It doesn't talk about crytogenic strokes only those already identified as ischemic. so this doesn't seem that useful.
http://www.news-medical.net/news/20170329/MGH-scientists-develop-software-that-provides-automated-support-for-diagnosing-cause-of-stroke.aspx
Determining the cause of an ischemic stroke - one caused by an
interruption of blood supply - is critical to preventing a second stroke
and is a primary focus in the evaluation of stroke patients. But
despite that importance, physicians have long lacked a robust and
objective means of doing so. Now a team of investigators at the
Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts
General Hospital (MGH) and the MGH Stroke Service have developed a
software package that provides evidence-based, automated support for
diagnosing the cause of stroke. Their study validating the package -
called Causative Classification of Stroke (CCS) - was published online
in
JAMA Neurology.
"This was a much-needed study because, although stroke
classifications systems are often used in research and clinical
practice, these systems are not always able to produce subtypes with
discrete pathophysiological, diagnostic and prognostic characteristics,"
says Hakan Ay, MD, a vascular neurologist, Martinos Center investigator
and senior author of the
JAMA Neurology paper. "We found that
the CCS-based classifications provided better correlations between
clinical and imaging stroke features and were better able to
discriminate among stroke outcomes than were two conventional,
non-automated classification methods."
There are more than 150 different possible causes - or etiologies -
of ischemic stroke, and approximately half of patients exhibit features
suggesting more than one possible cause. This leads to considerable
complexity in determining the cause of a stroke and, in roughly one of
two patients, can lead to disagreements among physicians about the
cause. The CCS software helps to reduce this complexity by exploiting
classification criteria that are well defined, replicable and based on
evidence rather than subjective assessment.
The CCS software does this in several ways. First, it weights the
possible etiologies by considering the relative potential of each to
cause a stroke. Second, in the presence of multiple potential causes it
incorporates the clinical and imaging features that make one mechanism
more probable than others for an individual patient. Third, it
determines the likelihood of that cause by taking into account the
number of diagnostic tests that were performed. And finally, it ensures
that data is entered in a consistent manner. The software can also serve
as an important research tool, by providing investigators with both the
ability to examine how stroke etiologies interact with one another and
the flexibility to define new etiology subtypes according to the needs
of the individual research project.
The
MGH team previously showed that use of the CCS algorithm reduced the
disagreement rate among physicians from 50 percent to approximately 20
percent. The recently published
JAMA Neurology study further
established the utility of the algorithm by demonstrating its ability to
generate categories of etiologies with different clinical, imaging and
prognostic characteristics for 1,816 ischemic stroke patients enrolled
in two previous MGH-based studies. Based on patient data, CCS was able
to assign etiologies to 20 to 40 percent of the patients for which two
other systems were unable to determine a cause. It also was better at
determining the likelihood of second stroke within 90 days.
"The validity data that have emerged from the current study add to
the utility of the software-based approach and highlight once again that
careful identification and accurate classification of the underlying
etiology is paramount for every patient with stroke," says Ay, who is an
associate professor of Radiology at Harvard Medical School. "The
information the software provides not only is critical for effective
stroke prevention but also could increase the chances for new
discoveries by enhancing the statistical power in future studies of
etiologic stroke subtypes. We estimate that, compared to conventional
systems, the use of CCS in stroke prevention trials testing targeted
treatments for a particular etiologic subtype could reduce the required
sample size by as much as 30 percent."
The MGH-licensed CCS is available at https:/
/
ccs.
mgh.
harvard.
edu/
and is free for academic use. The software was designed to be a "living
algorithm" and can accommodate new information as it emerges. New
etiology-specific biomarkers, genetic markers, imaging markers and
clinical features that become available can be incorporated into the
existing CCS algorithm to further enhance its ability to determine the
underlying causes of stroke.
