (CTR-CVT).1 Of the therapies for breast cancer, human epidermal growth factor receptor-2 (ERBB2)–targeted therapies, such as trastuzumab, and anthracyclines, such as doxorubicin, have the most well-described associations with both decline in left ventricular ejection fraction (LVEF), and clinical HF.2,3 Given that cardiotoxic effects are not always reversible and can result in significant morbidity and mortality, current European Society of Cardiology guidelines recommend risk stratification before starting potentially cardiotoxic anticancer therapy in all patients with cancer (Class 1B) to identify patients who are at high risk of developing CTR-CVT.4 Several risk prediction models have been developed to estimate adverse cardiac outcomes among patients with breast cancer. However, the design, performance, and methodological rigor of the risk prediction models have not been assessed systematically
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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