A New Smartphone Application to Predict Hematologic Acute Radiation Syndrome Based on Blood Cell Count Changes—The H-module App

Abstract

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.

Radiologische und nukleare Notfalllagen

“…[28]. Neuere Entwicklungen können datenbankbasiert anhand von Blutbildwerten eines einzelnen Tages Vorhersagen zur Entwicklung eines schweren Strahlensyndroms treffen, dieses sogenannte "H-Modul" steht als App kostenfrei zur Verfügung und kann zur Triage eingesetzt werden [12,31]. Punkte sammeln auf CME.thieme.de…”

Gene Expression Changes in Irradiated Baboons: A Summary and Interpretation of a Decade of Findings

“…Likewise, biological factors, such as cell type or individual radiosensitivity, would be included (integrated) by measuring bioindicators of effect. Different groups have already shown that changes in blood cell counts (10,12,13) and blood protein markers (4, 5) can be used for effect prediction. In a similar fashion, gene expression levels can be exploited for the same purpose, as explained below.…”

Early-response multiple-parameter biodosimetry and dosimetry: risk predictions

“…The Bundeswehr Institute of Raiobiology has developed a smartphone application, H-module, to perform clinical triage of radiation casualties [23][24][25]. The application is based on using peripheral blood cell counts measured within the 1st 3 d after radiation exposure to predict haematological acute radiation syndrome (H-ARS) severity.…”

“…ARS severity degrees were defined based on the medical treatment protocols for radiation accident victims (METRE-POL) [26]. Clinical case history data from the system for evaluation and archiving of radiation accidents based on case histories (SEARCH) database were used for developing the H-module [24].…”