Evidence map›Paper›PMID 26011498›Full record

ArticleHealth physics2015

HEMODOSE: A Biodosimetry Tool Based on Multi-type Blood Cell Counts.

Shaowen Hu, William F Blakely, Francis A Cucinotta

Abstract read
In one paragraph

Article in Health physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shaowen Hu*Wyle Laboratories, NASA Johnson Space Center, Houston, TX 77058; †Scientific Research Department, Armed Forces Radiobiology Research Institute, Uniformed Services University of the Health Sciences, Bethesda, MD 20889; ‡University of Nevada, Las Vegas, NV 89154.
William F Blakely
Francis A Cucinotta

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral blood cell counts are important biomarkers of radiation exposure. In this work, a simplified compartmental modeling approach is applied to simulate the perturbation of the hematopoiesis system in humans after radiation exposure, and HemoDose software is reported to estimate individuals' absorbed doses based on multi-type blood cell counts. Testing with patient data in some historical accidents indicates that either single or serial granulocyte, lymphocyte, leukocyte, and platelet counts after exposure can be robust indicators of the absorbed doses. In addition, such correlation exists not only in the early time window (1 or 2 d) but also in the late phase (up to 4 wk) after exposure, when the four types of cell counts are combined for analysis. These demonstrate the capability of HemoDose as a rapid point-of-care diagnostic or centralized high-throughput assay system for personnel exposed to unintended high doses of radiation, especially in large-scale nuclear/radiological disaster scenarios involving mass casualties.

Indexed as

AdolescentAdultAlgorithmsBiological AssayBiomarkersBlood Cell CountChildFemaleGranulocytesHumansLeukocytesLymphocytesMaleMiddle AgedPlatelet CountRadiation InjuriesBiomarkers

Identifiers

PMID26011498
PMCPMC4482456

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.