W3C home > Mailing lists > Public > public-semweb-lifesci@w3.org > September 2012

NCBO Webinar: Do Proton Pump Inhibitors increase the risk of Myocardial Infarction? -- insights from mining clinical notes - Sep 19th 10am PDT

From: Trish Whetzel <plwhetzel@gmail.com>
Date: Tue, 18 Sep 2012 00:34:53 +0100
Message-ID: <CAE4f=niA5v0kYPZLSmzshETMQEWuH3xqMAe1ONtajFM6oHDPTw@mail.gmail.com>
To: HCLS <public-semweb-lifesci@w3.org>
The next NCBO Webinar will be presented by Dr. Nigam Shah from Stanford
University on "Do Proton Pump Inhibitors increase the risk of Myocardial
Infarction? -- insights from mining clinical notes" at 10:00am PT,
Wednesday, Sep. 19.  Below is information on how to join the online meeting
via WebEx and accompanying teleconference. For the full schedule of the
NCBO Webinar presentations see: http://www.bioontology.org/webinar-series.

The current state of the art in post-marketing drug surveillance utilizes
voluntarily submitted reports of suspected adverse drug reactions. As
adoption of electronic health records increases, we present an approach
based on analyzing the unstructured clinical notes, which can enable rapid
pharmacovigilance. Using this approach we find that proton pump inhibitors
(PPIs) as a class appear strongly associated with major adverse
cardiovascular events, increasing the risk of myocardial infarction by
20-50% depending upon the individual PPI. The association of PPIs with such
events was hypothesized based on experimental results that show that PPIs,
as a class, elevate plasma levels of asymmetric dimethylarginine, a disease
marker and an independent predictor of major adverse cardiovascular events.

We show that it is possible to investigate adverse drug event associations
with high accuracy (72% sensitivity, 83% specificity) by analyzing textual
notes in a clinical data warehouse using ontology-driven methods. We
examine suspected associations for confounding via stratification and
propensity score matching. We find that such an analysis of textual
clinical notes could detect adverse drug events 2 years before the official
alert. We argue that data-mining of unstructured clinical notes may expand
meaningful use of the electronic health records for post-marketing drug
surveillance and for rapid retrospective analysis of adverse event risk
elucidated by experimental methods, such as in our case study on proton
pump inhibitors.

Dr. Nigam H. Shah is an Assistant Professor of Medicine (Biomedical
Informatics) at the Stanford School of Medicine. Dr. Shah's research is
focused on developing applications of bio-ontologies, specifically building
novel approaches to annotate, index, integrate and analyze diverse
information types available in biomedicine. Dr. Shah holds an MBBS from
Baroda Medical College, India, a PhD from Penn State University, USA and
completed post-doctoral training at the Stanford Medical School.

To start or join the online meeting
Go to

Meeting Number: 925 756 393
Meeting Password: ncbo

Audio conference information
To receive a call back, provide your phone number when you join the
meeting, or call the number below and enter the access code.
Call-in toll number (US/Canada): 1-650-429-3300
Global call-in numbers:

Access code: 925 756 393

Trish Whetzel, PhD
Outreach Coordinator
The National Center for Biomedical Ontology
Ph: 650-721-2378

"Like" NCBO on Facebook: http://on.fb.me/bioontology

Follow NCBO on Twitter: http://twitter.com/#!/bioontology

Join in Discussions on LinkedIn: http://linkd.in/ncbo-group
Received on Monday, 17 September 2012 23:35:21 UTC

This archive was generated by hypermail 2.3.1 : Wednesday, 7 January 2015 14:52:57 UTC