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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
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儿科长期COVID亚型:来自RECOVER计划的基于EHR的研究

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研究人员使用机器学习识别了儿科长期COVID的不同的临床表现或亚现型. 心脏呼吸系统问题是最常见的,其次是肌肉骨疼痛和神经精神疾病.

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科学领域:

  • 儿科医学 儿科医学 儿科医学
  • 计算生物学是一种计算生物学.
  • 传染病流行病学 传染病流行病学

背景情况:

  • 长期COVID在儿童中表现出多样化的症状,但不同的临床模式 (亚型) 仍然不清楚.
  • 了解儿科长期COVID亚表型对于有针对性的管理和研究至关重要.
  • 之前的研究还没有全面地描述长期COVID在没有复杂慢性疾病的儿科群体中的表现.

研究的目的:

  • 识别和描述儿科长期COVID的不同临床亚型.
  • 在大型儿科队列中利用无监督机器学习方法来发现子表型.
  • 分析电子健康记录数据,以寻找长期COVID呈现的模式.

主要方法:

  • 采用了无监督机器学习方法,这是Phe2Vec算法的扩展.
  • 确定了一组患有长期COVID且没有先前复杂慢性疾病的儿科患者 (<21岁).
  • 分析了来自38个机构的电子健康记录数据,涵盖了数万种临床概念.

主要成果:

  • 心肺呼吸表现是最常见的亚表型,在54%的患者中观察到.
  • 随后的子类型,按频率的下降顺序,包括肌肉骨疼痛,神经精神疾病,胃肠道症状,头痛和疲劳.
  • 机器学习模型成功地将患者分为不同的临床表现集群.

结论:

  • 已经确定了儿科长期COVID的不同临床亚现象,其中心肺呼吸系统参与是最常见的.
  • 这些发现为进一步研究不同儿科长期COVID表现的具体机制和治疗提供了基础.
  • 这项研究强调了机器学习在从大型电子健康记录数据集中剖析复杂的临床表型方面的实用性.