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Diabetologia. 2000 Jul;43(7):927-31.

Urinary albumin excretion and 24-hour blood pressure as predictors of pre-eclampsia in Type I diabetes.

Author information

1
The Department of Nephrology and Endocrinology, the National University Hospital (Rigshospitalet), Copenhagen, Denmark.

Abstract

AIMS/HYPOTHESIS:

To evaluate the value of 24-h blood pressure monitoring compared to office blood pressure and urinary albumin excretion in predicting pre-eclampsia in Type I (insulin-dependent) diabetes mellitus.

METHODS:

The study included 136 consecutive pregnancies in Caucasian women with Type I diabetes before gestation without diabetic nephropathy, anamnestic hypertension or early abortion. Values of urinary albumin excretion and office blood pressure before pregnancy and the HbA1C value at the time of conception were obtained. Microalbuminuria was defined as urinary albumin excretion of 30-300 mg/24 h in two out of three consecutive urine samples. Single measurements of 24-h urinary albumin excretion, office blood pressure and HbA1C were done five 5 times during pregnancy. In a subgroup of 74 women 24-h blood pressure measurements were done at 10 and 28 weeks of gestation. Pre-eclampsia was defined as office blood pressure higher than 140/90 mmHg accompanied by proteinuria above 0.3 g/24 h later than 20 weeks of gestation.

RESULTS:

Urinary albumin excretion and systolic blood pressure were higher before and throughout pregnancy in 14 women developing pre-eclampsia compared with women remaining normotensive (p <0.001; p < 0.05, respectively). By logistic regression analysis the best predictor for pre-eclampsia was microalbuminuria before pregnancy (p < 0.05) with no additive predictive effect of 24-h blood pressure or office blood pressure measurement. The night:day ratio of blood pressure was similar in the two groups.

CONCLUSION/INTERPRETATION:

Microalbuminuria before pregnancy is the strongest predictor of pre-eclampsia in Type I diabetes. Measuring 24-h blood pressure early in pregnancy did not improve the ability to identify women at risk.

PMID:
10952467
DOI:
10.1007/s001250051471
[Indexed for MEDLINE]

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