| Project/Area Number |
18K09232
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 56040:Obstetrics and gynecology-related
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| Research Institution | University of Miyazaki |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
鮫島 浩 宮崎大学, 学長 (50274775)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 先天性サイトメガロウイルス感染症 / 妊婦抗体スクリーニング / 妊婦メンタルヘルス / サイトメガロウイルス / CMV IgG avidity / 妊婦スクリーニング / 母子感染 / 周産期 / メンタルヘルスケア / 胎内感染 / ウイルス感染 / IgG avidity / 脳障害 |
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| Outline of Final Research Achievements |
We showed the following results regarding the maternal CMV antibody screening; (1) The anxiety score of pregnant women with CMV IgM-positive was statistically higher than that with CMV IgM-negative. This result indicate that the mental support is required for IgM-positive women. (2) IgG avidity index (AI) is useful to detect primary maternal infection. However, IgG AI increase as gestational age advances. Thus, we indicated that IgG AI was useful to detect the maternal primary infection, when measured within 14 weeks of gestation. (3) we conducted the study to establish a model to predict high CMV IgG AI using clinical information, to contribute to the maternal mental health of CMV IgM positive pregnant women. As a result, we established a useful mathematical model that included clinical factors such as the CMV IgM titer and the pregnant women with one parity to predict a pregnant women’s likelihood of having a high CMV IgG AI with a high probability of 97%.
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| Academic Significance and Societal Importance of the Research Achievements |
CMV IgM陽性者の不安度の高さの提示により、妊婦抗体スクリーニング時のメンタルヘルスの重要性を示した。また、CMV IgM陽性者からCMV初感染者を正確に判別するためには、IgG avidity index (AI)を妊娠14週までに検査する必要があることを示し、さらに高IgG AIを高い確率で予測する数理モデル式を開発した。この結果、妊婦スクリーニングでCMV IgMと判定された妊婦に過度の不安を長期間与えることなく、CMV IgM値と妊娠回数から胎内CMV感染のLow riskである高IgG AIを判定することを可能とし、妊婦メンタルヘルスに配慮した抗体スクリーニング確立に寄与できた。
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