Table 4

Logistic regression models predicting pregnancy outcomes from metabolite levels
Outcomes Metabolite IQR 95% CI P value
Min Max
All PB types (n = 114) Steroid conjugate: 0.63 (s) 1.90 0.99 3.69 0.054
Formate 0.51 0.26 0.99 0.047
SPB (n = 88) Steroid conjugate: 0.63 (s) 1.99 0.94 4.32 0.076
Lysine 2.79 1.20 6.98 0.021
N-methyl-2-pyridone-5-carboxamide 2.05 0.96 4.51 0.066
Formate 0.42 0.19 0.94 0.037
IPB (n = 26) N-acetyl glycoprotein fragments 5.84 1.44 39.50 0.028
Phenylacetylglutamine 0.37 0.09 1.28 0.131
FGR (n = 36) Tyrosine 0.27 0.08 0.81 0.025
Lactate 0.37 0.12 1.04 0.069
Alanine 0.38 0.13 1.02 0.064
Acetate 0.18 0.04 0.60 0.011
Citrate 0.33 0.09 0.99 0.058
Trimethylamine 0.14 0.04 0.40 0.001
Glycine 0.36 0.11 1.02 0.062
Formate 0.24 0.07 0.71 0.014
SGA (n = 19) Lactate 0.20 0.03 0.89 0.055
Alanine 0.19 0.03 0.88 0.055
Acetate 0.12 0.01 0.70 0.050
N-acetyl neuraminic acid 2.23 0.64 9.10 0.225
Glycine 0.19 0.03 0.88 0.052

Interquartile odds ratios (IQR, first versus fourth) with 95% confidence interval (CIs) are presented for the incident risk for pregnancy outcomes according to candidate metabolite relative concentrations.

Statistical analysis (z-score) of the beta values (log odds) indicated if the metabolite was significantly contributing to the model (highlighted in bold).

Models were adjusted for maternal education, maternal age, parity and smoking. FGR, fetal growth restriction; IPB, induced preterm birth; SGA, small for gestational age; SPB, spontaneous preterm birth.

Maitre et al.

Maitre et al. BMC Medicine 2014 12:110   doi:10.1186/1741-7015-12-110

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