Drive-thru influenza immunization: Fifteen years of experience

2012 ◽  
Vol 10 (3) ◽  
pp. 228 ◽  
Author(s):  
Ruth M. Carrico, PhD, RN, FSHEA, CIC ◽  
W. Paul McKinney, MD, FACP ◽  
Nicholas Adam Watson, JD ◽  
Timothy Wiemken, PhD, MPH, CIC ◽  
John Myers, PhD, MSPH

Background: In 1995, a yearly drive-thru immunization program was initiated in Louisville, KY. Since then, more than 50,000 doses of influenza vaccine have been administered, with no reports of syncopal episodes or vehicular accidents. This report aimed to identify reported adverse events from other areas that could threaten drive-thru mass immunization approaches.Methods: To identify reported adverse events in any drive-thru mass immunization event, the authors queried the following sources: 1) the vaccine adverse event reporting system, 2) court cases, 3) healthcare risk management databases, 4) MEDLINE, and 5) communication with vaccine experts. The authors also calculated the probability of syncopal episodes using data from our past immunization experiences to further elucidate the possibility of these events occurring.Results: No adverse events due to a drive-thru mass immunization event were identified in any of the sources queried. In our data, the forecasted probability of one adverse event was 0.8 percent for a 2-day event (20,000 immunizations).Conclusions: Although syncope may occur following immunization, it is a risk that can be managed, and due to the rarity of these events, should not be used as a reason to avoid drive-thru administration of influenza vaccine.

2019 ◽  
Vol 14 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Viswam Subeesh ◽  
Eswaran Maheswari ◽  
Hemendra Singh ◽  
Thomas Elsa Beulah ◽  
Ann Mary Swaroop

Background: The signal is defined as “reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously”. Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.


Vaccine ◽  
2019 ◽  
Vol 37 (44) ◽  
pp. 6760-6767 ◽  
Author(s):  
Michael M. McNeil ◽  
Iwona Paradowska-Stankiewicz ◽  
Elaine R. Miller ◽  
Paige L. Marquez ◽  
Srihari Seshadri ◽  
...  

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