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Use of Latent Class Analysis to Predict Intensive Care Unit Admission and Mortality in Children with a Major Congenital Anomaly.
Belza, Christina; Szentkúti, Péter; Horváth-Puhó, Erzsébet; Ray, Joel G; Nelson, Katherine E; Grandi, Sonia M; Brown, Hilary K; Sørensen, Henrik Toft; Cohen, Eyal.
Afiliação
  • Belza C; Edwin S.H. Leong Centre for Health Children, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada; Transplant and Regenerative Medicine Centre, The Hospital for Sick Children, Toronto, ON, Ca
  • Szentkúti P; Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.
  • Horváth-Puhó E; Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark.
  • Ray JG; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada; St. Michael's Hospital Department of Medicine, University of Toronto, Toronto, ON, Canada.
  • Nelson KE; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada; Department of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada.
  • Grandi SM; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
  • Brown HK; Department of Health & Society, University of Toronto Scarborough, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada.
  • Sørensen HT; Department of Clinical Epidemiology, Aarhus University Hospital and Aarhus University, Aarhus, Denmark; Clinical Excellence Research Center, Stanford University, Stanford, CA.
  • Cohen E; Edwin S.H. Leong Centre for Health Children, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, C
J Pediatr ; 270: 114013, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38494089
ABSTRACT

OBJECTIVE:

To define major congenital anomaly (CA) subgroups and assess outcome variability based on defined subgroups. STUDY

DESIGN:

This population-based cohort study used registries in Denmark for children born with a major CA between January 1997 and December 2016, with follow-up until December 2018. We performed a latent class analysis (LCA) using child and family clinical and sociodemographic characteristics present at birth, incorporating additional variables occurring until age of 24 months. Cox proportional hazards regression models estimated hazard ratios (HRs) of pediatric mortality and intensive care unit (ICU) admissions for identified LCA classes.

RESULTS:

The study included 27 192 children born with a major CA. Twelve variables led to a 4-class solution (entropy = 0.74) (1) children born with higher income and fewer comorbidities (55.4%), (2) children born to young mothers with lower income (24.8%), (3) children born prematurely (10.0%), and (4) children with multiorgan involvement and developmental disability (9.8%). Compared with those in Class 1, mortality and ICU admissions were highest in Class 4 (HR = 8.9, 95% CI = 6.4-12.6 and HR = 4.1, 95% CI = 3.6-4.7, respectively). More modest increases were observed among the other classes for mortality and ICU admissions (Class 2 HR = 1.7, 95% CI = 1.1-2.5 and HR = 1.3, 95% CI = 1.1-1.4, respectively; Class 3 HR = 2.5, 95% CI = 1.5-4.2 and HR = 1.5, 95% CI = 1.3-1.9, respectively).

CONCLUSIONS:

Children with a major CA can be categorized into meaningful subgroups with good discriminative ability. These groupings may be useful for risk-stratification in outcome studies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Sistema de Registros / Análise de Classes Latentes Limite: Child, preschool / Female / Humans / Infant / Male / Newborn País/Região como assunto: Europa Idioma: En Revista: J Pediatr Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Canadá
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Sistema de Registros / Análise de Classes Latentes Limite: Child, preschool / Female / Humans / Infant / Male / Newborn País/Região como assunto: Europa Idioma: En Revista: J Pediatr Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Canadá