The Radiation Injury Severity Classification system: an early injury assessment tool for the frontline health-care provider.

Our goal was to adapt current diagnostic methods for radiation overexposure patients into a practical system that can be implemented rapidly and reliably by responders unfamiliar with the effects of radiation. Our Radiation Injury Severity Classification (RISC) system uses clinical and haematological parameters from the prodromal phase of the acute radiation syndrome (ARS) to classify acute radiation injury for purposes of managing treatment disposition. Data from well-documented ARS cases were used to test the RISC system. Three-day summaries were generated for each case. These were individually reviewed by the three physicians most involved with the development of the system to establish both a consensus case score (CCS) and disposition category ranges. 30 volunteer raters from varying health disciplines using the RISC system then each independently rated a random selection of 12 cases for injury severity in a self-trained field-simulation exercise. The CCS identified discrete cut-off ranges for the three disposition categories in both manageable and mass casualty events. The group of raters, after a modest period of self-training, achieved overall levels of pairwise agreement with the CCS category of 0.944 for manageable events and 0.947 for mass casualty situations. In conclusion, an early assessment of the severity of the ARS injury is required for an appropriate disposition determination. The RISC system should produce reasonably accurate and reliable assessments of radiation injury severity within 6-12 hours post exposure despite the probable absence of physical dosimetric data.

Uncertainties analysis of doses resulting from chronic inhalation of plutonium at the Mayak production association.

A method is presented to determine the uncertainties in the reported dose due to incorporated plutonium for the Mayak Worker Cohort. The methodology includes errors generated by both detection methods and modeling methods. To accomplish the task, the method includes classical statistics, Monte Carlo, perturbation, and reliability groupings. Uncertainties are reported in percent of reported dose as a function of total body burden. The cohort was initially sorted into six reliability groups, with "A" being the data set that the investigators are most confident is correct and "G" being the data set with the most ambiguous data. Categories were adjusted based on preliminary calculation of uncertainties using the sorting criteria. Specifically, the impact of transportability (the parameter used to describe the transport of plutonium from the lung to systemic organs) was underestimated, and the structure of the sort was reorganized to reflect the impact of transportability. The finalized categories are designated with Roman numerals I through V, with "I" being the most reliable. Excluding Category V (neither bioassay nor autopsy), the highest uncertainty in lung doses is for individuals from Category IV-which ranged from 90-375% for total body burdens greater than 10 Bq, along with work histories that indicated exposure to more than one transportability class. The smallest estimated uncertainties for lung doses were determined by autopsy. Category I has a 32-38% uncertainty in the lung dose for total body burdens greater than 1 Bq. First, these results provide a further definition and characterization of the cohort and, second, they provide uncertainty estimates for these plutonium exposure categories.

Antibiotic resistance in coagulase-negative staphylococci isolated from Cope's gray treefrogs (Hyla chrysoscelis).

Organisms belonging to the genus Staphylococcus were isolated on mannitol salt agar from the feces of wild caught Cope's gray treefrogs (Hyla chrysoscelis) from east-central Kansas. All 222 presumptive isolates were confirmed as coagulase-negative staphylococci with Staphylococcus sciuri and Staphylococcus xylosus being most prevalent. Antibiotic susceptibility patterns to five different antibiotics were determined and the results indicated 99% of all isolates were resistant to penicillin G and 59% of the isolates were resistant to oxacillin, a clinical substitute for methicillin. Due to the significance of methicillin resistance in the genus Staphylococcus, 10 randomly chosen oxacillin resistant organisms were analyzed for the presence of the mecA gene, which is known to code for methicillin resistance. The gene was detected in four of the 10 organisms examined. These data indicate that gray treefrogs are harboring inordinately large numbers of methicillin resistant staphylococci as part of their normal flora and that the mechanism of methicillin resistance may be independent of mecA.

Antimicrobial susceptibility of staphylococci isolated from the faeces of wild turkeys (Meleagris gallopavo).

AIMS: The purpose of this study was to investigate the staphylococcal flora associated with wild turkey populations. METHODS AND RESULTS: Faecal samples obtained from 26 wild turkeys over a 16-month period were inoculated onto mannitol salt agar plates to select for staphylococci. Fifty-seven randomly chosen isolates were identified as Staphylococcus lentus and their susceptibility determined against clindamycin, chloramphenicol, ciprofloxacin, erythromycin, oxacillin, penicillin G, rifampin, tetracycline, trimethoprim-sulfamethoxazole, and vancomycin. Resistance was minimal as only 3 isolates showed resistance to clindamycin, 3 isolates were resistant to oxacillin, 3 isolates were resistant to penicillin G, and 1 isolate was resistant to erythromycin. Multiple antibiotic resistance was also minimal. CONCLUSIONS: S. lentus is the predominant staphylococcal species associated with wild turkey faeces and antibiotic resistance in these organisms is not problematic. SIGNIFICANCE AND IMPACT OF THE STUDY: S. lentus has been shown as a potential causative agent of inflammatory reactions in the respiratory tract. Due to increased numbers of wild turkeys and more frequent human exposure, surveys to monitor microbial populations are warranted.

Development of an improved dosimetry system for the workers at the Mayak Production Association.

Databases are being created that contain verified and updated dosimetry and worker history information for workers at the Mayak Production Association. Many workers had significant external and internal exposures, particularly during the early years (1948-1952) of operation. These dosimetric and worker history data are to be used in companion epidemiology studies of stochastic and deterministic effects. The database contains both external and internal dose information and is being constructed from other databases that include radiochemical analyses of tissues, bioassay data, air sampling data, whole body counting data, and occupational and worker histories. The procedures, models, methods, and operational uncertainties will be documented and included in the database, technical reports, and publications. The cohort of the stochastic epidemiological study is expected to include about 19,000 persons while the cohort for the deterministic epidemiological study is expected to include about 600 persons. For external dosimetry, workplace gamma, beta, and neutron doses are being reconstructed. The models used for this incorporate issues such as known isotopes, composition, shielding, further analysis of film badge sensitivities, and records of direct measurements. Organ doses from external exposures are also being calculated. Methods for calculating dose uncertainties are being developed. For internal dosimetry, the organ doses have been calculated using the established FIB-1 biokinetic model. A new biokinetic model is being developed that includes more information of the solubility and biokinetics of the different chemical forms and particulate sizes of plutonium that were in the workplace. In addition, updated worker histories will be used to estimate doses to some workers where direct measurements were not made. A rigorous quality control procedure is being implemented to ensure that the correct dosimetry data is entering the various databases being used by the epidemiologists.