80.2％（2717）的女性在出院队列中母乳喂养，而在验证队列中，只有82.1％（1390）进行母乳喂养。最终模型中的预测因素是：出生时的母亲年龄；BMI；儿童数量; 以前的母乳喂养；生育计划；引产；硬膜外镇痛；出生类型；早产; 多胎; 巨大儿；在第一个小时内开始母乳喂养和皮肤接触。开发队列的预测能力（ROC AUC）为0.76（95％CI ：0.74-0.78），而在验证队列中为0.74（ 95％CI：0.71-0.77）。
The benefits of breastfeeding for both mother and newborn have been widely demonstrated. However, breastfeeding rates at discharge are lower than recommended, so being able to identify women at risk of not breastfeeding at discharge could allow professionals to prioritise care.
To develop and validate a predictive model of exclusive breastfeeding at hospital discharge.
Retrospective cohort study on women who gave birth between 2014 and 2019 in Spain.
The data source was a questionnaire distributed through the Spanish breastfeeding associations. The development of the predictive model was made on a cohort of 3387 women and was validated on a cohort of 1694 women. A multivariate analysis was performed by means of logistic regression, and predictive ability was determined by areas under the ROC curve (AUC).
80.2% (2717) women exclusively breastfed at discharge in the derivation cohort, and 82.1% (1390) in the validation cohort. The predictive factors in the final model were: maternal age at birth; BMI; number of children; previous breastfeeding; birth plan; induced birth; epidural analgesia; type of birth; prematurity; multiple pregnancy; macrosomia; onset of breastfeeding within the first hour; and skin-to-skin contact. The predictive ability (ROC AUC) in the derivation cohort was 0.76 (CI 95%: 0.74-0.78), while in the validation cohort it was 0.74 (CI 95%: 0.71-0.77).
A predictive model of exclusive maternal breastfeeding at hospital discharge has been developed, based on thirteen variables, with satisfactory predictive ability in both the derivation cohort and the validation cohort according to the Swets' criteria. This model can identify women who are at high risk of not breastfeeding at hospital discharge.
Breastfeeding at hospital discharge
Predictive model validation