Knowing characteristic adverse events (AEs) and their incidence among patients participating in acute stroke trials may assist interpretation of future studies. We aimed to develop an online tool to inform stroke trial safety.
We identified relevant AEs from patients within the Virtual International Stroke Trials Archive (VISTA), using receiver operating characteristic principles. We modeled their incidence on patient age, baseline National Institutes of Health Stroke Scale, and comorbidities using binary logistic regression. Models with an R(2) >5% were deemed powerful enough to predict expected AE incidences and were included. The calculator was developed using programs R and Visual Studios.
Forty-eight of the most common AEs were identified and incorporated into the IschAEmic Stroke Calculator. The calculator, publicly available at www.vistacollaboration.org calculates the expected incidence of AEs or groups of AEs in a trial cohort and where possible compares them with the observed incidence.
The IschAEmic Stroke Calculator is an open access resource to support safety interpretation within acute stroke trials. Prediction of AEs with higher likelihood of occurrence may direct preventive clinical measures.
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 November 2019.
All research outputs
#8,404,970
of 32,332,113 outputs
Outputs from Stroke
#7,543
of 15,240 outputs
Outputs of similar age
#101,340
of 433,568 outputs
Outputs of similar age from Stroke
#87
of 141 outputs
Altmetric has tracked 32,332,113 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 15,240 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.1. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 433,568 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
