Matthew D. Sztajnkrycer

Bio: Matthew D. Sztajnkrycer is an academic researcher from Mayo Clinic. The author has contributed to research in topics: Poison control & Emergency medical services. The author has an hindex of 17, co-authored 68 publications receiving 1052 citations. Previous affiliations of Matthew D. Sztajnkrycer include University of Rochester & University of Cincinnati.

Valproic Acid Toxicity: Overview and Management

Abstract: Acute valproic acid intoxication is an increasing problem, accounting for more than 5000 calls to the American Association of Poison Control Centers in 2000. The purpose of this paper is to review ...

Chemical and radiological toxicity of depleted uranium.

Abstract: A by-product of the uranium enrichment process, depleted uranium (DU) contains approximately 40% of the radioactivity of natural uranium yet retains all of its chemical properties. After its use in the 1991 Gulf War, public concern increased regarding its potential radiotoxicant properties. Whereas in vitro and rodent data have suggested the potential for uranium-induced carcinogenesis, human cohort studies assessing the health effects of natural and DU have failed to validate these findings. Heavy-metal nephrotoxicity has not been noted in either animal studies or Gulf War veteran cohort studies despite markedly elevated urinary uranium excretion. No significant residual environmental contamination has been found in geographical areas exposed to DU. As such, although continued surveillance of exposed cohorts and environments (particularly water sources) are recommended, current data would support the position that DU poses neither a radiological nor chemical threat.

Effectiveness of Patient-Collected Swabs for Influenza Testing

Abstract: Objective To compare the effectiveness of self-collected and health care worker (HCW)–collected nasal swabs for detection of influenza viruses and determine the patients' preference for type of collection.

The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic

Abstract: Twitter is a free social networking and micro-blogging service that enables its millions of users to send and read each other's “tweets,” or short, 140-character messages. The service has more than 190 million registered users and processes about 55 million tweets per day. Useful information about news and geopolitical events lies embedded in the Twitter stream, which embodies, in the aggregate, Twitter users' perspectives and reactions to current events. By virtue of sheer volume, content embedded in the Twitter stream may be useful for tracking or even forecasting behavior if it can be extracted in an efficient manner. In this study, we examine the use of information embedded in the Twitter stream to (1) track rapidly-evolving public sentiment with respect to H1N1 or swine flu, and (2) track and measure actual disease activity. We also show that Twitter can be used as a measure of public interest or concern about health-related events. Our results show that estimates of influenza-like illness derived from Twitter chatter accurately track reported disease levels.

Major physical and psychological harms of methamphetamine use

Abstract: Issues. The major physical and psychological health effects of methamphetamine use, and the factors associated with such harms. Approach. Comprehensive review. Key Findings. Physical harms reviewed...

Using internet searches for influenza surveillance.

Abstract: The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine ( http://search.yahoo.com ) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.