Transient Hematotoxicity After Emerald Horned Pitviper (Ophryacus smaragdinus) Envenomation: A Case Report.

BACKGROUND: A minority of snake envenomations in the United States involve non-native snakes. In this report, we describe what we believe is the first documented human envenoming from an emerald horned pitviper, Ophryacus smaragdinus. CASE REPORT: A previously healthy 36-year-old woman was bitten on her left index finger by a captive emerald horned pitviper she was medicating at work. Swelling to the entire hand was present on emergency department arrival. She had no systemic symptoms and her initial laboratory studies were unremarkable. The affected limb was elevated. We administered five vials of Antivipmyn TRIⓇ (Bioclon), which specifically lists Ophryacus among the envenomations for which it is indicated. She developed pruritus and was treated with IV diphenhydramine and famotidine. Her swelling improved, but her repeat laboratory studies were notable for a platelet count of 102 K/µL and a fibrinogen level of 116 mg/dL. She declined additional antivenom because of the previous allergic reaction. She was admitted for further monitoring and pain control. Subsequent laboratory tests were better, but a small hemorrhagic bleb developed at the bite site. She was discharged the next day and followed up as an outpatient. Her swelling had resolved, her bleb had healed, and her laboratory studies continued to improve. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Emergency physicians may be required to treat bites from non-native snakes. Many of these bites will warrant treatment with non-U.S. Food and Drug Administration-approved antivenoms. Consultation with a regional poison center or medical toxicologist may be necessary to procure the proper antivenom.

Validating effectiveness of subgroup identification for longitudinal data.

In clinical trials and biomedical studies, treatments are compared to determine which one is effective against illness; however, individuals can react to the same treatment very differently. We propose a complete process for longitudinal data that identifies subgroups of the population that would benefit from a specific treatment. A random effects linear model is used to evaluate individual treatment effects longitudinally where the random effects identify a positive or negative reaction to the treatment over time. With the individual treatment effects and characteristics of the patients, various classification algorithms are applied to build prediction models for subgrouping. While many subgrouping approaches have been developed recently, most of them do not check its validity. In this paper, we further propose a simple validation approach which not only determines if the subgroups used are appropriate and beneficial but also compares methods to predict individual treatment effects. This entire procedure is readily implemented by existing packages in statistical software. The effectiveness of the proposed method is confirmed with simulation studies and analysis of data from the Women Entering Care study on depression.