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开发并外部验证了一个列线图,用于预测儿童阻塞性睡眠呼吸暂停。

Development and external validation of a Nomogram to predict obstructive sleep apnea in Children.

机构信息

Department of Otorhinolaryngology Head and Neck Surgery, Xi'an Jiaotong University, Xi'an, China.

Department of Otorhinolaryngology Head and Neck Surgery, Xi'an Children's Hospital, Xi'an, China.

出版信息

Eur J Pediatr. 2024 Nov 29;184(1):53. doi: 10.1007/s00431-024-05898-5.

Abstract

UNLABELLED

To develop a nomogram model to predict obstructive sleep apnea in children and perform an external validation. 864 children who underwent polysomnography at our hospital were randomly assigned to a training cohort and an internal validation cohort (7:3) and 292 children at another hospital were enrolled for external validation. Logistic regression analyses were performed to explore the risk factors for obstructive sleep apnea. Features selected by least absolute shrinkage and selection operator logistic regression were enrolled to develop a predictive nomogram, which was assessed by discrimination, calibration, and clinical benefit in three cohorts and six subgroups from the all development cohort: age, gender, nonobese children, and term children. Furthermore, the nomogram was compared with the Obstructive Sleep Apnea-18 questionnaire. Six features were selected to construct the nomogram: adenoid hypertrophy, tonsil size 2, tonsil size 3, birth weight, total sleep time, and the lowest oxygen saturation. The areas under the curve of the nomogram in the training cohort [0.784, 95%CI (0.746-0.821)], internal validation cohort [0.780 (0.721-0.840)], and external validation cohort [0.782 (0.726-0.838)] were higher than those of the OSA-18 and remained stable in subgroups. Calibration curves and decision curve analysis both exhibited favorable performance.

CONCLUSION

The nomogram with satisfactory performance was constructed as a robust tool for evaluating the risk of obstructive sleep apnea in children.

WHAT IS KNOWN

• Obstructive sleep apnea (OSA) is common in children and is closely related to multiple system dysfunction, while still remains underdiagnosed and undertreated because of the limited usage of polysomnography. • A prediction model for accurately identifying OSA in children is warranted in a subsequent recommendation of essential PSG to provide proper treatment and delay the occurrence of OSA complications.

WHAT IS NEW

• Adenoid hypertrophy, tonsil size 2, tonsil size 3, birth weight, total sleep time, and the lowest oxygen saturation were risk factors of children with OSA. • This nomogram with satisfactory performance was a robust tool for evaluating the risk of OSA in children.

摘要

目的

开发一种预测儿童阻塞性睡眠呼吸暂停(obstructive sleep apnea,OSA)的列线图模型,并进行外部验证。

方法

本研究纳入了 864 名在我院行多导睡眠图(polysomnography,PSG)检查的患儿,随机分为训练队列和内部验证队列(7:3),并纳入了另一家医院的 292 名患儿进行外部验证。采用 logistic 回归分析探讨 OSA 的危险因素。采用最小绝对收缩和选择算子 logistic 回归选择特征,并纳入预测列线图,通过在三个队列和全开发队列的六个亚组中评估其区分度、校准度和临床获益来评估其性能:年龄、性别、非肥胖儿童和足月儿童。此外,将该列线图与阻塞性睡眠呼吸暂停-18 问卷(Obstructive Sleep Apnea-18 questionnaire,OSA-18)进行比较。选择了 6 个特征来构建列线图:腺样体肥大、扁桃体 2 度肿大、扁桃体 3 度肿大、出生体重、总睡眠时间和最低血氧饱和度。训练队列中列线图的曲线下面积(area under the curve,AUC)为 0.784[95%CI(0.746-0.821)],内部验证队列为 0.780(0.721-0.840),外部验证队列为 0.782(0.726-0.838),均高于 OSA-18,且在亚组中保持稳定。校准曲线和决策曲线分析均显示出良好的性能。

结论

该列线图性能满意,可作为评估儿童 OSA 风险的一种可靠工具。

已知内容

•阻塞性睡眠呼吸暂停(obstructive sleep apnea,OSA)在儿童中很常见,与多系统功能障碍密切相关,但由于 PSG 的应用受限,其仍然存在诊断不足和治疗不足的情况。•需要建立一种预测模型,以便准确识别儿童 OSA,从而推荐进行必要的 PSG,提供适当的治疗,并延缓 OSA 并发症的发生。

新增内容

•腺样体肥大、扁桃体 2 度肿大、扁桃体 3 度肿大、出生体重、总睡眠时间和最低血氧饱和度是儿童 OSA 的危险因素。•该列线图性能满意,是评估儿童 OSA 风险的一种可靠工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec5c/11607062/dbf0a4c409b6/431_2024_5898_Fig1_HTML.jpg

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