Detection kit for predicting attack of early-onset preeclampsia

Abstract

The invention provides a detection kit for predicting an attack of early-onset preeclampsia, and discloses a nucleotide sequence shown in SEQ ID NO.1 used for predicting the attack of the early-onsetpreeclampsia, a forward primer sequence shown in SEQ ID NO.2 and a reverse primer sequence shown in SEQ ID NO.3, wherein the forward primer sequence shown in SEQ ID NO.2 and the reverse primer sequence shown in SEQ ID NO.3 are used for the nucleotide sequence. The detection kit can be applied to the clinical experiment operation, a detection method provided by the kit is simple, the index is single, the predicated specificity reaches 100%, the sensitivity reaches 88.9%, and compared with existing detection methods, the specificity and the sensitivity are greatly improved. Therefore, the detection kit has a wide application prospect in an aspect of predicting the attack of the early-onset preeclampsia.

Description

technical field [0001] The invention relates to the technical field of gene detection, in particular to a detection kit for predicting the onset of early-onset preeclampsia. Background technique [0002] Early-onset preeclampsia is a serious disease during pregnancy, usually onset after 20 weeks of gestation, and characterized by persistently elevated blood pressure (≥160 / 110 mmHg). It can lead to complications such as postpartum hemorrhage, placental abruption, premature birth, and stillbirth in pregnant women, often causing serious maternal and infant morbidity and mortality. The incidence of early-onset preeclampsia in my country is about 3%, and the incidence of preeclampsia in my country is about 2-8%. Therefore, if it can be predicted early and intervened in a timely manner, the morbidity and mortality of mothers and infants will be greatly reduced. [0003] At present, the clinical prediction of early-onset preeclampsia still relies on physicians' screening of blood...

AI Technical Summary

Problems solved by technology

[0004] Some of the prediction methods reported in previous studies, such as plasma biomarkers and susceptibility genes, cannot be really applied clinically due to their poor specificity, low sensitivity, or the need for multi-molecule joint diagnosis prediction

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