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Identifying Long-Term Morbidities and Health Trajectories After Prolonged Mechanical Ventilation in Children Using State All Payer Claims Data.
Maddux, Aline B; Mourani, Peter M; Miller, Kristen; Carpenter, Todd C; LaVelle, Jaime; Pyle, Laura L; Watson, R Scott; Bennett, Tellen D.
Afiliação
  • Maddux AB; Department of Pediatrics, Section of Critical Care Medicine, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO.
  • Mourani PM; Department of Pediatrics, Section of Critical Care, University of Arkansas for Medical Sciences and Arkansas Children's, Little Rock, AR.
  • Miller K; Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.
  • Carpenter TC; Department of Pediatrics, Section of Critical Care Medicine, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO.
  • LaVelle J; Section of Pediatric Critical Care Medicine, Children's Hospital Colorado, Aurora, CO.
  • Pyle LL; Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.
  • Watson RS; Department of Biostatistics and Informatics, Colorado School of Public Health, Children's Hospital Colorado, Aurora, CO.
  • Bennett TD; Department of Pediatrics, Division of Pediatric Critical Care Medicine, University of Washington School of Medicine and Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA.
Pediatr Crit Care Med ; 23(4): e189-e198, 2022 04 01.
Article em En | MEDLINE | ID: mdl-35250002
OBJECTIVES: To identify postdischarge outcome phenotypes and risk factors for poor outcomes using insurance claims data. DESIGN: Retrospective cohort study. SETTING: Single quaternary center. PATIENTS: Children without preexisting tracheostomy who required greater than or equal to 3 days of invasive mechanical ventilation, survived the hospitalization, and had postdischarge insurance eligibility in Colorado's All Payer Claims Database. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used unsupervised machine learning to identify functional outcome phenotypes based on claims data representative of postdischarge morbidities. We assessed health trajectory by comparing change in the number of insurance claims between quarters 1 and 4 of the postdischarge year. Regression analyses identified variables associated with unfavorable outcomes. The 381 subjects had median age 3.3 years (interquartile range, 0.9-12 yr), and 147 (39%) had a complex chronic condition. Primary diagnoses were respiratory (41%), injury (23%), and neurologic (11%). We identified three phenotypes: lower morbidity (n = 300), higher morbidity (n = 62), and 1-year nonsurvivors (n = 19). Complex chronic conditions most strongly predicted the nonsurvivor phenotype. Longer PICU stays and tracheostomy placement most strongly predicted the higher morbidity phenotype. Patients with high but improving postdischarge resource use were differentiated by high illness severity and long PICU stays. Patients with persistently high or increasing resource use were differentiated by complex chronic conditions and tracheostomy placement. CONCLUSIONS: New morbidities are common after prolonged mechanical ventilation. Identifying phenotypes at high risk of postdischarge morbidity may facilitate prognostic enrichment in clinical trials.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Respiração Artificial / Assistência ao Convalescente Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Pediatr Crit Care Med Assunto da revista: PEDIATRIA / TERAPIA INTENSIVA Ano de publicação: 2022 Tipo de documento: Article País de publicação: Estados Unidos
Texto completo
Adicionar na Minha BVS
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XML
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Respiração Artificial / Assistência ao Convalescente Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Pediatr Crit Care Med Assunto da revista: PEDIATRIA / TERAPIA INTENSIVA Ano de publicação: 2022 Tipo de documento: Article País de publicação: Estados Unidos