Literature DB >> 22095760

Disproportionality analysis for signal detection of implantable cardioverter-defibrillator-related adverse events in the Food and Drug Administration Medical Device Reporting System.

Hesha J Duggirala1, Naomi D Herz, Daniel Arthur Caños, Roberta A Sullivan, Richard Schaaf, Ellen Pinnow, Danica Marinac-Dabic.   

Abstract

BACKGROUND: The Food and Drug Administration (FDA) became aware of lead fracture and inappropriate shock events related to Sprint Fidelis leads in January 2007. The manufacturer announced a voluntary market withdrawal in October 2007. AIM: Our aim was to retrospectively evaluate this safety signal using disproportionality analysis to estimate whether disproportionality analysis could have detected this particular safety signal earlier than actually occurred.
MATERIALS AND METHODS: The Manufacturer and User Facility Device Experience (MAUDE) database contains reports on device-related adverse events, of which, FDA receives several hundred thousand every year. For each manufacturer, a list of the top lead brand names was ranked by frequency of reports. We used the Multi-item Gamma Poisson Shrinker (MGPS) method for analysis. We isolated 11 top-reported implantable cardioverter defibrillator (ICD) lead brand names. Using MGPS methodology, we calculated the one-sided 95% lower confidence bound EB05 on the empirical Bayes geometric mean of the reporting ratio.
RESULTS: We performed individual MGPS analysis for each of the top reported adverse events in 2006 for ICD leads. Fidelis had the highest EB05 scores for lead fractures and inappropriate shock. DISCUSSION: Through disproportionality analysis of the MAUDE database, we were able to identify known safety signals associated with the Medtronic Sprint Fidelis lead.
CONCLUSION: If utilized at the time, this disproportionality analysis would have identified signals earlier for lead fractures, oversensing, high impedance, and inappropriate shock.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 22095760     DOI: 10.1002/pds.2261

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  3 in total

1.  Digital drug safety surveillance: monitoring pharmaceutical products in twitter.

Authors:  Clark C Freifeld; John S Brownstein; Christopher M Menone; Wenjie Bao; Ross Filice; Taha Kass-Hout; Nabarun Dasgupta
Journal:  Drug Saf       Date:  2014-05       Impact factor: 5.606

Review 2.  Challenges Associated with the Safety Signal Detection Process for Medical Devices.

Authors:  Josep Pane; Katia M C Verhamme; Dorian Villegas; Laura Gamez; Irene Rebollo; Miriam C J M Sturkenboom
Journal:  Med Devices (Auckl)       Date:  2021-02-24

3.  Increasing Patient Engagement in Pharmacovigilance Through Online Community Outreach and Mobile Reporting Applications: An Analysis of Adverse Event Reporting for the Essure Device in the US.

Authors:  Chi Y Bahk; Melanie Goshgarian; Krystal Donahue; Clark C Freifeld; Christopher M Menone; Carrie E Pierce; Harold Rodriguez; John S Brownstein; Robert Furberg; Nabarun Dasgupta
Journal:  Pharmaceut Med       Date:  2015-08-05
  3 in total

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