Table 15_Development and validation of an epidemiological risk score for neonatal death in a middle-income country.docx

IntroductionDespite global reductions in neonatal mortality, significant disparities remain between regions and population groups. Identifying newborns at higher risk at birth may help direct preventive actions and enhance health planning.
ObjectiveTo develop an epidemiological risk score for neonatal death based on individual and contextual factors.
MethodsA cohort study was conducted using data from over 5.6 million live births in 645 municipalities of São Paulo State, Brazil, between 2009 and 2018. The outcome was neonatal death. Risk weights were calculated from adjusted odds ratios obtained through multilevel logistic regression, with coefficients transformed using the natural logarithm and scaled from 1 to 10. Internal validation was performed within the cohort; external validation used data from 2008.
ResultsPoints were assigned to congenital anomalies (4, 7, or 10 depending on severity), preterm vaginal birth (4), preterm cesarean (4), birthweight <2,500 g (4), and fewer than seven prenatal visits (3). Conditions assigned 1 point included male sex, maternal age <17 or ≥40 years, term cesarean, birth in spring/summer, multiple pregnancy, low municipal nurse density in public services, and low municipal health insurance coverage. The area under the ROC curve (AUC) was 0.83 for internal and 0.81 for external validation. Risk stratification thresholds were proposed based on total points.
ConclusionThis score combines routinely collected individual and municipal-level data in Brazil to classify neonatal death risk. It may support clinical prioritization, resource allocation, and identification of low-risk deaths, complementing individualized clinical assessment.

研究背景：尽管全球新生儿死亡率已有所下降，但不同地区与人群群体间仍存在显著健康差异。识别出生时即具有较高死亡风险的新生儿，可为预防干预措施的精准实施提供指引，同时助力卫生健康规划的优化完善。
研究目的：基于个体特征与地区环境因素，开发一款用于评估新生儿死亡风险的流行病学评分模型。
研究方法：本研究为队列研究，采用巴西圣保罗州645个市镇2009至2018年间超过560万活产儿的临床数据开展分析。以新生儿死亡作为核心研究结局，通过多水平logistic回归分析获取校正后的比值比，以此计算风险权重；将回归系数经自然对数转换后，缩放至1至10的分值区间。在原研究队列内部完成内部验证，外部验证则采用2008年的独立数据集。
研究结果：评分赋值规则如下：先天性畸形（按严重程度分别赋值4、7或10分）、早产阴道分娩（4分）、早产剖宫产（4分）、出生体重<2500克（4分）、产前检查次数少于7次（3分）。以下情况赋值1分：新生儿为男性、母亲年龄<17岁或≥40岁、足月剖宫产、分娩于春夏季、多胎妊娠、公立卫生机构的市级护士密度偏低、市级医疗保险覆盖率较低。受试者工作特征曲线（Receiver Operating Characteristic, ROC）下面积（AUC）在内部验证中为0.83，外部验证中为0.81。本研究基于总得分提出了标准化的风险分层阈值。
研究结论：本评分模型整合了巴西常规收集的个体层面与市级层面卫生数据，可实现新生儿死亡风险的精准分级。该模型可为临床优先级排序、卫生资源合理配置提供支持，同时有助于识别低死亡风险病例，作为个体化临床评估的有效补充工具。