| Title |
A characteristic flow cytometric pattern with broad forward scatter and narrowed side scatter helps diagnose immune thrombocytopenia (ITP)
|
|---|---|
| Published in |
International Journal of Hematology, April 2018
|
| DOI | 10.1007/s12185-018-2454-y |
| Pubmed ID | |
| Authors |
Raita Araki, Ryosei Nishimura, Rie Kuroda, Toshihiro Fujiki, Shintaro Mase, Kazuhiro Noguchi, Yasuhiro Ikawa, Hideaki Maeba, Akihiro Yachie |
| Abstract |
Various disorders cause severe thrombocytopenia, which can lead to critical hemorrhage. Procedures that rapidly support the diagnosis and risk factors for serious bleeding were explored, with a focus on immune thrombocytopenia (ITP). Twenty-five patients with thrombocytopenia, including 13 with newly diagnosed ITP, 3 with chronic ITP, 6 with aplastic anemia (AA), and 3 with other thrombocytopenia (one acute myeloid leukemia, one acute lymphoblastic leukemia, and one hemophagocytic lymphohistiocytosis), were reviewed. In addition to platelet-related parameters obtained by an automated hematology analyzer, flow cytometric analysis of platelets was performed. A characteristic flow cytometric pattern with broad forward scatter and narrowed side scatter, which is specific to ITP, but not other types of thrombocytopenia, was found. CD62P-positive platelets were increased in newly diagnosed ITP cases compared to control (P < 0.0001), AA (P = 0.0032). Moreover, detection of dramatic changes in these parameters on sequential monitoring may suggest internal hemorrhage, even absent skin or visible mucosal bleeding. The bleeding score for visible mucosae had a negative correlation with platelet count and a positive correlation with immature platelet fraction (%), forward scatter, and CD62P. This characteristic flow cytometric pattern makes it possible to distinguish ITP from other thrombocytopenic disorders. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 26% |
| Student > Master | 4 | 21% |
| Student > Ph. D. Student | 3 | 16% |
| Researcher | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Other | 3 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 47% |
| Biochemistry, Genetics and Molecular Biology | 4 | 21% |
| Veterinary Science and Veterinary Medicine | 1 | 5% |
| Environmental Science | 1 | 5% |
| Social Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 2 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 September 2018.
All research outputs
#20,532,290
of 23,102,082 outputs
Outputs from International Journal of Hematology
#1,108
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Outputs of similar age
#262,309
of 296,979 outputs
Outputs of similar age from International Journal of Hematology
#21
of 27 outputs
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