Syndrome surveillance of fentanyl-laced heroin outbreaks: Utilization of EMS, Medical Examiner and Poison Center databases.

OBJECTIVE: Describe surveillance data from three existing surveillance systems during an unexpected fentanyl outbreak in a large metropolitan area. METHODS: We performed a retrospective analysis of three data sets: Chicago Fire Department EMS, Cook County Medical Examiner, and Illinois Poison Center. Each included data from January 1, 2015 through December 31, 2015. EMS data included all EMS responses in Chicago, Illinois, for suspected opioid overdose in which naloxone was administered and EMS personnel documented other criteria indicative of opioid overdose. Medical Examiner data included all deaths in Cook County, Illinois, related to heroin, fentanyl or both. Illinois Poison Center data included all calls in Chicago, Illinois, related to fentanyl, heroin, and other prescription opioids. Descriptive statistics using Microsoft Excel® were used to analyze the data and create figures. RESULTS: We identified a spike in opioid-related EMS responses during an 11-day period from September 30-October 10, 2015. Medical Examiner data showed an increase in both fentanyl and mixed fentanyl/heroin related deaths during the months of September and October, 2015 (375% and 550% above the median, respectively.) Illinois Poison Center data showed no significant increase in heroin, fentanyl, or other opioid-related calls during September and October 2015. CONCLUSION: Our data suggests that EMS data is an effective real-time surveillance mechanism for changes in the rate of opioid overdoses. Medical Examiner's data was found to be valuable for confirmation of EMS surveillance data and identification of specific intoxicants. Poison Center data did not correlate with EMS or Medical Examiner data.

DNA identification of sperm cells collected and sorted by flow cytometry.

In cases of rape, obtaining enough biologic material for DNA identification of the attacker is often difficult because the methods for distinguishing and separating sperm cells from vaginal cells are not sufficiently efficacious. This article describes a new, innovative method for spermatic DNA extraction from the vaginal washing fluid by means of flow cytometry. The high specificity and sensitivity of the flow-cytometric sorting method provides enough sperm cells for DNA typing. The ease of execution of this method, involving vaginal washing with physiologic solution and flow-cytometric reading of the fresh sample, substantially increases its cost-benefit ratio.