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Published on: February 15, 2017
Classifying multicenter approaches to invasive mechanical ventilation for infants with bronchopulmonary dysplasia
Matthew J Kielt1, L Dupree Hatch2, Jonathan C Levin3
1Division of Neonatology, Department of Pediatrics, Nationwide Children's Hospital and The Ohio State University College of Medicine, Columbus, Ohio, USA.
Insights
Ventilator settings in infants with severe bronchopulmonary dysplasia (BPD) were analyzed, revealing three distinct ventilation strategies. Further research is needed to link these strategies to clinical outcomes.
Area of Science:
- Neonatal Medicine
- Pediatric Respiratory Medicine
- Critical Care Medicine
Background:
- Evidence-based ventilation strategies for severe bronchopulmonary dysplasia (BPD) are not well-defined.
- Contemporary ventilation approaches may represent distinct BPD care strategies.
- Characterizing these strategies can improve clinical trial design for BPD.
Purpose of the Study:
- To test if unsupervised clustering of ventilator settings identifies distinct physiological approaches in infants with severe BPD.
- To analyze ventilator data from a multicenter cohort of infants with severe BPD.
Main Methods:
- Secondary analysis of a multicenter point prevalence study.
- Invasive mechanical ventilation data from infants with severe BPD were used.
- Ward's hierarchical clustering analysis (HCA) was applied to mean airway pressure (MAP), positive end-expiratory pressure (PEEP), respiratory rate, and inspiratory time (Ti).
Main Results:
- Seventy-eight infants with severe BPD from 14 centers were included.
- HCA identified three discrete clusters with strong stability.
- Significant differences in PEEP, MAP, rate, Ti, and peak inspiratory pressure (PIP) were observed between clusters (p < 0.0001).
Conclusions:
- Unsupervised clustering of ventilator settings identified three distinct mechanical ventilation approaches in infants with severe BPD.
- Prospective trials are necessary to determine associations with BPD phenotypes.
- Further investigation is needed to assess differential effects on respiratory outcomes.
Introduction:
Evidence-based ventilation strategies for infants with severe bronchopulmonary dysplasia (BPD) remain unknown. Determining whether contemporary ventilation approaches cluster as specific BPD strategies may better characterize care and enhance the design of clinical trials. The objective of this study was to test the hypothesis that unsupervised, multifactorial clustering analysis of point prevalence ventilator setting data would classify a discrete number of physiology-based approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD.
Methods:
We performed a secondary analysis of a multicenter point prevalence study of infants with severe BPD treated with invasive mechanical ventilation. We clustered the cohort by mean airway pressure (MAP), positive end expiratory pressure (PEEP), set respiratory rate, and inspiratory time (Ti) using Ward's hierarchical clustering analysis (HCA).
Results:
Seventy-eight patients with severe BPD were included from 14 centers. HCA classified three discrete clusters as determined by an agglomerative coefficient of 0.97. Cluster stability was relatively strong as determined by Jaccard coefficient means of 0.79, 0.85, and 0.77 for clusters 1, 2, and 3, respectively. The median PEEP, MAP, rate, Ti, and PIP differed significantly between clusters for each comparison by Kruskall-Wallis testing (p < 0.0001).
Conclusions:
In this study, unsupervised clustering analysis of ventilator setting data identified three discrete approaches to mechanical ventilation in a multicenter cohort of infants with severe BPD. Prospective trials are needed to determine whether these approaches to mechanical ventilation are associated with specific severe BPD clinical phenotypes and differentially modify respiratory outcomes.
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