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Immature platelet fraction based diagnostic predictive scoring model for immune thrombocytopenia

Korean Journal of Internal Medicine 2020년 35권 4호 p.970 ~ 978
전민지 ( Jeon Min-Ji ) - Korea University Guro Hospital Department of Internal Medicine

유은상 ( Yu Eun-Sang ) - Korea University Guro Hospital Department of Internal Medicine
강가원 ( Kang Ka-Won ) - Korea University Anam Hospital Department of Internal Medicine
이병현 ( Lee Byung-Hyun ) - Korea University Anam Hospital Department of Internal Medicine
 ( Park Yong ) - Korea University Anam Hospital Department of Internal Medicine
이세련 ( Lee Se-Ryeon ) - Korea University Ansan Hospital Department of Internal Medicine
성화정 ( Sung Hwa-Jung ) - Korea University Ansan Hospital Department of Internal Medicine
이영 ( Lee Young ) - Korea University Guro Hospital Department of Laboratory Medicine
최철원 ( Choi Chul-Won ) - Korea University Guro Hospital Department of Internal Medicine
김병수 ( Kim Byung-Soo ) - Korea University Anam Hospital Department of Internal Medicine
김대식 ( Kim Dae-Sik ) - Korea University Guro Hospital Department of Internal Medicine

Abstract


Background/Aims: The diagnosis of immune thrombocytopenia (ITP) is based on clinical manifestations and there is no gold standard. Thus, even hematologic malignancy is sometimes misdiagnosed as ITP and adequate treatment is delayed. Therefore, novel diagnostic parameters are needed to distinguish ITP from other causes of thrombocytopenia. Immature platelet fraction (IPF) has been proposed as one of new parameters. In this study, we assessed the usefulness of IPF and developed a diagnostic predictive scoring model for ITP.

Methods: We retrospectively studied 568 patients with thrombocytopenia. Blood samples were collected and IPF quantified using a fully-automated hematology analyzer. We also estimated other variables that could affect thrombocytopenia by logistic regression analysis.

Results: The median IPF was significantly higher in the ITP group than in the non-ITP group (8.7% vs. 5.1%). The optimal cut-off value of IPF for differentiating ITP was 7.0%. We evaluated other laboratory variables via logistic regression analysis. IPF, hemoglobin, lactate dehydrogenase (LDH), and ferritin were statistically significant and comprised a diagnostic predictive scoring model. Our model gave points to each of variables: 1 to high hemoglobin (> 12 g/dL), low ferritin (≤ 177 ng/mL), normal LDH (≤ upper limit of normal) and IPF ≥ 7 and < 10, 2 to IPF ≥ 10. The final score was obtained by summing the points. We defined that ITP could be predicted in patients with more than 3 points.

Conclusions: IPF could be a useful parameter to distinguish ITP from other causes of thrombocytopenia. We developed the predictive scoring model. This model could predict ITP with high probability.

키워드

Thrombocytopenia; Immature platelet fraction; Immune thrombocytopenia
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