Data Science and Analytics Department, SESAN, Paris, France.
Obstetrical Perinatal and Pediatric Epidemiology Research Team (EPOPé), INSERM, INRA, CRESS, Université de Paris, Paris, France.
Paediatr Perinat Epidemiol. 2020 May;34(3):350-365. doi: 10.1111/ppe.12665. Epub 2020 Mar 23.
Neonatal morbidity is associated with lifelong impairments, but the absence of a consensual definition and the need for large data sets limit research.
To inform initiatives to define standard outcomes for research, we reviewed composite neonatal morbidity indicators derived from routine hospital discharge data.
PubMed (updated on October 12, 2018). The search algorithm was based on three components: "morbidity," "neonatal," and "hospital discharge data."
Studies investigating neonatal morbidity using a composite indicator based on hospital discharge data were included. Indicators defined for specific conditions (eg congenital anomalies, maternal addictions) were excluded. The target population, objectives, component morbidities, diagnosis and procedure codes, validation methods, and prevalence of morbidity were extracted.
For each study, we assessed construct validity by describing the methods used to select the indicator components and evaluated whether the authors assessed internal and external validity. We also calculated confidence intervals for the prevalence of the morbidity composite.
Seventeen studies fulfilled inclusion criteria. Indicators targeted all (n = 4), low-/moderate-risk (n = 9), and very preterm (VPT, n = 4) infants. Components were similar for VPT infants, but domains and diagnosis codes within domains varied widely for all and low-/moderate-risk infants. Component selection was described for 8/17 indicators and some form of validation reported for 12/17. Neonatal morbidity prevalence ranged from 4.6% to 9.0% of all infants, 0.4% to 8.0% of low-/moderate-risk infants, and 17.8% to 61.0% of VPT infants.
Multiple neonatal morbidity indicators based on hospital discharge data have been used for research, but their heterogeneity limits comparisons between studies. Standard neonatal outcome measures are needed for benchmarking and synthesis of research results.
新生儿发病率与终生损伤有关，但由于缺乏共识定义和需要大数据集，限制了相关研究。
为了为定义研究的标准结局提供信息，我们回顾了从常规出院数据中得出的综合新生儿发病率指标。
PubMed（更新于 2018 年 10 月 12 日）。搜索算法基于三个部分：“发病率”、“新生儿”和“出院数据”。
包括使用基于医院出院数据的综合指标研究新生儿发病率的研究。排除针对特定疾病（如先天性异常、母体成瘾）定义的指标。提取目标人群、目标、复合发病率、诊断和程序代码、验证方法以及发病率的流行率。
对于每一项研究，我们通过描述选择指标成分的方法来评估结构有效性，并评估作者是否评估了内部和外部有效性。我们还计算了发病率综合的置信区间。
17 项研究符合纳入标准。指标针对所有（n=4）、低/中危（n=9）和非常早产儿（VPT，n=4）婴儿。VPT 婴儿的指标相似，但所有和低/中危婴儿的各个领域和诊断代码差异很大。8/17 个指标描述了成分选择，12/17 个指标报告了某种形式的验证。所有婴儿的发病率流行率范围为 4.6%至 9.0%，低/中危婴儿的发病率流行率范围为 0.4%至 8.0%，VPT 婴儿的发病率流行率范围为 17.8%至 61.0%。
基于医院出院数据的多个新生儿发病率指标已用于研究，但它们的异质性限制了研究之间的比较。需要标准的新生儿结局测量方法来进行基准测试和研究结果的综合。
