The obtained result reveals sensitivity for preeclampsia around 80% that increases for hypertensive and normal pregnancy groups. On the other hand, specificity is around 85-90%. These results indicate that the combination of HRV indexes with artificial neural networks (ANN) could be helpful for pregnancy study and characterization.

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Including all the subjects in the analysis, we found that complexity indexes are positively related with hemoglobin concentration in the pathologic group and uric acid blood levels whereas low frequency (LF) was negatively correlated with uric acid and creatinine concentration as well as positively correlated with platelet levels. The LF was the only spectral region with significant correlation. Through an independent analysis of groups, only significant correlations were found in normal and preeclamptic groups between LF and uric acid concentration and in normal and hypertensive groups for LF and creatinine blood levels.

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