Table 1.
Number of women included in the cluster analysis with each risk factor.
A participant may have one or more risk factors.
Table 2.
Baseline and pregnancy characteristics.
Table 3.
Confirmed diagnoses in the cohort of high-risk women.
Table 4.
Delivery characteristics.
Fig 1.
Heat map—Results of the cluster analysis.
The heatmap presents the risk factors (columns) in the different clusters on the left side with black boxes. The rows correspond to the 25 clusters (C1-C25) identified on the basis of the risk factor profiles, and the sizes of the clusters are shown on the left side of the heat map (n = 226 etc.). The size (i.e. area) of the black box illustrates the proportion of women in the particular cluster with the risk factor in question. Right side of the heatmap presents the risk ratios of the outcomes. The colour of the cell represents the estimated risk ratio of the corresponding outcome in the corresponding cluster, and the colour encoding is shown on the right side of the heatmap. Those cells are colored which are significant at the nominal 5% level (see text for discussion). The exact risk ratios are presented in Table 5.
Table 5.
Risk ratios and 95% Confidence Intervals (CIs) of the cluster analysis.
The marking C1 etc. is referring to certain row in the heatmap. If the risk factor is inside brackets, only a portion of women in the cluster had that risk factor.
Fig 2.
Risk ratio grows exponentially (linearly on the logarithmic scale) as the number of risk factors increases.
The increase is significant when the risk of preeclampsia is predicted by the number of risk factors using logistic regression (Preeclampsia (total)(n = 86), p = 0.0181, b = 0.3429)
Table 6.
Important risk factors and clusters and number of women who developed preeclampsia in each group.