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Health Phys ; 119(1): 64-71, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32484636

RESUMO

Treatment regimens for acute radiation syndrome have been improved over the past years. The application of appropriate therapy relies on rapid and high-throughput tests ideally conducted in the first 3 d after a radiation exposure event. We have examined the utility of blood cell counts (BCCs) 3 d post irradiation to predict clinical outcome for hematologic acute radiation syndrome (HARS). The BCCs and HARS severity information originated from data available in the System-for-Evaluation-and-Archiving-of-Radiation Accidents-based-on-Case-Histories (SEARCH). We found an almost complete discrimination of unexposed (HARS score H0) vs. irradiated individuals during model development and validation (negative predictive value > 94%) when using BCC data for all 3 d. We also found that BCC data increased the correct prediction of exposed individuals from day 1 to day 3. We developed spreadsheets to calculate the likelihood of correct diagnoses of the worried-well, requirement of hospitalization (HARS 2-4), or development of severe hematopoietic syndrome (HARS 3-4). In two table-top exercises, we found the spreadsheets were confusing and cumbersome, so we converted the spreadsheets into a smartphone application, named the H-module App, designed for ease of use, wider dissemination, and accommodation of co-morbidities in the HARS severity prediction algorithm.


Assuntos
Síndrome Aguda da Radiação/diagnóstico , Contagem de Células Sanguíneas/métodos , Aplicativos Móveis , Medição de Risco/métodos , Smartphone/instrumentação , Síndrome Aguda da Radiação/induzido quimicamente , Algoritmos , Relação Dose-Resposta à Radiação , Humanos , Doses de Radiação , Exposição à Radiação/efeitos adversos , Liberação Nociva de Radioativos , Fatores de Tempo
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