Abstract：
OBJECTIVE: To investigate risk factors for metabolic bone disease (MBD) in preterm infants and establish a nomogram model for predicting MBD risk.
METHODS: A total of 1104 preterm infants were enrolled, among whom 809 were included in the modelling set and 295 were included in the validation set. The modelling set was divided into MBD (n = 185) and non-MBD (n = 624) groups. A multivariate logistic regression analysis was used to investigate the independent risk factors for MBD. R software was used to plot the nomogram model, which was then validated by the data of the validation set. Receiver operating characteristic (ROC) and calibration curves were used to evaluate the nomogram model\'s performance, and the clinical decision curve was used to assess the clinical practicability of the model.
RESULTS: Gestational age, time of trophic feeding initiation, parenteral nutrition duration, necrotizing enterocolitis, bronchopulmonary dysplasia, cholestasis and sepsis were independent risk factors for MBD in preterm infants (P < 0.05). The ROC curve of the modelling set had an area under the curve (AUC) of 0.801; the risk prediction value of 0.196 corresponding to the maximum Youden index was the best value, and the prediction critical value was 125 points. The ROC curve of the validation set had an AUC of 0.854. The calibration curve analysis showed good accuracy and consistency between the model\'s predicted and actual values.
CONCLUSIONS: The nomogram model provides an efficient tool for the early assessment of MBD risk. Preterm infants with scores ≥ 125 should receive close attention and interventions in the early stage.
BACKGROUND: • The incidence and severity of MBD are inversely proportional to gestational age and birth weight. Bone loss can lead to prolonged hospital stay, ventilator dependence, pathological fractures and short stature.
BACKGROUND: • Gestational age, time of trophic feeding initiation, parenteral nutrition duration, necrotizing enterocolitis, bronchopulmonary dysplasia, cholestasis and sepsis were independent risk factors for MBD in preterm infants. The nomogram model provides an efficient tool for the early assessment of MBD risk.
METHODS: A total of 1104 preterm infants were enrolled, among whom 809 were included in the modelling set and 295 were included in the validation set. The modelling set was divided into MBD (n = 185) and non-MBD (n = 624) groups. A multivariate logistic regression analysis was used to investigate the independent risk factors for MBD. R software was used to plot the nomogram model, which was then validated by the data of the validation set. Receiver operating characteristic (ROC) and calibration curves were used to evaluate the nomogram model\'s performance, and the clinical decision curve was used to assess the clinical practicability of the model.
RESULTS: Gestational age, time of trophic feeding initiation, parenteral nutrition duration, necrotizing enterocolitis, bronchopulmonary dysplasia, cholestasis and sepsis were independent risk factors for MBD in preterm infants (P < 0.05). The ROC curve of the modelling set had an area under the curve (AUC) of 0.801; the risk prediction value of 0.196 corresponding to the maximum Youden index was the best value, and the prediction critical value was 125 points. The ROC curve of the validation set had an AUC of 0.854. The calibration curve analysis showed good accuracy and consistency between the model\'s predicted and actual values.
CONCLUSIONS: The nomogram model provides an efficient tool for the early assessment of MBD risk. Preterm infants with scores ≥ 125 should receive close attention and interventions in the early stage.
BACKGROUND: • The incidence and severity of MBD are inversely proportional to gestational age and birth weight. Bone loss can lead to prolonged hospital stay, ventilator dependence, pathological fractures and short stature.
BACKGROUND: • Gestational age, time of trophic feeding initiation, parenteral nutrition duration, necrotizing enterocolitis, bronchopulmonary dysplasia, cholestasis and sepsis were independent risk factors for MBD in preterm infants. The nomogram model provides an efficient tool for the early assessment of MBD risk.
摘要：
目的：探讨早产儿代谢性骨病（MBD）的危险因素，建立预测MBD风险的列线图模型。
方法：共纳入1104名早产儿，其中809人被纳入模型集，295人被纳入验证集。模型集分为MBD组(n=185)和非MBD组(n=624)。采用多因素logistic回归分析探讨MBD的独立危险因素。使用R软件绘制列线图模型，然后通过验证集的数据进行验证。接收器工作特性(ROC)和校准曲线用于评估列线图模型的性能,临床决策曲线评估模型的临床实用性。
结果：孕龄，开始营养喂养的时间，肠外营养持续时间，坏死性小肠结肠炎,支气管肺发育不良,胆汁淤积和脓毒症是早产儿MBD的独立危险因素(P<0.05)。建模集的ROC曲线的曲线下面积（AUC）为0.801；最大Youden指数对应的风险预测值为0.196是最佳值，预测临界值为125点。验证集的ROC曲线具有0.854的AUC。校准曲线分析显示模型预测值与实际值具有良好的准确性和一致性。
结论：列线图模型为早期评估MBD风险提供了有效的工具。评分≥125的早产儿应在早期给予密切关注和干预。
背景：•MBD的发生率和严重程度与胎龄和出生体重成反比。骨质流失会导致住院时间延长,呼吸机依赖，病理性骨折和身材矮小。
背景：•孕龄，开始营养喂养的时间，肠外营养持续时间，坏死性小肠结肠炎,支气管肺发育不良,胆汁淤积和脓毒症是早产儿MBD的独立危险因素。列线图模型为早期评估MBD风险提供了有效的工具。
方法：共纳入1104名早产儿，其中809人被纳入模型集，295人被纳入验证集。模型集分为MBD组(n=185)和非MBD组(n=624)。采用多因素logistic回归分析探讨MBD的独立危险因素。使用R软件绘制列线图模型，然后通过验证集的数据进行验证。接收器工作特性(ROC)和校准曲线用于评估列线图模型的性能,临床决策曲线评估模型的临床实用性。
结果：孕龄，开始营养喂养的时间，肠外营养持续时间，坏死性小肠结肠炎,支气管肺发育不良,胆汁淤积和脓毒症是早产儿MBD的独立危险因素(P<0.05)。建模集的ROC曲线的曲线下面积（AUC）为0.801；最大Youden指数对应的风险预测值为0.196是最佳值，预测临界值为125点。验证集的ROC曲线具有0.854的AUC。校准曲线分析显示模型预测值与实际值具有良好的准确性和一致性。
结论：列线图模型为早期评估MBD风险提供了有效的工具。评分≥125的早产儿应在早期给予密切关注和干预。
背景：•MBD的发生率和严重程度与胎龄和出生体重成反比。骨质流失会导致住院时间延长,呼吸机依赖，病理性骨折和身材矮小。
背景：•孕龄，开始营养喂养的时间，肠外营养持续时间，坏死性小肠结肠炎,支气管肺发育不良,胆汁淤积和脓毒症是早产儿MBD的独立危险因素。列线图模型为早期评估MBD风险提供了有效的工具。
