阻塞性睡眠呼吸暂停患儿颅面发育特征预测模型的建立及外部验证。

IF 3 2区 医学 Q2 CLINICAL NEUROLOGY Nature and Science of Sleep Pub Date : 2024-12-21 eCollection Date: 2024-01-01 DOI:10.2147/NSS.S492714
Yonglong Su, Zitong Wang, Huanhuan Chang, Simin Zhu, Yanuo Zhou, Zine Cao, Lina Ma, Yuqi Yuan, Yushan Xie, Xiaoxin Niu, Chendi Lu, Yitong Zhang, Haiqin Liu, Na Shao, Libo Yin, Chao Si, Xiaoyong Ren, Yewen Shi
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引用次数: 0

摘要

目的:分析阻塞性睡眠呼吸暂停(OSA)患儿颅面结构及软组织发育特点,建立预测模型并进行评价。方法:对2017年7月至2024年3月在西安交通大学第二附属医院耳鼻喉头颈外科就诊的747名2-12岁儿童(患者337例,对照组410例)进行回顾性研究。获得侧位头x线片以比较头侧测量值。采用LASSO回归分析建立临床预测模型。我们分析了来自西安儿童医院的300名儿童进行外部验证。结果:OSA患儿体重较高,扁桃体分级较高,AN比(腺样体与骨骼上气道宽度之比)较大,扁桃体半径较大,颅底与上颌骨夹角较小(SNA),颅底与下颌骨夹角较小(SNB),舌骨至下颌平面距离较大(H-MP),第三颈椎至舌骨距离较小(H-C)。软腭厚度(SPT)大于对照组,软腭倾角小于对照组(p < 0.05)。建立2-12岁组预测模型(AUC为0.812 [95% CI: 0.781-0.842])。针对学龄前儿童(AUC为0.769 [95% CI: 0.725-0.814])和学龄儿童(AUC为0.854 [95% CI: 0.812-0.895])建立了年龄特异性预测模型。结论:我们的研究结果支持舌骨、上颌骨、下颌骨和软腭等颅面结构在儿童OSA中的重要作用。儿童OSA的年龄分层预测模型显示不同年龄组的参数不同,这强调了在未来的研究中按年龄分层的必要性。所设计的预测模型将极大地帮助卫生保健从业人员快速识别。
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Craniofacial Development Characteristics in Children with Obstructive Sleep Apnea for Establishment and External Validation of the Prediction Model.

Purpose: Aimed to analyze the developmental characteristics of craniofacial structures and soft tissues in children with obstructive sleep apnea (OSA) and to establish and evaluate prediction model.

Methods: It's a retrospective study comprising 747 children aged 2-12 years (337 patients and 410 controls) visited the Department of Otolaryngology-Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University (July 2017 to March 2024). Lateral head radiographs were obtained to compare the cephalometric measurements. The clinical prediction model was constructed using LASSO regression analysis. We analyzed 300 children from the Xi'an Children's Hospital for external validation.

Results: Children with OSA had a higher body mass, a higher tonsil grade, larger AN ratio (ratio of the adenoids to the skeletal upper airway width), larger radius of the tonsils, a smaller angle between the skull base and maxilla (SNA) and smaller angle between the skull base and mandible (SNB), a larger distance from the hyoid to the mandibular plane (H-MP) and smaller distance between the third cervical vertebra and hyoid (H-C), a larger thickness of the soft palate (SPT) and smaller inclination angle of the soft palate than those of the controls (all p < 0.05). A prediction model was constructed for 2-12 years group (AUC of 0.812 [95% CI: 0.781-0.842]). Age-specific prediction models were developed for preschool children (AUC of 0.769 [95% CI: 0.725-0.814]), for school-aged children (AUC of 0.854 [95% CI: 0.812-0.895]).

Conclusion: Our study findings support the important role of craniofacial structures such as the hyoid, maxilla, mandible, and soft palate in pediatric OSA. Age-stratified predictive models for pediatric OSA indicated varying parameters across different age groups which underscore the necessity for stratifying by age in future research. The prediction model designed will greatly assist health care practitioners with rapidly identifying.

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来源期刊
Nature and Science of Sleep
Nature and Science of Sleep Neuroscience-Behavioral Neuroscience
CiteScore
5.70
自引率
5.90%
发文量
245
审稿时长
16 weeks
期刊介绍: Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep. Specific topics covered in the journal include: The functions of sleep in humans and other animals Physiological and neurophysiological changes with sleep The genetics of sleep and sleep differences The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness Sleep changes with development and with age Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause) The science and nature of dreams Sleep disorders Impact of sleep and sleep disorders on health, daytime function and quality of life Sleep problems secondary to clinical disorders Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health) The microbiome and sleep Chronotherapy Impact of circadian rhythms on sleep, physiology, cognition and health Mechanisms controlling circadian rhythms, centrally and peripherally Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms Epigenetic markers of sleep or circadian disruption.
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