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Classification of Illness01:17

Classification of Illness

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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Respiratory Syncytial Virus Disease01:29

Respiratory Syncytial Virus Disease

Human respiratory syncytial virus (RSV) is a widespread pathogen that primarily targets infants and young children but also poses a serious health risk to elderly and immunocompromised individuals. Belonging to the Pneumoviridae family, RSV is a negative-sense, single-stranded RNA virus within the Pneumovirus genus. Its global health burden is significant, with millions of cases annually resulting in hospitalizations and mortality, particularly in resource-limited settings. Although most...
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Pediatric Long COVID Subphenotypes: An EHR-based study from the RECOVER program.

Vitaly Lorman1, L Charles Bailey1, Xing Song2

  • 1Applied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Medrxiv : the Preprint Server for Health Sciences
|October 7, 2024
PubMed
Summary
This summary is machine-generated.

Researchers identified distinct clinical presentations, or subphenotypes, of pediatric Long COVID using machine learning. Cardiorespiratory issues were most common, followed by musculoskeletal, neuropsychiatric, and gastrointestinal symptoms.

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Area of Science:

  • Pediatric Health
  • Infectious Diseases
  • Data Science

Background:

  • Long COVID presents with diverse symptoms in children, but distinct clinical patterns (subphenotypes) are not well-defined.
  • Understanding these pediatric Long COVID subphenotypes is crucial for targeted management and research.

Purpose of the Study:

  • To identify and characterize distinct clinical subphenotypes of pediatric Long COVID.
  • To analyze a cohort of pediatric patients without pre-existing complex chronic conditions.

Main Methods:

  • Utilized an unsupervised machine learning approach, an extension of the Phe2Vec algorithm.
  • Analyzed electronic health record data from 38 institutions for patients under 21 with Long COVID.
  • Employed tens of thousands of clinical concepts to represent patient histories and identify similar presentations.

Main Results:

  • Identified multiple pediatric Long COVID subphenotypes.
  • Cardiorespiratory presentations were the most frequent, observed in 54% of patients.
  • Other common subphenotypes included musculoskeletal pain, neuropsychiatric conditions, gastrointestinal symptoms, headache, and fatigue, in decreasing order of frequency.

Conclusions:

  • Distinct clinical subphenotypes of pediatric Long COVID exist.
  • Cardiorespiratory, musculoskeletal, and neuropsychiatric symptoms represent common presentations.
  • Further research into these subphenotypes can inform clinical care and therapeutic strategies for pediatric Long COVID.