Prediction of early recurrent thromboembolic event and major bleeding in patients with acute stroke and atrial fibrillation by a risk stratification schema: the ALESSA score study

Background and Purposes—This study was designed to derive and validate a score to predict early ischemic events and major bleedings after an acute ischemic stroke in patients with atrial fibrillation. Methods—The derivation cohort consisted of 854 patients with acute ischemic stroke and atrial fibrillation included in prospective series between January 2012 and March 2014. Older age (hazard ratio 1.06 for each additional year; 95% confidence interval, 1.00–1.11) and severe atrial enlargement (hazard ratio, 2.05; 95% confidence interval, 1.08–2.87) were predictors for ischemic outcome events (stroke, transient ischemic attack, and systemic embolism) at 90 days from acute stroke. Small lesions (≤1.5 cm) were inversely correlated with both major bleeding (hazard ratio, 0.39; P=0.03) and ischemic outcome events (hazard ratio, 0.55; 95% confidence interval, 0.30–1.00). We assigned to age ≥80 years 2 points and between 70 and 79 years 1 point; ischemic index lesion >1.5 cm, 1 point; severe atrial enlargement, 1 point (ALESSA score). A logistic regression with the receiver-operating characteristic graph procedure (C statistic) showed an area under the curve of 0.697 (0.632–0.763; P=0.0001) for ischemic outcome events and 0.585 (0.493–0.678; P=0.10) for major bleedings. Results—The validation cohort consisted of 994 patients included in prospective series between April 2014 and June 2016. Logistic regression with the receiver-operating characteristic graph procedure showed an area under the curve of 0.646 (0.529–0.763; P=0.009) for ischemic outcome events and 0.407 (0.275–0.540; P=0.14) for hemorrhagic outcome events. Conclusions—In acute stroke patients with atrial fibrillation, high ALESSA scores were associated with a high risk of ischemic events but not of major bleedings

Timing of initiation of oral anticoagulants in patients with acute ischemic stroke and atrial fibrillation comparing posterior and anterior circulation strokes

Background: The aim of this study in patients with acute posterior ischemic stroke (PS) and atrial fibrillation (AF) were to evaluate the risks of recurrent ischemic event and severe bleeding and these risks in relation with oral anticoagulant therapy (OAT) and its timing. Methods: Patients with PS were prospectively included; the outcome events of these patients were compared with those of patients with anterior stroke (AS) which were taken from previous registries. The primary outcome was the composite of: stroke recurrence, TIA, symptomatic systemic embolism, symptomatic cerebral bleeding and major extracranial bleeding occurring within 90 days from acute stroke. Results: A total of 2,470 patients were available for the analysis: 473 (19.1%) with PS and 1,997 (80.9%) AS. Over 90 days, 213 (8.6%) primary outcome events were recorded: 175 (8.7%) in patients with AS and 38 (8.0%) in those with PS. In patients who initiated OAT within 2 days, the primary outcome occurred in 5 out of 95 patients (5.3%) with PS compared to 21 out of 373 patients (4.3%) with AS (OR 1.07; 95% CI 0.39-2.94). In patients who initiated OAT between days 3 and 7, the primary outcome occurred in 3 out of 103 patients (2.9%) with PS compared to 26 out of 490 patients (5.3%) with AS (OR 0.54; 95% CI 0.16-1.80). Conclusions: Patients with posterior or anterior stroke and AF appear to have similar risks of ischemic or hemorrhagic events at 90 days with no difference concerning the timing of initiation of OAT

Hemorrhagic transformation in acute ischemic stroke patients and atrial fibrillation: time to initiation of anticoagulants and outcome

Background: In patients with acute ischemic stroke and atrial fibrillation, early anticoagulation prevents ischemic recurrence but with the risk of hemorrhagic transformation (HT). The aims of this study were to evaluate in consecutive patients with acute stroke and atrial fibrillation (1) the incidence of early HT, (2) the time to initiation of anticoagulation in patients with HT, (3) the association of HT with ischemic recurrences, and (4) the association of HT with clinical outcome at 90 days. Methods and Results: HT was diagnosed by a second brain computed tomographic scan performed 24 to 72 hours after stroke onset. The incidence of ischemic recurrences as well as mortality or disability (modified Rankin Scale scores >2) were evaluated at 90 days. Ischemic recurrences were the composite of ischemic stroke, transient ischemic attack, or systemic embolism. Among the 2183 patients included in the study, 241 (11.0%) had HT. Patients with and without HT initiated anticoagulant therapy after a mean 23.3 and 11.6 days, respectively, from index stroke. At 90 days, 4.6% (95% confidence interval, 2.3–8.0) of the patients with HT had ischemic recurrences compared with 4.9% (95% confidence interval, 4.0–6.0) of those without HT; 53.1% of patients with HT were deceased or disabled compared with 35.8% of those without HT. On multivariable analysis, HT was associated with mortality or disability (odds ratio, 1.71; 95% confidence interval, 1.24–2.35). Conclusions: In patients with HT, anticoagulation was initiated about 12 days later than patients without HT. This delay was not associated with increased detection of ischemic recurrence. HT was associated with increased mortality or disability

Anticoagulation After Stroke in Patients With Atrial Fibrillation : To Bridge or Not With Low-Molecular-Weight Heparin?

Background and Purpose- Bridging therapy with low-molecular-weight heparin reportedly leads to a worse outcome for acute cardioembolic stroke patients because of a higher incidence of intracerebral bleeding. However, this practice is common in clinical settings. This observational study aimed to compare (1) the clinical profiles of patients receiving and not receiving bridging therapy, (2) overall group outcomes, and (3) outcomes according to the type of anticoagulant prescribed. Methods- We analyzed data of patients from the prospective RAF and RAF-NOACs studies. The primary outcome was defined as the composite of ischemic stroke, transient ischemic attack, systemic embolism, symptomatic cerebral bleeding, and major extracerebral bleeding observed at 90 days after the acute stroke. Results- Of 1810 patients who initiated oral anticoagulant therapy, 371 (20%) underwent bridging therapy with full-dose low-molecular-weight heparin. Older age and the presence of leukoaraiosis were inversely correlated with the use of bridging therapy. Forty-two bridged patients (11.3%) reached the combined outcome versus 72 (5.0%) of the nonbridged patients (P=0.0001). At multivariable analysis, bridging therapy was associated with the composite end point (odds ratio, 2.3; 95% CI, 1.4-3.7; P Conclusions- Our findings suggest that patients receiving low-molecular-weight heparin have a higher risk of early ischemic recurrence and hemorrhagic transformation compared with nonbridged patients.Peer reviewe

Characterizing the US Research Computing and Data (RCD) Workforce

A growing share of computationally and data-intensive research, both inside and outside of academia, requires the involvement and support of computing and data professionals. Yet little is known about the composition of the research computing and data (RCD) workforce. This paper presents the results of a survey (N=563) of RCD professionals' demographic and educational backgrounds, work experience, current positions, job responsibilities, and views of working in the RCD field. We estimate the size of the RCD workforce and discuss how the demographic diversity and distribution of backgrounds of those in the RCD workforce fail to match that of the larger academic and technical workforces. These survey results additionally support the insights of those working in the field concerning the need to recruit a wider variety of professionals into the RCD profession, better define job descriptions and career pathways, and improve institutional recognition for the value of RCD work.National Science FoundationImmediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Compensation of Academic Research Computing and Data Professionals

Previous work identified low compensation levels as a barrier to recruitment and retention in the Research Computing and Data (RCD) field. In order to better understand the characteristics of RCD compensation, a 2021 survey of RCD professionals in the United States gathered salary information from 480 full-time, currently-employed RCD professionals, including 394 respondents working at non-medical academic institutions. The median salary reported for academic institutions was $90,000 ($80,000 for individual contributor levels), with variation observed across respondents' position levels, gender, ethnicity, education, years of experience, and geography. While RCD roles require a combination of expertise in two fields - research and technology - the median compensation for academic RCD professionals falls below that for either of these fields independently. The variation in compensation within the academic RCD field is also found to be less than the variation in the non-academic technology industry or for academic research faculty positions, with salary ranges limited at the upper end. Smaller differences in compensation between respondents based on years of experience and education were observed compared to the broader labor market. Further research with data from more RCD professionals is needed for a complete analysis of compensation within the RCD field.National Science FoundationImmediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The US-RSE Association: Bringing Together Research Software Engineers

Digital Humanities brings, among other things, digital sources, algorithms, and software into the field of humanities. This typically requires additional skills and expertise from disciplines outside of the humanities such as programming knowledge, data science, or statistics. The more complex the envisioned digital output, the more in-depth technical skills are usually required. This is true for most academic disciplines; many projects cannot be accomplished anymore without collaborating with someone with technical expertise. Often this expertise can be found in software engineers who work with researchers on their projects. Depending on the context, many of these people call themselves Research Software Engineers. Over the last 10 years, the awareness for this role within academia has steadily increased. The first association of Research Software Engineers was founded in 2013 in the UK, followed by several other national associations. In early 2018, the United States Research Software Engineer Association (US-RSE) was established with the goal to create a community, advocate, and provide resources for Research Software Engineers in order to advance research by improving the quality and trustworthiness of research software. US-RSE holds regular community calls, hosts virtual workshops, and had its first annual member meeting in December 2020. US-RSE has grown quickly from a couple of members to over 600 within just three years. This poster will present the US-RSE Association, its goals and initiatives. It will be an invitation to everyone doing the “technical part” of a digital humanities project to join and find like-minded people for exchange and support

easystats/parameters: parameters 0.21.2

Changes Minor improvements to factor analysis functions. The ci_digits argument of the print() method for model_parameters() now defaults to the same value of digits. model_parameters() for objects from package marginaleffects now also accepts the exponentiate argument. The print(), print_html(), print_md() and format() methods for model_parameters() get an include_reference argument, to add the reference category of categorical predictors to the parameters table. Bug fixes Fixed issue with wrong calculation of test-statistic and p-values in model_parameters() for fixest models. Fixed issue with wrong column header for glm models with family = binomial("identiy"). Minor fixes for dominance_analysis()

Learner engagement v. video watching, assignments, and weeks of the introductory STEM MOOC.

(A) Joint histogram of enrolled in the introductory MOOC by total number of modules/course weeks in which they participated by watching videos (vertical axis) or taking quizzes (horizontal axis). The outlined region approximately separates “learners” from disengaged “non-learners;” a small number (31 or 1%) of learners who completed a PGA but few quizzes may not fall within the outlined region. (Note that the course included a module “0”, introducing the course.) (B) Percent of total enrolled who participated during each module/course week by watching more than one video that week, distinguished by character of participant.</p