Statistics
A descriptive analysis was performed using absolute and relative
frequencies for categorical variables and mean value with standard
deviation for continuous variables. Then, we performed Pearson’s
Chi-Square and t-test, as appropriate, of clinical and demographic
characteristics of women between the groups. We used logistic regression
to evaluate an association between the mode of conception and preterm
delivery in infertile women after reproductive surgery. The logistic
regression model was adjusted for variables which presented as
significantly different between the spontaneous and IVF/ICSI group in
descriptive analysis. The association was presented as adjusted odds
ratio (aOR) with 95 % confidence interval (95% CI).
For the case-control study of the effect of reproductive surgery on
preterm delivery, we used the propensity score (PS) method. Controls
were selected from among all fertile women (n=100765) who delivered in
the same period using PS matching. In the PS model, we included maternal
age as a continuous variable, BMI as a categorical variable
(underweight, normal weight, obese), and dichotomous variables: previous
conization, chronic diseases (pre-pregnancy hypertension, pre-pregnancy
diabetes, kidney, heart, thyroid and/or mental disease), previous
preterm delivery, smoking, and multiple pregnancies. We performed 1:1
matching with an optimal matching algorithm with a calliper width of the
linear predictor of 0.1 standard deviations. The balance between the
control and treated group was considered well when the value of the
standardized difference was <0.1. The effect of reproductive
surgery on preterm delivery was evaluated in the PS-matched sample by
Pearson’s Chi-Square test and presented as the odds ratio (OR) with 95%
confidential interval (95% CI).
Considering an increase in preterm delivery rate by 30% in infertile
women, within the limit of the number of treated women, the study’s
power was 0.78 at a 5% Type I error rate.
For statistical calculations, we used statistical program IBM SPSS
Statistics v25 and R18 with R-package
”Matchlt”19. For all calculations, a two-sided
probability (p ) value < 0.05 was considered
statistically significant.