ArticlePediatric pulmonology2015
Automated analysis of respiratory behavior in extremely preterm infants and extubation readiness.
Article in Pediatric pulmonology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Peri-extubation settings in preterm neonates: a systematic review and meta-analysis.Journal of perinatology : official journal of the California Perinatal Association · 2024Pooled it
- Predictors of extubation success for premature infants.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.BMC pulmonary medicine · 2024Article
- Towards precision medicine for extubation of extremely preterm infants: is variability the spice of life?Pediatric research · 2023Article
- Automated prediction of extubation success in extremely preterm infants: the APEX multicenter study.Pediatric research · 2023Article
- Can Fraction of Inspired Oxygen Predict Extubation Failure in Preterm Infants?Children (Basel, Switzerland) · 2022Article
- Diaphragmatic activity and neural breathing variability during a 5-min endotracheal continuous positive airway pressure trial in extremely preterm infants.Pediatric research · 2021Article
- Extubation Readiness in Preterm Infants: Evaluating the Role of Monitoring Intermittent Hypoxemia.Children (Basel, Switzerland) · 2021Article
- Prediction of Extubation readiness in extremely preterm infants by the automated analysis of cardiorespiratory behavior: study protocol.BMC pediatrics · 2017Observational
- Scoring Tools for the Analysis of Infant Respiratory Inductive Plethysmography Signals.PloS one · 2015Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRates of extubation failure of extremely preterm infants remain high. Analysis of breathing patterns variability during spontaneous breathing under endotracheal tube continuous positive airway pressure (ETT-CPAP) is a potential tool to predict extubation readiness.
objectiveTo investigate if automated analysis of respiratory signals would reveal differences in respiratory behavior between infants that were successfully extubated or not.
methodsRespiratory Inductive Plethysmography (RIP) signals were recorded during ETT-CPAP just prior to extubation. Signals were digitized, and analyzed using an Automated Unsupervised Respiratory Event Analysis (AUREA). Extubation failure was defined as reintubation within 72 hr. Statistical differences between infants who were successfully extubated or failed were calculated.
resultsA total of 56 infants were enrolled and one was excluded due to instability during the ETT-CPAP; 11 out of 55 infants studied failed extubation (20%). No differences in demographics were observed between the success and failure groups. Significant differences on the variability of some respiratory parameters or 'metrics' estimated by AUREA were observed between the 2 groups. Indeed, a simple classification using the variability of two metrics of respiratory behavior predicted extubation failure with high accuracy.
conclusionAutomated analysis of respiratory behavior during a short ETT-CPAP period may help in the prediction of extubation readiness in extremely preterm infants.
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