Percutaneous coronary intervention in the elderly: changes in case-mix and periprocedural outcomes in 31758 patients treated between 2000 and 2007

<p>Background: The elderly account for an increasing proportion of the population and have a high prevalence of coronary heart disease. Percutaneous coronary intervention (PCI) is the most common method of revascularization in the elderly. We examined whether the risk of periprocedural complications after PCI was higher among elderly (age ≥75 years) patients and whether it has changed over time.</p> <p>Methods and Results: The Scottish Coronary Revascularization Register was used to undertake a retrospective cohort study on all 31 758 patients undergoing nonemergency PCI in Scotland between April 2000 and March 2007, inclusive. There was an increase in the number and percentage of PCIs undertaken in elderly patients, from 196 (8.7%) in 2000 to 752 (13.9%) in 2007. Compared with younger patients, the elderly were more likely to have multivessel disease, multiple comorbidity, and a history of myocardial infarction or coronary artery bypass grafting (χ2 tests, all P<0.001). The elderly had a higher risk of major adverse cardiovascular events within 30 days of PCI (4.5% versus 2.7%, χ2 test P<0.001). Over the 7 years, there was a significant increase in the proportion of elderly patients who had multiple comorbidity (χ2 test for trend, P<0.001). Despite this, the underlying risk of complications did not change significantly over time either among the elderly (χ2 test for trend, P=0.142) or overall (χ2 test for trend, P=0.083).</p> <p>Conclusions: Elderly patients have a higher risk of periprocedural complications and account for an increasing proportion of PCIs. Despite this, the risk of complications after PCI has not increased over time.</p&gt

Body Image in Collegiate Male Athletes: Education and Awareness on an Underexplored Topic

Body image involves perceptions and attitudes toward one’s own physical appearance (Phillips & deMan, 2010). Although female athletes have been given the most empirical attention, body image is also critical to the male athlete experience. The ideal male body is associated with leanness and muscularity (e.g., Baghurst 2009). Beyond attempting to meet societal expectations, male athletes may also experience pressures to maintain an ideal physique for their sport. For example, wrestlers may need to cut weight (Marttinen et al., 2003) while football players may need to increase size (Chatterton & Petrie, 2013). Although body image may be positive in many instances, some male athletes may experience body dissatisfaction or develop a psychiatric condition called muscle dysmorphia (e.g., Morgan, 2000). The purpose of this presentation is to discuss the importance of body image among male athletes, the potential pressures to alter one’s body in male athletics, and strategies for prevention

These are not the k-mers you are looking for: efficient online k-mer counting using a probabilistic data structure

K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix arrays, and trie structures, khmer relies entirely on a simple probabilistic data structure, a Count-Min Sketch. The Count-Min Sketch permits online updating and retrieval of k-mer counts in memory which is necessary to support online k-mer analysis algorithms. On sparse data sets this data structure is considerably more memory efficient than any exact data structure. In exchange, the use of a Count-Min Sketch introduces a systematic overcount for k-mers; moreover, only the counts, and not the k-mers, are stored. Here we analyze the speed, the memory usage, and the miscount rate of khmer for generating k-mer frequency distributions and retrieving k-mer counts for individual k-mers. We also compare the performance of khmer to several other k-mer counting packages, including Tallymer, Jellyfish, BFCounter, DSK, KMC, Turtle and KAnalyze. Finally, we examine the effectiveness of profiling sequencing error, k-mer abundance trimming, and digital normalization of reads in the context of high khmer false positive rates. khmer is implemented in C++ wrapped in a Python interface, offers a tested and robust API, and is freely available under the BSD license at github.com/ged-lab/khmer

Syndemic contexts: findings from a review of research on non-communicable diseases and interviews with experts

Background Syndemics are characterized by the clustering of two or more health conditions, their adverse interaction, and contextual factors that create the conditions for clustering and/or interaction that worsens health outcomes. Studying syndemics entails drawing on diverse disciplines, including epidemiology and anthropology. This often means collaboration between researchers with different scholarly backgrounds, who share and – ideally – integrate their findings. Objective This article examines how context within syndemics has been defined and studied. Methods A literature review of empirical studies focusing on syndemics involving non-communicable diseases (NCDs) and mental health conditions was conducted and the full text of 13 articles was analyzed. The review was followed-up with semi-structured interviews with 11 expert researchers working in the field. Results The review and interviews highlighted a relatively consistent definition of syndemics. The reviewed studies of NCD-related syndemics tended to focus on micro-level context, suggesting a need to analyze further underlying structural factors. In their syndemics research, respondents described working with other disciplines and, although there were some challenges, welcomed greater disciplinary diversity. Methodological gaps, including a lack of mixed methods and longitudinal studies, were identified, for which further interdisciplinary collaborations would be beneficial. Conclusions NCD-related syndemics research would benefit from further analysis of structural factors and the interconnections between syndemic components across multiple levels, together with more ambitious research designs integrating quantitative and qualitative methods. Research on the COVID-19 pandemic can benefit from a syndemics approach, particularly to understand vulnerability and the unequal impacts of this public health crisis