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Ultrasound in Obstetrics and Gynecology 2015-May

Serum soluble fms-like tyrosine kinase-1 in the three trimesters of pregnancy: effects of maternal characteristics and medical history.

يمكن للمستخدمين المسجلين فقط ترجمة المقالات
الدخول التسجيل فى الموقع
يتم حفظ الارتباط في الحافظة
A Tsiakkas
N Duvdevani
A Wright
D Wright
K H Nicolaides

الكلمات الدالة

نبذة مختصرة

OBJECTIVE

To define the contribution of maternal variables which influence the measured level of maternal serum soluble fms-like tyrosine kinase-1 (sFlt-1) in screening for pregnancy complications.

METHODS

Maternal characteristics and medical history were recorded and serum sFlt-1 was measured in women with a singleton pregnancy attending for three routine hospital visits at 11 + 0 to 13 + 6, 19 + 0 to 24 + 6 and 30 + 0 to 34 + 6 or 35 + 0 to 37 + 6 weeks' gestation. For pregnancies delivering phenotypically normal live births or stillbirths ≥ 24 weeks' gestation, variables from maternal demographic characteristics and medical history that are important in the prediction of sFlt-1 were determined from a linear mixed-effects multiple regression.

RESULTS

Serum sFlt-1 was measured in 7066 cases in the first trimester, 8078 in the second trimester and 10,464 in the third trimester. Significant independent contributions to serum sFlt-1 were provided by gestational age, maternal weight, racial origin, cigarette smoking, birth-weight Z-score of the neonate in the previous pregnancy and interpregnancy interval. Random-effects multiple regression analysis was used to define the contribution of maternal variables that influence the measured level of serum sFlt-1 and express the values as multiples of the median (MoMs). The model was shown to provide an adequate fit of MoM values for all covariates, both in pregnancies that developed pre-eclampsia and in those without this pregnancy complication.

CONCLUSIONS

A model was fitted to express measured serum sFlt-1 across the three trimesters of pregnancy as MoMs, after adjusting for variables from maternal characteristics and medical history that affect this measurement.

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قاعدة بيانات الأعشاب الطبية الأكثر اكتمالا التي يدعمها العلم

  • يعمل في 55 لغة
  • العلاجات العشبية مدعومة بالعلم
  • التعرف على الأعشاب بالصورة
  • خريطة GPS تفاعلية - ضع علامة على الأعشاب في الموقع (قريبًا)
  • اقرأ المنشورات العلمية المتعلقة ببحثك
  • البحث عن الأعشاب الطبية من آثارها
  • نظّم اهتماماتك وابقَ على اطلاع دائم بأبحاث الأخبار والتجارب السريرية وبراءات الاختراع

اكتب أحد الأعراض أو المرض واقرأ عن الأعشاب التي قد تساعد ، واكتب عشبًا واطلع على الأمراض والأعراض التي تستخدم ضدها.
* تستند جميع المعلومات إلى البحوث العلمية المنشورة

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