中国实用儿科杂志

中国实用儿科杂志 ›› 2026, Vol. 41 ›› Issue (7): 610-616.DOI: 10.19538/j.ek2026070614

• 综述 • 上一篇    

儿童睡眠评估工具选择策略及临床诊治应用进展

  

  1. 上海交通大学医学院附属上海儿童医学中心  a 护理部，b 转化医学研究所，c 呼吸科，上海  200127
  • 出版日期:2026-07-06 发布日期:2026-09-17
  • 通讯作者: 沈碧玉，电子信箱：shenbiyu@126.com；张静，电子信箱：zhangjing@scmc.com.cn
  • 基金资助:
    上海申康医院发展中心管理研究项目（2024SKMR-29）；创新生态建设计划“科普与科技传播”项目（25DZ2302500）；儿联体医院管理科研项目（SHDB-CM-202401）

Selection strategy of pediatric sleep assessment tools and progress in the clinical application

  1. *Shanghai Children’s Medical Center，Shanghai Jiao Tong University School of Medicine，Shanghai  200127，China
  • Online:2026-07-06 Published:2026-09-17

摘要： 儿童睡眠在神经发育、情绪调节及生长发育中发挥关键作用，有效且科学的睡眠评估是早期发现与干预睡眠障碍的基础。当前临床可选的儿童睡眠评估工具多样，涵盖不同评估目的、适用年龄及操作复杂度。儿科临床医生面临的挑战是如何基于患儿具体临床表现和环境条件，合理选择并整合多种评估工具，形成科学、系统的诊疗路径。该文按照儿童不同年龄阶段对国内外常用的主观和客观儿童睡眠评估工具进行梳理，分析并比较这些工具的优缺点及其适用性，结合最新指南及AI 前沿研究，探讨常见儿童睡眠障碍（失眠、睡眠呼吸障碍、昼夜节律紊乱）的临床诊治流程，旨在为儿科临床工作者提供科学、创新的实践指导。

关键词: 睡眠评估, 多导睡眠监测, 人工智能, 儿童睡眠障碍

Abstract: Pediatric sleep plays a critical role in neurodevelopment，emotional regulation，and physical growth.Valid and scientific sleep assessment is the cornerstone for early detection and intervention of sleep disorders.Currently，various pediatric sleep assessment tools are available for clinical use，differing in purpose，age applicability，and operational complexity. A key challenge for pediatricians is to rationally select and integrate these tools based on the child’s clinical presentation and environmental conditions to form a systematic diagnostic and therapeutic pathway.This article reviews commonly used subjective and objective pediatric sleep assessment tools by age group，analyzes their strengths，limitations，and applicability，and discusses clinical management workflows for common pediatric sleep disorders（insomnia，sleep-disordered breathing，circadian rhythm disorders）in light of the latest guidelines and cutting-edge AI research.It aims to provide evidence-based and innovative practical guidance for pediatric clinicians.

Key words: sleep assessment, pediatric sleep disorders, polysomnography, artificial intelligence