| Autor: |
Masatoki Kaneko, Masanao Ohhashi, Yoshinori Fujii, Toshio Minematsu, Kazumi Kusumoto |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
International Journal of Infectious Diseases, Vol 100, Iss , Pp 1-6 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1201-9712 |
| DOI: |
10.1016/j.ijid.2020.08.034 |
| Popis: |
Objective: To establish a model to predict high cytomegalovirus (CMV) immunoglobulin (Ig)G avidity index (AI) using clinical information, to contribute to the mental health of CMV-IgM positive pregnant women. Methods: We studied 371 women with IgM positivity at ≤14 w of gestation. Information on the age, parity, occupation, clinical signs, IgM and G values, and IgG AI was collected. The IgG AI cut-off value for diagnosing congenital infection was calculated based on a receiver operating characteristic curve analysis. Between-group differences were assessed using the Mann–Whitney U-test or χ2 analysis. The factors predicting a high IgG AI were determined using multiple logistic regression. Results: The women were divided into high or low IgG AI groups based on an IgG AI cut-off value of 31.75. There were significant differences in the IgG and IgM levels, age, clinical signs, and the number of women with one parity between the two groups. In a multiple logistic regression analysis, IgM and the number of women with one parity were independent predictors. This result helped us establish a mathematical model that correctly classified the IgG AI level for 84.6% of women. Conclusion: We established a highly effective model for predicting a high IgG AI immediately after demonstrating IgM positivity. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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