Abstract：
Background: Bronchopulmonary dysplasia (BPD) is the most common serious pulmonary morbidity in preterm infants with high disability and mortality rates. Early identification and treatment of BPD is critical. Objective: This study aimed to develop and validate a risk scoring tool for early identification of preterm infants that are at high-risk for developing BPD. Methods: The derivation cohort was derived from a systematic review and meta-analysis of risk factors for BPD. The statistically significant risk factors with their corresponding odds ratios were utilized to construct a logistic regression risk prediction model. By scoring the weights of each risk factor, a risk scoring tool was established and the risk stratification was divided. External verification was carried out by a validation cohort from China. Results: Approximately 83,034 preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g were screened in this meta-analysis, and the cumulative incidence of BPD was about 30.37%. The nine predictors of this model were Chorioamnionitis, Gestational age, Birth weight, Sex, Small for gestational age, 5 min Apgar score, Delivery room intubation, and Surfactant and Respiratory distress syndrome. Based on the weight of each risk factor, we translated it into a simple clinical scoring tool with a total score ranging from 0 to 64. External validation showed that the tool had good discrimination, the area under the curve was 0.907, and that the Hosmer-Lemeshow test showed a good fit (p = 0.3572). In addition, the results of the calibration curve and decision curve analysis suggested that the tool showed significant conformity and net benefit. When the optimal cut-off value was 25.5, the sensitivity and specificity were 0.897 and 0.873, respectively. The resulting risk scoring tool classified the population of preterm infants into low-risk, low-intermediate, high-intermediate, and high-risk groups. This BPD risk scoring tool is suitable for preterm infants with gestational age < 32 weeks and/or birth weight < 1500 g. Conclusions: An effective risk prediction scoring tool based on a systematic review and meta-analysis was developed and validated. This simple tool may play an important role in establishing a screening strategy for BPD in preterm infants and potentially guide early intervention.
摘要：
背景：支气管肺发育不良（BPD）是早产儿中最常见的严重肺部疾病，具有很高的致残率和死亡率。BPD的早期识别和治疗至关重要。目的：本研究旨在开发和验证一种风险评分工具，用于早期识别发生BPD的高危早产儿。方法：衍生队列来自BPD危险因素的系统评价和荟萃分析。利用具有统计学意义的危险因素及其相应的比值比构建逻辑回归风险预测模型。通过对每个风险因素的权重进行评分，建立了风险评分工具,并对风险分层进行了划分.外部验证由来自中国的验证队列进行。结果：在这项荟萃分析中，筛选了约83,034名胎龄<32周和/或出生体重<1500g的早产儿。BPD的累积发生率约为30.37%。该模型的9个预测因子是绒毛膜羊膜炎，妊娠年龄,出生体重,性,小于胎龄，5分钟阿普加得分，分娩室插管,以及表面活性剂和呼吸窘迫综合征。根据每个风险因素的权重，我们将其转化为一个简单的临床评分工具,总评分范围为0~64分.外部验证表明该工具具有良好的区分度，曲线下面积为0.907,Hosmer-Lemeshow检验显示良好的拟合(p=0.3572).此外,校准曲线和决策曲线分析的结果表明，该工具表现出显著的一致性和净效益。当最佳临界值为25.5时，灵敏度和特异度分别为0.897和0.873。由此产生的风险评分工具将早产儿人群分为低风险，低中间,高中间，和高危人群。该BPD风险评分工具适用于胎龄<32周和/或出生体重<1500g的早产儿。结论：开发并验证了基于系统评价和荟萃分析的有效风险预测评分工具。这个简单的工具可能在建立早产儿BPD筛查策略中起重要作用，并可能指导早期干预。
