Prabhjot K Bedi1, Kristie DeHaan2, Joanna E MacLean1,3, Maria L Castro-Codesal1,3. 1. Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada. 2. Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada. 3. Women and Children's Health Research Institute, University of Alberta, Edmonton, Canada.
Abstract
BACKGROUND: Noninvasive ventilation (NIV) is a first-line therapy for sleep-related breathing disorders and chronic respiratory insufficiency. Evidence about predictors that may impact long-term NIV outcomes, however, is scarce. The aim of this study is to determine demographic, clinical, and technology-related predictors of long-term NIV outcomes. METHODS: A 10-year multicentred retrospective review of children started on long-term continuous or bilevel positive airway pressure (CPAP or BPAP) in Alberta. Demographic, technology-related, and longitudinal clinical data were collected. Long-term outcomes examined included ongoing NIV use, discontinuation due to improvement in underlying conditions, switch to invasive mechanical ventilation (IMV) or death, patient/family therapy declination, transfer of services, and hospital admissions. RESULTS: A total of 622 children were included. Both younger age and CPAP use predicted higher likelihood for NIV discontinuation due to improvement in underlying conditions (p < .05 and p < .01). Children with upper airway disorders or bronchopulmonary dysplasia were less likely to continue NIV (p < .05), while presence of central nervous system disorders had a higher likelihood of hospitalizations (p < .01). The presence of obesity/metabolic syndrome and early NIV-associated complications predicted higher risk for NIV declination (p < .05). Children with more comorbidities or use of additional therapies required more hospitalizations (p < .05 and p < .01) and the latter also predicted higher risk for being switched to IMV or death (p < .001). CONCLUSIONS: Demographic, clinical data, and NIV type impact long-term NIV outcomes and need to be considered during initial discussions about therapy expectations with families. Knowledge of factors that may impact long-term NIV outcomes might help to better monitor at-risk patients and minimize adverse outcomes.
BACKGROUND: Noninvasive ventilation (NIV) is a first-line therapy for sleep-related breathing disorders and chronic respiratory insufficiency. Evidence about predictors that may impact long-term NIV outcomes, however, is scarce. The aim of this study is to determine demographic, clinical, and technology-related predictors of long-term NIV outcomes. METHODS: A 10-year multicentred retrospective review of children started on long-term continuous or bilevel positive airway pressure (CPAP or BPAP) in Alberta. Demographic, technology-related, and longitudinal clinical data were collected. Long-term outcomes examined included ongoing NIV use, discontinuation due to improvement in underlying conditions, switch to invasive mechanical ventilation (IMV) or death, patient/family therapy declination, transfer of services, and hospital admissions. RESULTS: A total of 622 children were included. Both younger age and CPAP use predicted higher likelihood for NIV discontinuation due to improvement in underlying conditions (p < .05 and p < .01). Children with upper airway disorders or bronchopulmonary dysplasia were less likely to continue NIV (p < .05), while presence of central nervous system disorders had a higher likelihood of hospitalizations (p < .01). The presence of obesity/metabolic syndrome and early NIV-associated complications predicted higher risk for NIV declination (p < .05). Children with more comorbidities or use of additional therapies required more hospitalizations (p < .05 and p < .01) and the latter also predicted higher risk for being switched to IMV or death (p < .001). CONCLUSIONS: Demographic, clinical data, and NIV type impact long-term NIV outcomes and need to be considered during initial discussions about therapy expectations with families. Knowledge of factors that may impact long-term NIV outcomes might help to better monitor at-risk patients and minimize adverse outcomes.