Butler Emma, Spirtos Michelle, O' Keeffe Linda M, Clarke Mary
Department of Population Health, Royal College of Surgeons Ireland, Dublin, Ireland.
Department of Occupational Therapy, Trinity College Dublin, Dublin, Ireland.
Eur Child Adolesc Psychiatry. 2025 May 15. doi: 10.1007/s00787-025-02730-9.
We developed and internally validated a multivariable model to be used in the perinatal period, to predict 5-year-olds mental health, using the ELFE prospective French multicentre birth cohort (n=9768). Twenty-six candidate predictors were used, spanning pre-pregnancy maternal health, pregnancy-specific-experiences, birth factors and sociodemographic risk (maternal age, education, relationship, migrancy and family income). The Strengths and Difficulties Questionnaire total score at 5-years, dichotomised at the recommended cut-off (16), was the outcome. Least Absolute Shrinkage and Selector Operator followed by bootstrapping was used. High and low-risk was classified by ≥8% risk-threshold score. Stability of the model at population- and individual-level and model performance across groups of interest (sex, sociodemographic risk and neonatal intensive care admissions) was also examined. 10 variables (total number pregnancy-specific experiences, sociodemographic risk, maternal pre-existing hypertension and psychological difficulties, gravidity, maternal mental health problems in a previous pregnancy, smoking and alcohol use in current pregnancy, how labour started and infant sex) with a C-statistic of 0.67; 95%CI (0.64-0.69) predicted mental health. The positive and negative predictive value were 12% & 95.4% respectively, leading to 78.8% of children correctly classified. Model performance was similar across groups of interest but increased for children (born ≥33-weeks-gestation) with neonatal admissions (AUC 0.78; 95%CI (0.69-0.87)). This model is most useful for identifying low-risk children. Applying this model in a tiered preventative intervention framework could be beneficial with those predicted to be high-risk receiving further screening to determine the level of intervention required. External validation and implementation research are required before considering its use in practice.
我们开发并在内部验证了一个多变量模型,该模型用于围产期,利用法国ELFE前瞻性多中心出生队列(n = 9768)预测5岁儿童的心理健康状况。我们使用了26个候选预测变量,涵盖孕前母亲健康状况、孕期特定经历、出生因素和社会人口统计学风险(母亲年龄、教育程度、关系、移民身份和家庭收入)。以5岁时优势与困难问卷总分作为结果变量,该总分按照推荐的临界值(16分)进行二分法划分。采用最小绝对收缩和选择算子法并结合自抽样法。根据风险阈值得分≥8%对高风险和低风险进行分类。我们还检验了该模型在总体水平和个体水平的稳定性,以及在感兴趣的群体(性别、社会人口统计学风险和新生儿重症监护病房入院情况)中的模型表现。10个变量(孕期特定经历总数、社会人口统计学风险、母亲既往高血压和心理问题、妊娠次数、前次妊娠时母亲的心理健康问题、本次妊娠期间吸烟和饮酒情况、分娩发动方式和婴儿性别)的C统计量为0.67;95%置信区间(0.64 - 0.69),可预测心理健康状况。阳性预测值和阴性预测值分别为12%和95.4%,78.8%的儿童被正确分类。在感兴趣的群体中,模型表现相似,但对于有新生儿重症监护病房入院经历(孕周≥33周)的儿童,模型表现有所提高(曲线下面积为0.78;95%置信区间(0.69 - 0.87))。该模型对于识别低风险儿童最为有用。在分层预防干预框架中应用此模型可能有益,预计为高风险的儿童将接受进一步筛查,以确定所需的干预水平。在考虑将其应用于实际之前,需要进行外部验证和实施研究。