Brain-type natriuretic peptide at birth reflects foetal maturation and antenatal stress.

AIM: Antenatal stress, maturation and other foetal conditions affect the postnatal cardiovascular function. Atrial- (ANP) and brain-type natriuretic peptide (BNP) play important roles in regulating extracellular fluid volume and blood pressure, which may surrogate the foetal cardiovascular condition. The aim of this study was to investigate the dependence of serum ANP and BNP at birth on antenatal variables in high-risk infants. METHODS: Plasma ANP and BNP levels in the umbilical cord blood were compared with antenatal clinical information in 280 infants. RESULTS: High levels of ANP and BNP were associated with multiple pregnancy, antenatal magnesium sulphate and foetal distress. Caesarean section (CS) was paradoxically associated with low ANP and high BNP; low ANP was related with CS before labour whereas high BNP was related with CS after the commencement of labour. High BNP levels further correlated with younger gestational age and intrauteral growth restriction. With regard to short-term postnatal variables, high BNP levels were associated with low Apgar scores and respiratory failure whereas high ANP only correlated with the latter. CONCLUSION: High natriuretic peptide levels were associated with prematurity at birth, uteral contraction and antenatal stress: cord blood ANP and BNP may be a useful surrogate marker for hidden antenatal stress.

Statistical power of multiplicity adjustment strategies for correlated binary endpoints.

There are numerous alternatives to the so-called Bonferroni adjustment to control for familywise Type I error among multiple tests. Yet, for the most part, these approaches disregard the correlation among endpoints. This can prove to be a conservative hypothesis testing strategy if the null hypothesis is false. The James procedure was proposed to account for the correlation structure among multiple continuous endpoints. Here, a simulation study evaluates the statistical power of the Hochberg and James adjustment strategies relative to that of the Bonferroni approach when used for multiple correlated binary variables. The simulations demonstrate that relative to the Bonferroni approach, neither alternative sacrifices power. The Hochberg approach has more statistical power for rho