title: Maternal vaccination and preterm birth: using data mining as a screening tool.
abstract: OBJECTIVE
  The main purpose of this study was to identify possible associations between medicines used in pregnancy and preterm deliveries using data mining as a screening tool.
  
  
  METHODS
  Prospective cohort study.
  
  
  METHODS
  We used data mining to identify possible correlates between preterm delivery and medicines used by 92,235 pregnant Danish women who took part in the Danish National Birth Cohort (DNBC). We then evaluated the association between one of the identified exposures (vaccination) and the risk for preterm birth by using logistic regression. The women were classified into groups according to their exposure to vaccination. The regression analyses were adjusted for the following covariates: parity, infant's gender, maternal Body-Mass Index (BMI), age, smoking, drinking, job, number of inhabitants in the place of residence, infections, diabetes, high blood pressure and preeclampsia.
  
  
  METHODS
  Preterm birth, a delivery occurring before the 259th day of gestation (i.e., less than 37 full weeks).
  
  
  RESULTS
  Data mining had indicated that maternal vaccination (among other factors) might be related to preterm birth. The following regression analysis showed that, the women who reported being vaccinated shortly before or during gestation had a slightly higher risk of giving preterm birth (O.R. = 1.14; 95% CI 1.04-1.25) as compared to the non-vaccinated group.
  
  
  CONCLUSIONS
  Whether the association between maternal vaccination and the risk for preterm birth found here is causal or not deserves further studies. Data mining, especially with additional refinements, may be a valuable and very efficient tool to screen large databases for relevant information which can be used in clinical and public health research.
authors.affiliation: Danish Transport Research Institute, Knuth-Winterfeldts Allé, Bygning, Lyngby, Denmark. iob@dtf.dk
authors.forename: Ivanka
authors.initials: I
authors.lastname: Orozova-Bekkevold
authors.forename: Henrik
authors.initials: H
authors.lastname: Jensen
authors.forename: Lone
authors.initials: L
authors.lastname: Stensballe
authors.forename: Jørn
authors.initials: J
authors.lastname: Olsen
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D015984:Causality; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data*; D003718:Denmark; D005260:Female; D006801:Humans; D016015:Logistic Models; D008403:Mass Screening / Q000379:methods* / Q000706:statistics & numerical data; D015233:Models, Statistical; D011247:Pregnancy; D011251:Pregnancy Complications, Infectious / Q000517:prevention & control; D011256:Pregnancy Outcome; D047928:Premature Birth / Q000139:chemically induced*; D011295:Prenatal Care; D011446:Prospective Studies; D018570:Risk Assessment; D014611:Vaccination / Q000009:adverse effects*