This is Observational study, aiming to investigate the potentiality of cffDNA and cfRNA by a non-invasive test, in combination with clinical characteristics, to establish models for early screening and predicting high-risk pregnancy of PE, SPB, and GDM in Vietnam.
This study is estimated to enroll 663 pregnant women with adverse pregnancy complications, including 221 cases of PE/eclampsia, 221 cases of SPB due to Preterm premature rupture of membranes (PPROM) or preterm labor, and 221 cases of GDM. Furthermore, the control group will enroll 442 participants, who are healthy pregnancies, ≥ 37 weeks of gestation. Study subjects who participate should meet the study inclusion and exclusion criteria: As part of the protocol, demographic data, medical and family history, outcomes at delivery, and any relevant prior concomitant medication data will be recorded during follow-up visits. All participants are to be followed until birth delivery. SAMPLE COLLECTION * At recruitment, 10 mL of peripheral blood is collected for cffDNA and cfRNA analyses. * An available NIPT sample at 1st trimester is processed for cffDNA and cfRNA analyses. * A case report forms (CRF-1 and CRF-2) are used to collect demographic data, medical and family history, any relevant prior concomitant medication data, and outcomes at delivery. The study end date of a participant is estimated within 7 months since her enrollment date.
Study Type
OBSERVATIONAL
Enrollment
1,105
Medical Genetics Institute
Ho Chi Minh City, Hồ Chí Minh, Vietnam
Characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation)
Observe the characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation): clinical features, cffDNA, cfRNA
Time frame: 12 months
Characteristics of pregnant women at recruitment
Characteristics of pregnant women at recruitment: clinical features, cffDNA, cfRNA
Time frame: 12 months
Define the significant differences between cases and controls
Comparison between clinical features, cffDNA, and cfRNA of early pregnancy and at recruitment, then defines the significant differences between cases and controls
Time frame: 12 months
The development of learning machine models
The development of learning machine models involved potential factors that help predict events of interest (PE, SPB, and GDM). From cfRNA and cfDNA data, factors that differ between the two groups will be identified and evaluated for their potentiality in predicting high-risk individuals. The Receiver Operating Characteristic (ROC) curve and values of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were used to determine the validity of the constructed model.
Time frame: 12 months
Evaluation of the developed models
Evaluation of the developed models by determining their sensitivity, specificity, area under the ROC Curve (AUC), positive predictive value (PPV), negative predictive value (NPV), and accuracy.
Time frame: 12 months
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