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Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate
Premananda Indic1, Elisabeth Bloch-Salisbury, Frank Bednarek
1Department of Anesthesia and Critical Care, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. Premananda.Indic@umassmed.edu
Insights
This study introduces a new method to assess cardio-respiratory interactions in preterm infants, finding significant coupling during breathing. This approach aids in understanding infant development and cardiopulmonary function.
Area of Science:
- Developmental physiology
- Infant cardiopulmonary function
- Systems biology
Background:
- Cardio-respiratory interactions are minimal in early human development.
- Assessing these interactions is crucial for infant development indicators.
- Existing methods for infant cardiopulmonary assessment are limited.
Purpose of the Study:
- To present a novel methodological framework for analyzing cardiovascular variables in preterm infants.
- To adapt mathematical tools for quantifying cardiovascular control in developing systems.
- To assess cardio-respiratory interactions in preterm infants.
Main Methods:
- Applied a tailored multivariate autoregressive analysis to 11 preterm infants.
- Quantified cardio-respiratory interactions using coherence and gain via causal approaches.
- Utilized surrogate data analysis to determine interaction significance.
Main Results:
- Significantly higher coherence observed in the eupneic breathing frequency range.
- Surrogate data analysis confirmed the significance of these interactions.
- Cardio-respiratory coupling was detected in preterm infants.
Conclusions:
- The study validates the new methodological framework for infant cardio-respiratory analysis.
- Confirmed the presence of cardio-respiratory coupling in early development.
- Mild mechanosensory intervention showed potential to enhance these interactions.
Background:
Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system.
Methods:
We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention.
Results:
Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges.
Conclusions:
Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach.
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