Poor Functional Outcomes in Pediatric Intensive Care Survivors in Brazil: Prevalence and Associated Factors.
Vanessa Campes DannenbergGabrielle Costa BorbaPaula M E RovedderPaulo R A CarvalhoPublished in: Journal of pediatric intensive care (2021)
Survivors of pediatric critical illnesses develop temporary or permanent functional impairments. We do not have enough data on Brazilian children, however, and the available evidence mainly shows results from high-income countries. Our objective was to assess changes in the functional status of children and adolescents surviving critical illnesses in Brazil, and to identify which factors contribute to these functional changes at pediatric intensive care unit (PICU) discharge. To develop this cross-sectional study, two researchers blinded to previous patient information applied the Functional Status Scale (FSS) with patients and caregivers at two different times in a tertiary PICU. The FSS examines six function domains as follows: (1) mental status, (2) sensory functioning, (3) communication, (4) motor functioning, (5) feeding, and (6) respiratory status. The functional decline/poor outcome was defined as an increase in points sufficient to alter the FSS total scores at discharge when comparing to the total baseline score. A total of 303 patients completed the study. Of these, 199 (66%) were with previous chronic conditions. The prevalence of functional decrease was 68% at PICU discharge. Young age (<12 months) and mechanical ventilation time ≥11 days increased by 1.44 (95% confidence interval [CI]: 1.20-1.74, p < 0.001) and 1.74 (95% CI: 1.49-2.03, p < 0.001), respectively, the chances of poor functional results at PICU discharge. This study is the first in Brazil to show that during the episode of critical illness, young age (≤12 months) and duration of invasive mechanical ventilation independently increased the chances of functional impairment in children.
Keyphrases
- mechanical ventilation
- intensive care unit
- young adults
- acute respiratory distress syndrome
- end stage renal disease
- prognostic factors
- newly diagnosed
- ejection fraction
- healthcare
- machine learning
- chronic kidney disease
- clinical trial
- peritoneal dialysis
- physical activity
- palliative care
- social media
- health information
- deep learning