Prospective Validation of a Prognostic Model for Respiratory Syncytial Virus Bronchiolitis in Late Preterm Infants: A Multicenter Birth Cohort Study

Maarten O. Blanken, Hendrik Koffijberg, Elisabeth E. Nibbelke, Maroeska M. Rovers, Louis Bont*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

39 Citations (Scopus)
23 Downloads (Pure)

Abstract

Objectives: This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA).

Study Design: The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227). In the validation cohort (n = 1,194), predicted versus actual RSV hospitalization rates were compared to determine validity of the model.

Results: RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%). In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2), birth period (OR 2.6; 1.6-4.2), breastfeeding (OR 1.7; 1.0-2.7) and siblings or daycare attendance (OR 4.7; 1.7-13.1). The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping). External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74).

Conclusions: Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.

Original languageEnglish
Article numbere59161
JournalPLoS ONE
Volume8
Issue number3
DOIs
Publication statusPublished - 12 Mar 2013

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