Analysing medical predictors for the outcome of infertility treatment: a 5-year follow-up survey.

Purpose: For many couples, bearing children is a common life goal; however it cannot always be fulfilled. Undergoing infertility treatment does not always guarantee pregnancies and live births. Couples experience miscarriages and even discontinue infertility treatment. Significant medical predictors for the outcome of infertility treatment have yet to be fully identified.

Methods: To further our understanding, a cross-sectional 5-year follow-up survey was undertaken, in which 95 women and 82 men that have been treated at the Women's Hospital of Heidelberg University participated. Binary logistic regressions, parametric and non-parametric methods were used for our sample to determine the relevance of biological (infertility diagnoses, maternal and paternal age) and lifestyle factors (smoking, drinking, over- and underweight) on the outcome of infertility treatment (clinical pregnancy, live birth, miscarriage, dropout rate). In addition, chi-square tests were used to examine differences in the outcome depending on the number of risk factors being present.

Results: In the binary logistic regression models for clinical pregnancies, live births and drop outs were statistically significant only for the maternal age, whereas the maternal and paternal BMI, smoking, infertility diagnoses and infections showed no significant predicting effect on any of the outcome variables. A correlation between the number of risk factors and the outcome of infertility treatment could not be excluded.

Conclusion: The results confirm that maternal age has an effect on infertility treatment, whereas the relevance of other possible medical predictors remains unclear. Further large-scale studies should be considered to increase our knowledge on their predictive power.