Abstract
Introduction
Identification of predictors of potential mass poisonings may increase the speed and accuracy with which patients are recognized, potentially reducing the number ultimately exposed and the degree to which they are affected. This analysis used a decision-tree method to sort such potential predictors.
Methods
Data from the Toxic Exposure Surveillance System were used to select cyanide and botulism cases from 1993 to 2005 for analysis. Cases of other poisonings from a single poison center were used as controls. After duplication was omitted and removal of cases from the control sample was completed, there remained 1,122 cyanide cases, 262 botulism cases, and 70,804 controls available for both analyses. Classification trees for each poisoning type were constructed, using 131 standardized clinical effects. These decision rules were compared with the current case surveillance definitions of one active poison center and the American Association of Poison Control Centers (AAPCC).
Results
The botulism analysis produced a 4-item decision rule with Sensitivity (Se) of 68% and Specificity (Sp) of 90%. Use of the single poison center and AAPCC definitions produced Se of 19.5% and 16.8%, and Sp of 99.5% and 83.2%, respectively. The cyanide analysis produced a 9-item decision rule with Se of 74% and Sp of 77%. The single poison center and AAPCC case definitions produced Se of 10.2% and 8.6%, and Sp of 99.8% and 99.8%, respectively.
Conclusions
These results suggest the possibility of improved poisoning case surveillance sensitivity using classification trees. This method produced substantially higher sensitivities, but not specificities, for both cyanide and botulism. Despite limitations, these results show the potential of a classification-tree approach in the detection of poisoning events.
Keywords: botulism; cyanide; decision trees; models, statistical; poisons, public health aspects; surveillance
Full Text
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Footnotes
This project was supported by a grant from the National Bioterrorism Hospital Preparedness Cooperative Agreement—North Carolina, administered by the North Carolina Office of Emergency Medical Services.
References
- 1.Beuhler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V. Framework for evaluating public health surveillance systems for early detection of outbreaks. MMWR Morb Mortal Wkly Rep. 2004;53(RR05):1–11. [PubMed] [Google Scholar]
- 2.Shapiro RL, Hatheway C, Swerdlow DL. Botulism in the United States: A clinical and epidemiologic review. Ann Intern Med. 1998;129:221–228. doi: 10.7326/0003-4819-129-3-199808010-00011. [DOI] [PubMed] [Google Scholar]
- 3.Yen D, Tsai J, Wang LM, et al. The clinical experience of acute cyanide poisoning. Am J Emerg Med. 1995;13:524–528. doi: 10.1016/0735-6757(95)90162-0. [DOI] [PubMed] [Google Scholar]
- 4.Wolkin AF, Patel M, Watson W, et al. Early detection of illness associated with poisonings of public health significance. Ann Emerg Med. 2006;47:170–176. doi: 10.1016/j.annemergmed.2005.09.016. [DOI] [PubMed] [Google Scholar]
- 5.Hoyt BT, Rasmussen R, Griffin S, Smilkstein MJ. Poison center data accuracy: A comparison of rural hospital chart data with the TESS database. Acad Emerg Med. 1999;6:851–855. doi: 10.1111/j.1553-2712.1999.tb01220.x. [DOI] [PubMed] [Google Scholar]