Background Anaphylaxis-related deaths in the United States (US) have not been well characterized in recent years. Objectives To define epidemiological features and time trends of fatal anaphylaxis in the US from 1999 to 2010. Methods Anaphylaxis-related deaths were identified by the 10th clinical modification of the International Classification of Diseases (ICD-10) system diagnostic codes on death certificates from the US National Mortality Database. Rates were calculated using census population estimates. Results There were a total of 2,458 anaphylaxis deaths in the US from 1999 to 2010. Medications were the most common cause (58.8%), followed by unspecified anaphylaxis (19.3%), venom (15.2%), and food (6.7%). There was a significant increase in fatal drug anaphylaxis over twelve years: from 0.27 (95%CI: 0.23-0.30) in 1999-2001 to 0.51 (95%CI: 0.47-0.56) per million in 2008-2010, P<0.001. Fatal anaphylaxis due to medications, food, and unspecified allergens was significantly associated with African-American race and older age, P<0.001. Fatal anaphylaxis to venom was significantly associated with White race, older age, and male gender, P<0.001. The rates of fatal anaphylaxis to foods in African-American males increased from 0.06 (95%CI 0.01-0.17) in 1999-2001 to 0.21 (95%CI 0.11-0.37) per million in 2008-2010, P<0.001. The rates of unspecified fatal anaphylaxis decreased overtime from 0.30 (95%CI: 0.26-0.34) in 1999-2001 to 0.09 (95%CI: 0.07-0.11) per million in 2008-2010, P<0.001. Conclusion There are strong and disparate associations between race and specific classes of anaphylaxis mortality in the United States. The increase in medication-related anaphylaxis deaths likely relates to increased medication and radiocontrast use, enhanced diagnosis, and coding changes.
Denervation induced plastic changes impair locomotor recovery after spinal cord injury (SCI). Spinal motoneurons become hyperexcitable after SCI, but the plastic responses of locomotor network interneurons after SCI have not been studied. Using an adult mouse SCI model, we analyzed the effects of complete spinal cord lesions on the intrinsic electrophysiological properties, excitability and neuromodulatory responses to serotonin (5-HT) in mouse lumbar V2a spinal interneurons, which help regulate left-right alternation during locomotion. Four weeks after SCI, V2a interneurons showed almost no changes in baseline excitability or action potential properties; the only parameter that changed was a reduced input resistance. However, V2a interneurons became 100-1000 fold more sensitive to 5-HT. Immunocytochemical analysis showed that SCI caused a coordinated loss of serotonergic fibers and the 5-HT transporter (SERT). Blocking the SERT with citalopram in intact mice did not increase 5-HT sensitivity to the level seen after SCI. SCI also evoked an increase in 5-HT2C receptor cluster number and intensity, suggesting that several plastic changes cooperate in increasing 5-HT sensitivity. Our results suggest that different components of the spinal neuronal network responsible for coordinating locomotion are differentially affected by SCI, and highlight the importance of understanding these changes when considering therapies targeted at functional recovery.
Introduction: There is growing interest in, and emphasis on, electronic teaching tools in medicine. Despite relevant testing on the United States Medical Licensing Examination (USMLE), American medical schools offer limited training in skin disorders. Teaching visual topics like dermatology in classroom formats is challenging. We hypothesized that an electronic module would enhance students' dermatology competency. Methods: A self-directed, case-based module was created. To test its efficacy, 40 medical students were randomized to have module access (interventional group) or none (conventional group). Learning outcomes were compared using a multiple-choice exam, including questions relevant and irrelevant to the module. Outcomes included proportions of correctly answered module questions (module scores) and nonmodule questions (nonmodule scores). Difference scores were calculated: (module score) − (nonmodule score). Positive values indicated that knowledge of module questions surpassed that of
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