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596 Early Prediction of Bronchopulmonary Dysplasia (Bpd) by an Easily Available Risk Score
  1. M Roth-Kleiner1,
  2. J Chnayna1,
  3. E Giannoni1,
  4. M Faouzi2
  1. 1Clinic of Neonatology, University Hospital of Lausanne, CHUV
  2. 2Center of Clinical Epidemiology, Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland


Background Early prediction of BPD is important for identifying high risk patients likely to benefit from preventive treatment approaches and for providing prognostic information. Therefore we aimed to develop a risk score for BPD based on early available clinical parameters.

Patients and methods: All infants born at the University Hospital of Lausanne < 32 weeks of gestation (WG) between 1998 and 2007 (n=936) were included. Patients diagnosed with RDS (n=232) were divided in two groups, either developing BPD or not. Independent risk factors for the development of BPD were searched by multivariate logistic regression analysis. The β-coefficients (β=log(OR)) derived from the fitted multivariate model were used to build a scoring system. An internal validation was performed using a two-fold cross-validation technique with two subgroups: two thirds of the patients were used as training set for model calibration and one third as prediction set.

Results BPD-risk score was developed based on five covariates: intubation in the delivery room, early neonatal infection, duration of invasive mechanical ventilation in days, birth weight and gestational age, weighted according their β-coefficients. Area under curve (AUC) was 0.896. Sensitivity and specificity reached 82.7% and 82.6% with a score cut-off of –8 (range –25 to +17). Internal calibration proved a good prediction: AUC for the same cut-off was 0.882 for the training set and 0.927 for the prediction set.

Conclusions A simple scoring system available within the first postnatal week can reliably predict the probability of developing BPD in infants born < 32 WG.

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