Department Pediatric Immunology and Infectious Diseases, University Medical Center, Utrecht, Utrecht, The Netherlands.
PLoS One. 2013;8(3):e59161. doi: 10.1371/journal.pone.0059161. Epub 2013 Mar 12.
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).
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.
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).
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.
本研究旨在更新和验证一个预测 33-35 孕周早产儿(GA)呼吸道合胞病毒(RSV)住院的预测规则。
RISK 研究由 41 家医院的 2 个多中心前瞻性出生队列组成。在健康的 33-35 周 GA 早产儿中,在出生时评估危险因素。所有因呼吸道感染住院的患儿均通过免疫荧光或聚合酶链反应(PCR)筛查确诊 RSV 感染。多变量逻辑回归分析用于更新推导队列(n=1227)中现有的预测模型。在验证队列(n=1194)中,比较预测与实际 RSV 住院率以确定模型的有效性。
两个队列的 RSV 住院风险相当(5.7%与 4.9%)。在推导队列中,使用 4 个预测因素制定了一个预测 RSV 住院风险的预测规则:家族特应性(OR 1.9;95%CI,1.1-3.2)、分娩期(OR 2.6;1.6-4.2)、母乳喂养(OR 1.7;1.0-2.7)和兄弟姐妹或日托出勤率(OR 4.7;1.7-13.1)。该模型具有良好的区分度(C 统计量为 0.703;0.64-0.76,bootstrap 后为 0.702)。外部验证显示了良好的区分度和校准度(C 统计量为 0.678;0.61-0.74)。
我们前瞻性验证的预测规则可识别出 RSV 住院风险增加的婴儿,这些婴儿可能受益于有针对性的预防干预措施。该预测规则可以促进特定国家/地区在晚期早产儿中进行 RSV 预防的成本效益利用。